Comparison Between Different Electrode Arrays In ...

Ministry of Higher Education and Scientific Research University of Baghdad / College of Science Department of Geology

Comparison Between Different Electrode Arrays In Delineating Aquifer Boundaries By using 1D And 2D Techniques In North Badra Area Eastern Iraq.

A Thesis Submitted to the college of Science / University of Baghdad In partial fulfillment of the requirements for the degree of Master of Science in Geology (Geophysics) By Mohammed Mohsen Ali AL-Hameedawie B.Sc. 2005 Supervised by Dr. Jassim M. Thabit Assistant Professor

1435

2013

I certify that this thesis was prepared under my supervision at the University of Baghdad as a partial fulfillment of the requirements for the degree of Master of Science in Geology (Geophysics).

Signature: Advisor: Dr. Jassim M. Thabit Scientific title: Assist. Prof. Address: College of Science / University of Baghdad Date: / /2013

Approve of the college Committee of Graduate studies In view of the available recommendation I forward this dissertation for debate by examining committee.

Signature: Dr. Ahmed S. Al-Banna Scientific title: professor Address: Head of geologic Department / College of Science /University of Baghdad Date: / /2013

We certify that we have read this thesis and as examining committee examined

the student in its contents and that in our opinion it is adequate thesis for the degree of Master of Science in Geology (Geophysics).

Signature: Name: Dr. Khalid Sh. AL-Mukhtar Scientific title: Professor Address: University of Baghdad Date: / / 2013 (Chairman)

Signature: Name: Dr. Salman Z. Alabedeen Scientific title: Assist. Professor Address: University of Baghdad Date: / / 2013 (Member)

Signature: Name: Dr. Dhia A. AL-Mansouri Scientific title: Assist. Professor Address: University of AL-Mustansiriya Date: / / 2013 (Member)

Signature: Name: Dr. Jassim M. Thabit Scientific title: Assist. Professor Address: University of Baghdad Date: / / 2013 (Member)

Approve of the college Committee of Graduate studies Signature: Name: Dr. Salih M. Ali Scientific title: professor Dean of the college of Science Date: / / 2013

Dedication To the dearests father, mother, and brothers To the kindness wife, and lovely daughter To the first Iraqi geologist To all those who love me

Mohammed

Acknowledgement My best praises, and thanks to Allah the great and Almighty for what I have achieved that all this is from his vantage and the vantage of his messenger's Mohammed peace upon him and his Descendants. My best thanks to the dean of the college of science and to the head of Geological department in University of Baghdad. I would like to produce my grateful and deep thanks to my supervisor (Dr. Jassim, M. Thabit) for his valuable guidance, and advices along the whole work. I would also like to thank the general director of General Commission for Groundwater (Mr. Dhafir Abdullah) for providing requirements for achieving the field work, as well as offering all facilities to finish this work. Also, I would like to thanks (Dr. Ahmad Nadhum), the head of studies and investigation department, and (Mr. Dhia'a Basho) for their supporting. My thanks to the geophysicists (Mr. Ahmed, S. AL-Zubedi), (Dr. Firas, H. AL-Menshed), and (Mr. Ahmed, A. Al-Ibrahimi) for continues advices, and supporting in all work stages. My thanks to the geologists (Mr. Mahdi Alwan), and (Ameer, J. Al-Kilaby) for providing me the necessary information, and maps about study area. Also, my thanks to my friends the hydrologists (Hazim Karsm, Muthana Mahmuod, and Sawsan Abdul- Rahman) for their supporting and helping. Finally, my thanks to (Mr. Amer), and (Mr. Youssef) for helping in the fieldwork

Mohammed

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Abstract The study area occupies about (101) Km2, and it is located within Wasit province, north Badra area, eastern Iraq. This area is bounded between latitude (33o 17'– 33o 07') north, and longitude (45º 53'-46º 04') east. The aims are to compare four electrode arrays to determine the best array in delineating the aquifers using 2D imaging technique, and then compare between 1D and 2D imaging techniques in delineating layers and aquifer boundaries in complex sedimentary deposits, and to determine the thickness and depth of aquifers in the study area. Six 2D imaging stations were applied in the study area. The first two stations (2DS1, and 2DS2) were selected to make the comparison between Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner arrays. The total length survey for each array in the (2DS1) was 1190m, while in the (2DS2) was 590m with electrode spacing of 10m. Also, cross Vertical Electrical Sounding technique was carried out in the same positions of the 2D imaging stations (2DS1, and 2DS2) to determine any lateral change in lithology and to check the reliability of results of 2D imaging stations. They show that the first site is characterized by higher background noise level than that of the second site. The other four 2D imaging stations were carried out using Wenner-Schlumberger array, where the total length for each station was 1190m, while the spacing between its electrodes was 10m. Furthermore, (11) VES points were conducted using Schlumberger array, distributed along two parallel profiles. The maximum current and potential electrodes spacing was 1400m, and 80m respectively. All 2D imaging stations and VES profiles were applied as much as possible near existing wells. The results of 2D imaging show that the Dipole-Dipole array is highly affected by near surface inhomogeneity (NSI) and lateral inhomogeneity, so that it’s inverse model fails in delineating layers and aquifers in the two sites. Its vertical resolution decreases with increasing depth and/or increasing inhomogeneity. The Wenner array shows good quality apparent resistivity measurements in comparison with the others electrode arrays, because it is less affected by inhomogeneity. Its ability in delineating aquifers (or layers), however, decreases with increasing the array length and/or increasing inhomogeneity. The apparent resistivity measurements of Schlumberger reciprocal array shows good quality compared with the Dipole-Dipole array, and the inverse models of Schlumberger reciprocal array succeed in delineating the aquifers. Furthermore, it gives more depth of investigation (DOI) than dose other arrays. However, Wenner and Schlumberger reciprocal arrays give significant results in delineating layers and aquifers especially with small survey line and/or low inhomogeneity, but they do not show an optimal correspondence with the

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lithological sections of wells. However, their resolution is still less than that of WennerSchlumberger array The Wenner-Schlumberger array gives the best results in delineating layers and aquifers, and shows the best resolution. Therefore, it is useful in determining the aquifers especially in areas with high background noise The field curves of VES points show good quality data. They are interpreted manually using Ebert method and also interpreted by computer using IPI2Win software. The results of inverse modeling are closest to manual interpretation. Therefore, the results of inverse modeling are used to construct two geoelectrical sections, and then transformed to geological sections. They show presence of six zones reflecting the presence of sand, gravel, silt, and clay deposits, where the deposits size decreases with depth In general, two types of aquifers are recognized in the study area. The first is The Quaternary aquifer, which appears in all the geological sections and 2D imaging stations, and it can be divided into upper and lower aquifer as shown in (2DS1), (2DS3), and (2DS4). Generally, the thickness of this aquifer ranges between (30-200 m) which occurs at depth (10-30m) according to geological sections, while its thickness ranges between (35-180m) and occurs at depth (10-45m) according to 2D imaging stations. The second is AL-Mukdadiya aquifer, which appears only in 2DS1 at depth (140m), and it thickness is more than (80m). The comparison between 1D and 2D imaging techniques reveals that the 1D resistivity technique is the best in delineating the boundaries between layers. But, 2D imaging technique is better in delineating the aquifers and in determining the changes in resistivity within layers and aquifers. It also succeeds in recognizing the upper and lower aquifers as shown in (2DS1), (2DS3), and (2DS4). Therefore, 2D imaging is better in recognizing more layers or aquifers than dose 1D resistivity technique especially with the presence of gradual decrease (or increase) in resistivity values, or layers with small thickness. Also, 1D resistivity technique shows high DOI in comparison with 2D imaging technique. But, in 1D resistivity technique this depth becomes uncontrolled and it is difficult to determine whether the distance between electrodes increasing, while in 2D imaging technique the DOI is controlled by huge data measurements obtained by this technique.

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List of Contents Subject

Pages

Chapter one / Introduction…………………………………….

1-11

1.1 Preface……………………………………………………………

1

1.2 Location and topography ………………..………………………

1

1.3 Geology of the study area………………………………………..

1

1.3.1 Injana (Upper fars) Formation…...……………………...….

1

1.3.2 AL-Mukdhadiya Formation………………...…….………...

3

1.3.3 Quaternary deposits………………………………………...

4

1.4 Hydrology and hydrogeology ………………..………………….

5

1.5 Structural geology sitting………………………………………...

6

1.6 Previous studies………………………………………………….

7

1.6.1Previous studies in the world……………………………….

7

1.6.2 Previous studies in Iraq…………………………………….

9

1.6.3 Summary of studies………………………………………..

10

1.7 Aims of the study………………………………………………...

11

Chapter two / Theoretical background…..…………………

12-38

2.1 preface……………………………………………………………

12

2.2 Measurement theory……………………………………………...

12

2.3 Resistivity of the earth material………………………………….

16

2.4 Array types…………………….……………..…………………..

18

2.4.1 Schlumberger array…………………………………….……

18

2.4.2 Wenner array……….……………………………………….

19

2.4.3 Dipole-Dipole array …………………………….…………..

20

2.4.4 Wenner-Schlumberger array ……….……………………….

22

2.4.5 Schlumberger reciprocal array ……….……………………..

24

2.4.6 Summary of array ……......………………………………....

25

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Pages

2.5 One-Dimension (1D) resistivity technique………………………

27

2.5.1 Constant Separation Travers (CST)…………………………

27

2.5.2 Vertical electrical sounding (VES)……………………….…

27

2.5.2.1 Displacements in Schlumberger (VES) curves………..

29

2.5.2.2 Cross Vertical Electrical Sounding……………...…….

31

2.6 Two-Dimension (2D) imaging resistivity technique…..………...

32

2.6.1 Data processing and presentation…………………………...

32

2.6.1.1 Measurements error (bad data)………………………..

33

1. Electrode spacing errors…………………………..……

33

2. Observed potential errors (outliers)…………...………..

34

2.6.1.2 Apparent resistivity Pseudosection...………………….

34

2.6.1.3 Interpretation by inversion method….………………...

35

Chapter three / field work……………………………………..

39-55

3.1 Preface……………………………………………………………

39

3.2 Instruments……………………………………………………….

39

3.2.1 SYSCAL pro………………………………………………..

39

3.2.2 SYSCAL R2………………………………………………...

43

3.3 Select array parameters…………………………………………..

45

3.4 Field work………………………………………………………..

49

3.4.1 First field work stage……………………………………….

50

3.4.2 Second field work stage……………………………………

52

3.4.3 Third field work stage………………………………………

52

Chapter four / Data processing and interpretation ….…..

56-122

4.1 1D resistivity technique………………………………………….

56

4.1.1 Data quality of 1D technique…………......…………...…….

56

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Pages

4.1.2 Interpretation of 1D resistivity sounding curves.………...….

58

4.1.2.1 Qualitative interpretation…….……………………......

61

4.1.2.1.1 Curve types…………………………………...…

62

4.1.2.1.2 Apparent resistivity sections…………………....

70

4.1.2.2 Quantitative interpretation….………………………....

72

4.1.2.2.1 Manual interpretation (Ebert method) ...…..........

73

4.1.2.2.2 Computer interpretation (IPI2Win program)........

75

4.2 Cross sounding technique………………...……………………...

80

4.3 2D Imaging technique……………………………………………

83

4.3.1 Data quality of 2D imaging technique………..……………..

83

4.3.2 Data processing and inversion………………..…………......

96

4.3.2.1 Filtering process and inversion of 2DS1…….……..….

98

4.3.2.1.1 Manual filtering and inversion of 2DS1………...

98

4.3.2.1.2 Automatic filtering and inversion of 2DS1…......

104

4.3.2.2 Filtering process and inversion of 2DS2…………..…..

111

4.3.2.2.1 Manual filtering and inversion of 2DS2………...

111

4.3.2.2.2 Automatic filtering and inversion of 2DS2……..

116

4.4 Comparison between manual and automatic filtering…………...

118

4.5 Array parameters relationship ………………..…………….........

119

• Dipole-Dipole array…………………………………................

119

• Wenner-Schlumberger and Schlumberger reciprocal array……

120

• Wenner array………………………………………………….

121

4.6 Comparison between different electrode arrays…………………

121

Chapter five /Aquifer delineation…..………………...……... 123-142 5.1 Geoelectrical and geological sections……………………………

123

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Pages

5.1.1 Geoelectrical and geological sections along profile (A-A`)....

123

5.1.2 Geoelectrical and geological sections along profile (B-B`)....

127

5.2 Inversion models of 2D imaging stations………………………...

131

5.2.1 Station one (2DS1)………………………………..………....

132

5.2.2 Station two (2DS2)…..……………………………………....

133

5.2.3 Station three (2DS3)………………………………………....

134

5.2.4 Station four (2DS4)……………….………………………....

136

5.2.5 Station five (2DS5)……………………..…………………....

138

5.2.6 Station six (2DS6)……...…………………………………....

139

5.3 Aquifer delineating……………………………………………….

141

5.4 Comparisons between 1D, and 2D imaging technique…………..

141

Chapter six/Conclusions and Recommendations

143-146

6.1 Conclusions………………………………………………………

143

6.2 Recommendations………………………………………………..

146

References………………………………………………....………. 147-154

VII

List of Figures Figure title Figure (1-1) The elevation Contour map of the study area (General commission for groundwater). Figure (1-2) Geologic map of the study area (State Company of Geological Survey and Mining, 1996) Figure (2.1) Point source of current at the surface of a homogeneous medium Figure (2-2) Sketch showing the distances between current and potential electrodes in Schlumberger array Figure (2-3) Most common used and their geometric factors. (Aizebeokhai 2010) Figure (2-10) 2D sensitivity section of Wenner array (Loke, 2011) Figure (2-11) 2-D sensitivity sections for the dipole-dipole array. The sections with (a) n=1, (b) n=2, (c) n=4 and (d) n=6. (Loke, 2011) Figure (2-12) 2-D sensitivity sections for the Wenner-Schlumberger array. The sections with (a) n=1, (b) n=2, (c) n=4 and (d) n=6 (Loke, 2011). Figure (2-13) Sketch showed a) Schlumberger array. B) Schlumberger reciprocal, modified from (Stanton et al 2007). Figure (2-14) Pseudo cross-section for a) Schlumberger array. b) Schlumberger reciprocal, modified from (Bohachev et al 2005). Figure (2-15) A comparison of the pseudosections data pattern for a) the Wenner, b) Wenner-Schlumberger and c) Dipole-Dipole arrays. (Modified after Look, 2011). Figure (2-16) Apparent resistivity measurements, with increased current electrode spacing, are leading to increased penetration depths of the injected current. Results are compiled in the sounding curve (Kirsch 2006) Figure (2-17) Smoothing of field curve displacement for Schlumberger vertical electrical sounding (Zohdy et al, 1974) Figure (2-18) Cusps types on VES curves. (Zohdy et al, 1974) Figure (2-19) Rectangular cells with their resistivity points for 2D resistivity survey.

Pages 2 4 13 14 15 19 21 23 25 25 26

29

30 31 36

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List of Figures Figure title

Pages

Figure (3-1) SYSCAL pro resistivity meter.

41

Figure (3-2) Showing the keys of SYSCAL PRO + resistivity meter

41

Figure (3-3) Resistivity meter and their accessories

44

Figure (3-4) The change in n-factor and its effect a-spacing

47

Figure (3-5) Pattern of levels and a-spacing from 1a to 9a

47

Figure (3-6) Locations 2D imaging stations, and VESs profiles

49

Figure (3-7) Show fieldwork near BH5

50

Figure (3-8) The lithology sections of BH5 & BH6

51

Figure (3-9) The lithology of BH1, BH2, BH3, and BH4 Figure (4-1) (a) good quality curve for VES11 and (b, c) show the different distortion phenomenon. Figure (4-2) The distortion of VES 12 and VES12

53 57

Figure (4-3) The VES-13 and VES-13` near 2DS2

60

Figure (4-4) Smoothing process on field curve of VES 11

61

Figure (4-5) Field curve of VES-1

63

Figure (4-6) Field curve of VES- 4

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Figure (4-11) Field curve of VES- 11

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59

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Pages

Figure (4-14) Apparent resistivity section along (A-A`) profile

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Figure (4-15) Apparent resistivity section along (B-B`) profile Figure (4-16) Quantitative interpretation of Ebert method (manual interpretation) Figure (4-17) Quantitative interpretation of Ebert method (manual interpretation) Figure (4-18) The unusual values by forward calculation of IPI2 Win program Figure (4-19) The cancelling layers by forward calculation of IPI2 Win program for VES-3 Figure (4-20) Results of A) forward calculation and B) inverse modeling by IPI2 Win program Figure (4-21) Results of manual and inverse interpretation

71

Figure (4-22) Field curves of VES (12) and VES (12`) Figure (4-23) Smoothed field curves of VES (12) and VES (12`) and their (λ) Figure (4-24) Interpretation results of VES-13, VES-13`, and the relationship between (λ) and (AB/2) spacing Figure (4-25) Electrode watered by saltwater.

81

74 74 76 77 78 78

81 82 83

Figure (4-26) Locations of bad data in Wenner profiles for 2DS1 Figure (4-27) Locations of bad data of Wenner-Schlumberger profiles for 2DS1 Figure (4-28) Locations of bad data of Schlumberger reciprocal profiles for 2DS1 Figure (4-29) Locations of bad data of Dipole-Dipole profiles for 2DS1 Figure (4-30) The effect of bad data on the apparent resistivity pseudosections of the four arrays in 2DS1

85

87

Figure (4-31) Locations of bad data of Dipole-Dipole profiles in 2DS2

93

Figure (4-32) Locations of the oscillations in Wenner profiles in 2DS2

94

Figure (4-33) The effect of bad data on the apparent resistivity pseudosection of the four arrays 2DS2

95

86

88 91

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List of Figures Figure title Figure (4-34) The measured and calculated apparent resistivity and the inverse model sections of Wenner-Schlumberger array in 2DS1 after manual filtering Figure (4-35) The apparent resistivity pseudosections of DipoleDipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after manual filtering Figure (4-36) The inverse model sections of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after manual filtering Figure (4-37) The measured and calculated apparent resistivity and the inverse model sections of Wenner-Schlumberger array in 2DS1 after automatic filtering Figure (4-38) The apparent resistivity pseudosections of DipoleDipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1after automatic filtering Figure (4-39) The inverse model sections of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after automatic filtering Figure (4-40) The measured and calculated apparent resistivity and the inverse model sections of Wenner-Schlumberger array under 2DS2 after manual filtering Figure (4-41) The measured apparent resistivity pseudosections of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays respectively in2DS2 after manual filtering Figure (4-42) The inverse model sections of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner array s respectively in 2DS2 after manual filtering Figure (4-43) The measured and calculated apparent resistivity pseudosection and inverse model section of Dipole-Dipole after automatic filtering in 2DS2 Figure (5-1) The geoelectrical section along (A-A`) profile

Pages 99

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103

106

107

109

112

113

115

117 124

Figure (5-2) The geological section along (A-A`) profile

125

Figure (5-3) The geoelectrical section along (B-B`) profile

128

Figure (5-4) The geological section along (B-B`) profile

129

Figure (5-5) The inverse model of 2DS1

132

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Pages

Figure (5-6) The inverse model of 2DS2.

134


135


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Figure (5-9) The inverse model of 2DS5 Figure (4-10) The inverse model of 2DS6

139 140

List of Tables Table title Table (2-1) Resistivity of some earth materials (modified from Zohdy et al 1974, Lowrie 2007, and Loke 2011.) Table (3-1) Show parameters of the arrays with 60 electrodes Table (3-2) Show parameters of the arrays with 120 electrodes Table (3-3) Shows electrodes spacing for apparent resistivity measurements modified after (Bhattacharya, and Patra. 1968; AL. Ane, 1998) Table (4-1) Show the interpretation results of Ebert method Table (4-2) Show the interpretation results of Ebert method, and IPI2 Win program

Pages 17 45 46 54 75 79

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Appendices Appendix title

Pages

Appendix (1)

(VES field curves)

I

Appendix (2)

(shows the anisotropic factor for each AB/2 spacing for V (VES (12) and (12`)), and (VES (13) and (13`))

Appendix (3)

The quality data along profiles of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner VI arrays for 2DS2 before filtering

Appendix (4)

The quality data along profiles of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner array VIII for 2DS1 after manual filtering

Appendix (5)

The measured and calculated pseudosection and invers model section of Dipole-Dipole, Wenner-Schlumberger, Schlumberger XII reciprocal, and Wenner array for 2DS1 after manual filtering

Appendix (6)

The quality data along profiles of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner array XV for 2DS1 after automatic filtering

Appendix (7)

The measured and calculated pseudosection and invers model section of Dipole-Dipole, Wenner-Schlumberger, Schlumberger XIX reciprocal, and Wenner array in 2DS1 after automatic filtering

Appendix (8)

The measured and calculated pseudosection and invers model section of Dipole-Dipole, Wenner-Schlumberger, Schlumberger XXII reciprocal, and Wenner array for 2DS2 after manual filtering

Appendix (9)

The measured and calculated pseudosection and invers model section of Wenner-Schlumberger array for 2DS3, 2DS4, 2DS5, XXV and 2DS6

Chapter one/ Introduction

1

Chapter one/ introduction 1.1 Preface The groundwater exploration has increased in the last decades, due to increasing population and decreasing rainfall, which leads to draw down of the water table in aquifers. However, the most used method in exploration of groundwater is resistivity method. It is inexpensive compared with other methods, such as drilling. Therefore, this method must be developed to be more efficient in detecting the boundaries and thickness of layers of groundwater aquifers.

1.2 Location and topography. The study area occupies an area of about (101) Km2, located within Wasit province, north Badra area, between latitudes (N33º 17' 42.17''), (N33º 10' 39.1''), and longitude (E45º 58' 0.9''), (E46' 04' 31.3''). The major part of the study area is flat reflecting the Mesopotamian zone. It is hilly in places representing the foot hill zone. It rises in elevation to more than (360m) near the Iranian territory (Figure 1-1). However, the area slopes gradually toward southwest. The highest point reaches (140m) above sea level, and the lowest point is (50m) above the sea level, (Figure 1-1).

1.3

Geology of the study area.

1.3.1 Injana (Upper Fars) Formation. Injana (Upper fars) Formation was described by Busk and Mayo in Iran 1918 and subsequently recognized widely in Iraq (Jassim and Goff, 2006). AL-Rawi et al., (1992) was renamed Injana Formation and select a type section in Iraq, which was taken along the main Baghdad-kirkuk road on the north-eastern limb of Hemrin south anticline. It is 620m thick.

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360 120 140

100 60

80

200 140 120

60

80

100

140

120 60 100

80

Iran

Figure (1-1) The elevation topographic map of the study area (General commission for groundwater, 2011).


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Generally, the Formation comprises of fine grand pre-molasses sediments deposited initially in coastal area, and later in fluviolacustrine system (Jassim and Goff, 2006). This Formation is exposed north Zurbatyah town only, in the east of study area, (Barawary, 1993). It is composed of several progressive cycles of sandstone, siltstone and claystone with predominant red coloring, and many veins of secondary gypsum, (Figure 1-2), (Jassim, 2009). The sandstone beds becomes thicker, less compacted and coarser upward, where clay stone beds are brownish, fractured, silty and containing often lenses of siltstone and/or sandstone, (Barawary, 1993).The thickness of the Injana Formation in Badra area is (618m),(AL-Harbood, 2000). However, the age of Formation is usually accepted as late Miocene, and the lower contact of Formation is conformable based on the first appearance of thick sandstone, (Barawary, 1993).

1.3.2 Mukdadiya (Lower Bakhtiari) Formation This Formation was first described from Iran by Busk and mayo in 1918, and later introduced in Iraq (Jassim and Goff, 2006). The Formation is strongly diachronous but can be recognized throughout the foothill and folded zone, (Jassim and Goff, 2006). However, later the name Lower Bakhtiari was replaced to Mukdadiya. The type section in Iraq is located northeast of the Mukdadiya town in Diyala Governorate, with thickness of 1411m, (AL-Rawi et al., 1992).The Mukdadiya Formation is comprised of fining upward cycles of gravely sandstone, sandstone, and red mudstone, (Jassim and Goff, 2006). In the study area the Formation is exposed east of Badra area, and has thickness range between of (20-75m), (Jassim, 2009). The Formation is composed principally of clastics, mainly pebbly sandstone, sandstone and red mudstone. The sandstone is often cross bedded, (Jassim, 2009), and it was deposited in fluvial environment, (Enad, 2007), and in arid to semi-arid climate, (Jassim, 2009).

4

Chapter one/ Introduction 450 55`48`È

Legend

4607`48`È

4601`48`È

Qv

N Mio2f 33018`45``N

330 18`45``N

Mio3i

Qf Q af

Valley fill deposits Gravel, Sand Flood plain deposits Sand, Silt, clay Alluvial fan deposits Silty clays, Silt, Sand

Mio3-Plim

Mukdadiya (lower Bakhtiari) Fn . Sand stone, clay stone, silt stone

Mio3i

Injana (upper fars) Formation Sand stone, Clay stone, silt stone

Mio2f

Fatha (lower fars) Fn. Clay stone, marl, limestone, gypsum

Mio1e

Euphhretes Fn. Limestone, conglomerate limestone

e 1

33012`45``N

Mio3i Q af

Mio3-Plim

330 12`45``N

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Paved road

Qv BADRA

45055`48`È

Town 3306`45``N

3306`45``N

Q

Zurbatiya

f

4601`48`È

4607`48`È

Figure (1-2) Geologic map of the study area (State Company of Geological Survey and Mining, 1996)

The lower contact of Mukdadia Formation is conformable and gradational marked by the appearance of gravely (pebble) sandstone, (Barawary, 1993; Jassim and Goff, 2006). This contact is diachronous and gradational with the underlying Injana Formation, where the upper contact of the Formation in the study area is an erosional surface, and it is an angular unconformity surface with overlying Quaternary deposits, (Jassim, 2009). The age of Formation is late Miocene, (Jassim and Goff, 2006)

1.3.3 Quaternary deposits The Quaternary deposits are located in the Unstable Shelf within the Foothill Zone and Mesopotamian plain, which consists mainly of alluvial fans in the study area. In general, the alluvial fans consist of poorly sorted clastics deposits, usually gravel, boulders, and cobbles with subordinate amount of sand, silts, and clays. The alluvial fans deposits are generally massive or lenticular and randomly bedded. The coarse clastics are limbercated with irregular


5

arrangement while sand layers or lenses show horizontal or cross bedded. Alluvial fans consist of five stages in maximum with distinct stratigraphic boundaries marked often by sudden break in the slope, (Barawary. 1993). However, the oldest fans were deposited near stream outlet from Jabal Hemrin, and the younger fans lie further downstream (Jassim and Goff, 2006). The size of the fan is variable depending on the size of the drainage basin, type of sediments and stream gradient (Barawary, 1993). Finally, secondary gypsum in variable form is usually associated with alluvial fan deposits. The Quaternary deposits in the study area are comprised of gravel, sand, silt and clay, sometimes, sand deposits may contain gypsum. This area is characterized by existence of many valleys which connected by Galal Badra river. However, the Quaternary sediments are unconsolidated and usually finer grained than the underlying pebbly sandstone of Mukdadiya Formation (Jassim and Goff, 2006).The contact between them is of angular unconformity nature.

1.4 Hydrology and hydrogeology. There are two kinds of water source feeding the aquifers in the area. The first is Galal Badra River, which represents the main source of surface water. This river is in the south of the study area. The second source is the rainfall. The mean annual rainfall is (212.62mm) during the period 1994-2006, (ALShammary, 2008). From the hydrogeological side, two types of aquifers present: confined aquifer represented by Mukdadiya Formation and unconfined aquifer represented by Quaternary deposits, (AL-Azawi, 2002; and AL-Shammary, 2008). AL-Azawi, (2002), mentioned that there are two types of aquifers within the Quaternary deposits; the first is unconfined aquifer, which is distributed generally in all Badra area, while the second is confined and is found in north Badra area.


6

According to wells drilled in the Quaternary deposits, the thickness of these deposits exceeds (100m) (AL-Jiburi, 2005). However, the depth of unconfined aquifer increases towards the west and southwest. The static water level of the unconfined aquifer is between (2 to 14m). The depth of confined aquifer increases to the west, northwest, and southeast (AL-Azawi 2002), while the static water level is between (3-45m) (AL-Jiburi 2005). Generally, the direction of the ground water movement is from northeast to southwest. In the study area the depth of drilled wells is between (55-65m) and all of them are penetrated within Quaternary deposits, the water static level reaches to 10m with TDS between (2500-4000 ppm). However, one borehole is penetrated with Quaternary deposits and Mukdadiya Formation in the study area. Its depth is 220m and TDS equal to 9600 ppm.

1.5 Structural geology sitting. Iraq lies in the border area between the two main Phanerozoic units of the Middle East i.e. between the Arabian part of the Nubio-Arabian platform and Asian branches of the Alpine Geosyncline, (Buday, 1980). In general, the area lies within both eastern center part of the Mesopotamian zone (Tigris subzone) and the southeastern part of the Foothill Zone (Makhul subzone). The two zones represent the outer and central units of the Unstable Shelf, (Buday, 1980). The outer (westernmost) unit of the Unstable Shelf is characterized by great subsidence since at least Mesozoic times culminating in the late Cenozoic and by slight folding of sedimentary covers (Buday, 1980). The subsidence can be evidenced by the continuously filling of the basin by recent deposits (Barawary, 1993). The central part of the unstable is characterized by thick sedimentary cover and well-marked folding, (Buday. 1980). Since the study area is a part of the Unstable Shelf, it must have been affected by the late regional intensive tectonic movement that caused the uplifting of


7

Hemrin structural syncline in the Mesopotamian zone. The last intensive tectonic movement was in the late Pliocene. The influence of this movement is extended to deform the Mesopotamian synclinal basin. The evidence of this deformation is the uneven paleo-surface of pre-Quaternary rocks which now covered by thick Quaternary deposits, (Barawary, 1993).

1.6 Previous studies 2D resistivity imaging method is widely used in the world and there are many studies discussing different cases and try to solve the difficulties facing the interpretation of the obtained results. Although, there are very few studies conducted in Iraq. In this section it will describe some of these studies.

1.6.1 Previous studies in the world Hago (2000) applied Wenner electrode array by electrical resistivity imaging technique in order to locate, delineation subsurface water resources and estimate its reserve, in Bukit jalil-serdang area, selangor Durul Ehsan, Malaysia. The result showed that the aquifer occupies a surface area of about 15977900 m2 and has a mean depth 13m. Ahmed and Sulaiman (2001) used electrical resistivity imaging, Wenner array, to investigate the leachate production within landfill of seri pleating located in state of Selangor, Malaysia. However, the resistivity imaging indicated the presence on large zones of decomposed waste bodies saturated with highly conducing leachate. The model section of Wenner array gives high RMS error (79%). Zhou et al. (2002) compared between dipole-dipole, Wenner and Schlumberger arrays to delineate sinkholes and karst hazard. The Dipole-dipole array appeared to be better than those from the Wenner and Schlumberger in displaying the sinkholes and karst hazard. Dahline and Zhou (2004) used five synthetic geological models to compare the resolution and efficiency of 2D resistivity imaging survey for ten electrode


8

arrays. These arrays were pole-pole, pole-dipole, half-Wenner, Wenner-α, Schlumberger, dipole-dipole, Wenner-β, γ-array, multiple or moving gradient array, and midpoint-potential-referred measurement arrays. Also he investigated the responses of variation in the data density and noise sensitivities of these electrodes using robust inversion and smoothness-constrain least-square inversion. They provides that the γ-array, and Wenner-β are less contaminated by noise than the others electrode arrays. And the dipole-dipole, pole-pole, moving gradient and Schlumberger arrays can yield better resolution images than that of others. In addition, the robust inversion generally gives better imaging results than the smoothness-constrain least-squares inversion, especially with noisy data. Zogala et al. (2008) used Wenner-Schlumberger protocol to delineate the boundary between Miocene and Pleistocene sediments. This survey preformed in pilawa River valley in the area of middle Pomerania (Poland). The resistivity profile measuring was 800m and this allowed to investigation the geologic to depth 150m. The resistivity cross section shows the structure of Pleistocene sediments and the depth of the Miocene – Pleistocene boundary. Ayolabi et al. (2009) applied (24) vertical electrical sounding (VES points) and (8) 2D imaging stations to locate sites for water supply wells in Ajebo foursquare comp, Nigeria. Only two VES points have aquifer thickness about 14m, while the results of 2D imaging show about two points where productive boreholes could be sited. Thus, 2D resistivity imaging gives a better lateral view of the subsurface layers than geoelectrical section from 1D because of its ability to give a continuous record of subsurface image. Reiser et al. (2009) examined the imaging resolution of four different arrays (Dipole-Dipole, Gradient, Pole-Dipole and Wenner) for mapping of fracture zones in bedrock. This study was carried out in Norway. The best results were achieved with Gradient and dipole-dipole especially for mapping fracture zones with various depth and width. The Gradient array gives the best response for


9

mapping steeply dipping structures and different contrast, whereas Wenner is good at illustrating horizontal layers. Dipole-Dipole and Pole-Dipole show the most accurate results for situations where a low resistivity top layer is present. Srinivasamoorthy et al. (2009) carried out electrical imaging techniques for measuring apparent resistivity values using different electrodes separation (Wenner array) to identify the extent of pollution in the aquifer matrix of Tirupur, south India. All profiles shows existence a contamination although the RMS errors were reach to 35%. Ebraheem et al. (2009) used an intensive 2D earth resistivity imaging survey-distance of profiles reach to (2220m) to conduct in the aquifers of eastern coast area of UAE, to assess the available groundwater resources, and to delineate saltwater intrusion. Then, they made an empirical relationship between the inferred earth resistivity and the amount of total dissolved solids obtained from chemical analysis of water samples collected from the wells on the 2D earth resistivity profiles.

1.6.2 Previous studies in Iraq Aziz (2005) conducted 1D and 2D resistivity imaging to evaluate the hydrogeological conditions of Bazian basin in the west SulaImania city, NEIraq. Four different aquifers with variable thickness and depths were detected, two within Quaternary deposits (recent subbasin), and two within Pila Spi subbasin. In addition to construct a depth map to the surface of Sinjar Formation. It shows depths ranging between (126- 268m) through the whole area. Amin (2008) applied (281) vertical electrical sounding points to determine aquifers and to evaluate the hydraulic parameters in SharaZoor basin north east Iraq. The geological sections and extracted relations between the geoelectrical and hydraulic parameters were showed the presence of unconfined aquifer with thickness range between less than (20m) to more than (80m).


10

Al-Zubedi (2009) used (13) vertical electrical sounding (VES) with Schlumberger array, and (4) 2D sounding stations (Wenner array), to delineate aquifers in the area located in the south and southwest of Samawa city, southern Iraq, and to make a comparison between 2D imaging survey and VES. The results show that 2D imaging survey is the best for determining the shallow aquifers, and it can support the VES in area with lack nay drill wells. Three parts from three aquifers, in addition to two secondary aquifers were delineated in the study area AL-Menshed (2011) used Wenner, Schlumberger and Polar Dipole-Dipole in three types of measuring technique (1D, 2D, 3D), near six wells contaminated with hydrocarbon materials in Karbala governorate, Iraq. It is found that 1D technique is the best in delineating contaminated and clear zones, In addition to the direction of contaminated water plume and boundary of hydrocarbon spot. It was not active to detect the hydrocarbon contaminatedbearing layers in actual position. 2D imaging technique was better than 1D technique, while 3D technique is the best and gives clear image than 2D and 1D technique. AL-Shemmari (2012) carried out 25 VES sounding using Schlumberger array, and 2 stations of 2D imaging in Bahr Al- Najaf basin to determine the direction of ground water and to detect the cause of emission of (H2S) respectively. Then establish mathematical empirical relations by combining the geoelectrical, and hydrogeological data for estimating its hydraulic parameters. The hydro-geophysical models were constructed and they showed the occurrences of confined aquifer with thickness reach to (160m). In addition, the 2D imaging survey was able to obtain more detail information about the variations of the apparent resistivity of subsurface rocks.

1.6.3 Summary of previous studies The previous studies show comparisons between different arrays to delineate fractures and synthetic models using 2D imaging technique, in addition to use


11

1D (VES) and 2D imaging techniques to delineate shallow aquifers (small survey) and other features. It is not shown any comparison between different arrays, such as (DipoleDipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays), in delineating aquifers by applying long survey (deep investigation) using 2D imaging technique to verify the difference between them in delineating these aquifers. Also, it is not found any comparison between 1D and 2D imaging technique by applying long survey (deep investigation) to determine the best in delineating the boundaries between layers.

1.7 Aims of the study 1. The main goal is to compare between four electrode arrays (Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays) to determine the best array in delineating the aquifers by using 2D imaging technique in complex sedimentary deposits. 2. Comparison between 1D vertical electrical sounding and 2D imaging in delineating layers and aquifer boundaries. 3. Determining the thickness and depth of groundwater aquifer in north Badra area.

Chapter two/ Theoretical Background

12

Chapter Two/ Theoretical Background 2.1 Preface The resistivity method is one of the geophysical methods used in groundwater exploration by several techniques. One of these techniques is one-Dimensional (1D) and two-Dimensional imaging (2D) techniques. These techniques are depending on passing a DC electrical current through ground using pair of current electrodes and then measuring the results of potential difference by a pair of potential electrodes.1D resistivity method was used many decades ago. Geoelectrical resistivity method is increasingly used in environmental, engineering and hydrological investigations as well as geothermal and mineral prospecting (Aizebeokhai, 2010). The development of equipment design capability and computer program expedite using this method also the increasing demand on the groundwater caused the increase of studies, and researches on the thicknesses of the aquifers.

2.2 Measurement theory The resistivity survey depends on emitting current (I), using two electrode (C1, C2), in the subsurface and then measures the potential (V) between another electrode pair (P1, P2). The equipotential surfaces have hemispherical shapes. The current lines, flowing underground, will be taken a symmetrical radial form and these lines are perpendicular on the equipotential surfaces, (Figure 2-1). If the half space is homogenous, and isotropic, flowing of electrical current will be radially symmetrical in the half space.

13

Chapter two/ Theoretical Background P1

r

C1

C2

Current flow lines Equipotential hemispherical surfaces

Figure (2.1) Point source of current at the surface of a homogeneous medium modified from (Telford et al, 1990).

Therefore, the potential (V) will be proportional directly with the current (I) and with the resistivity (ρ) of the medium and inversely with the distance (r), which is the distance between current electrode to potential electrode. So (V) can be taken by =

… … … … … … (1)

2

In electrical survey, it is used four electrodes (C1, C2, P1, P2), (Figure 2-2),

the distance (r) between electrodes is change according to the location of current and potential electrodes. From Figure (2-2), the potential (V) at electrode (P1) from positive current electrode (C1) is: =

2

∙

1

………………2

For potential electrode (P2) the equation will be:=

2

∙

1

………………3

14


C1

P2

P1

C2

r1

r4

r2

r3

Figure (2-2) Sketch showing the distances between current and potential electrodes in Schlumberger array

Therefore, the potential difference between electrodes (P1, P2) which caused by positive current electrode (C1) is:∆

=

2

∙

1

−

1

………………4

By the same way, it can calculate the potential difference at current electrode (C2), which is resulted from (P1, P2) potential electrodes, so. ∆

=

2

1 1 ∙ (− ) − (− ) … … … … … … 5

Where the negative signal refers to the current emitting from electrode (C2). Therefore, the potential difference between P1, and P2 is: ∆

∆

=∆

=

2

∙

1

−∆ −

1

−

1

………………6 +

1

………………7

From rearranging equation (7) the resistivity in homogenous half space medium is

∆

…………….8

15

Chapter two/ Theoretical Background =

……………9

Where (K) is geometric factor that depending on the arrangement of the four

electrodes. The resistivity (ρ), which is computed from equation (9), in homogenous and isotropic half space medium, is called true resistivity. However, if the medium is inhomogeneous and/or anisotropic, then the computed resistivity from equation (9) is called an apparent resistivity ( =

… … … … … 10

).

The modern resistivity instruments normally give apparent resistivity value. The apparent resistivity is measured by ohm.m (Ω.m), and it depends on the electrode array and on geology. It may be larger or smaller than the true resistivity or may even be negative. The full theory can be found in (Kunetz 1966; Keller and Frischknecht. 1966; Battacharya, and Patra. 1968; Zohdy et al 1974). Figure (2- 3), shows the geometric factor of the most common arrays used in resistivity survey

a

na

=

na

( + )

=

C1 Dipole-Dipole array

=

( + )( + )

Pole-Dipole array

=

( + )

Figure (2-3) Most common used and their geometric factors. (Aizebeokhai, 2010)


16

2.3 Resistivity of the earth material The electrical properties of most rocks in upper part of the earth crust are depending primarily upon the amount of water in the rock, the salinity of water, and the distribution of water in the rock, so the saturated rocks have lower resistivity than unsaturation or dry rocks (Zohdy et al 1974). Electrical current passes through earth material by two modes: electronic, occurs in metals and crystals, or electrolytic, conduction in liquid (Keller and Frischknecht, 1966). In electronic mode the current flows via free electrons, while in electrolytic, most rocks conduct electricity by mineralized water and porous. It is depending on the conductivity of the amount water contain and on the manner in which the water is distributed. Here, it must mention that the conductivity is the reciprocal of resistivity. However, the flow of current in clay layers is in both electronic and electrolytic. As shown in table (2-1), the resistivity of earth material varies from less than 1 ohm.meter (Ω.m) to several thousand ohm.meter. Sedimentary rocks, which are usually porous and have higher water content have resistivity values range (1-10000 Ω.m), with most values below 1000 Ω.m. the resistivity values are largely depending on porosity of rocks and the salinity of contained water (Zohdy et al, 1974; Lowrie 2007; and Loke, 2011), where The higher the porosity of saturated rocks, the lower the resistivity and the higher the salinity of saturating fluids, the lower of resistivity. Unconsolidated sediments generally have lower resistivity values than sedimentary rocks. The values commonly range from less than 1 Ω.m for certain clays and sands saturated with saline water to several thousand of Ω.m for dry sand and gravel (Zohdy et al, 1974). The resistivity of these sediments is depending on the porosity and clay content, clayey soil normally has lower resistivity value than sandy soil.

17

Chapter two/ Theoretical Background Table (2-1) Resistivity of some earth materials (modified from Zohdy et al 1974, Lowrie 2007, and Loke 2011.) Type of rock

Resistivity (ohm.m)

Limestone

10-10000

Sandstone

1-10000

Conglomerate

10-10000

Soil

Less than 1-10

Clay

Less than 1-100

Alluvium

Less than 1-1000

Sand

Less than 1-10000

Gravel

100-10000

Fresh water

10-100

Sea water

0.2

The overlapping in the resistivity values of different classes of rocks and soils is because that the resistivity of particular rocks or soil samples depend on a number of factors such as porosity, the degree of water saturation and the concentration of dissolved salts. The resistivity of groundwater varies from 10 to 100Ω.m depending on the concentration of dissolved salts. Note that the low resistivity (about 0.2Ω.m) of sea water is due to the relatively high salt content. This wide range of values is at the same time the strength and the weakness of electrical prospecting. It is the strength because it facilities distinction types of rocks; it is a weakness because it sometimes means variation in measurements that have no relation to problem under consideration (kunetz 1966).


18

2.4 array types 2.4.1 Schlumberger array The electrode array most commonly used in electrical prospecting is Schlumberger array, especially in investigation of groundwater aquifers. It is adopted by Conrad schlumberger in his pioneer works (Kunetz 1966, and Koefoed 1979). In this array, four electrodes (C1, C2, P1, P2) are placed symmetrically along straight line on the earth surface, the current electrodes on the outside and the potential electrodes on the inside, (Figure 2-3b). The distance between potential electrodes (P1, P2) in principle are infinity small, in practice the Schlumberger (P1, P2) cannot be made infinity small (Kunetz 1966). It is always kept equal to the ratio (1/12 ≤ P1P2/C1C2 ≤ 1/5), (AL-Ani, 1998). In traditional Schlumberger array sounding, the current electrodes are successively moved away from each other at each new reading, while the potential electrodes are left at the same position in order to increase the depth of investigation, to determine the effect of surface inhomogeneity in potential electrodes, and to reduce the time and efforts which is spending in changing the location of potential electrodes for each (C1, C2) separation. Therefore, it is less sensitive for lateral inhomogeneity, and the measured apparent resistivity is more representative of deep layers for the farther (P1, P2) electrode form (C1, C2) electrodes. However, when the ratio of the distance between the current electrodes to that between the potential electrodes becomes too large, the potential difference become too small to be measured with sufficient accuracy (Koefoed 1979). In this case, it is necessary to increase the distance between potential electrodes (Jakosky, 1961). Finally, AL-Ane (1998) was mentioned that the depth of investigation (DOI) for Schlumberger array is more than Wenner array, and this (DOI) reduces with increasing the distance between (P1, P2) of Schlumberger array.


19

2.4.2 Wenner array This array was popularized by the pioneering work carried by The University of Birmingham research group (Griffiths and Turnbull 1985). The arrangement of the electrodes is shown in figure (2-3a). In figure (2-10), the sensitivity plot for Wenner array has almost horizontal contour beneath the center of array. Because of this property, the Wenner array is relatively sensitive to vertical changes in the subsurface resistivity below the center of the array. However, it is less sensitive to horizontal changes in subsurface resistivity, (Loke, 2011). Hence, the Wenner array is good in resolving vertical changes (horizontal structures) but it is relatively poor in detecting horizontal changes (vertical structures). The median depth of investigation (DOI) is approximately 0.519 times spacing compared with other arrays, therefor it has moderate depth of investigation. The Wenner array is characterized by small geometric factor(2

), it is advantage because the signal strength, used to calculate the

apparent resistivity value for this array, is inversely proportional to geometric factor. Therefore, Wenner array has strongest signal strength (Loke, 2011). This means that Wenner array has less effected by noise contamination and has better signal-to-noise ratio than other arrays (Dahlin and Zhou, 2004).

Figure (2-10) 2D sensitivity section of Wenner array (Loke, 2011)


20

This array in many situations has practical advantage, where measurements can be easily collected with control system (Griffiths et al, 1990). It disadvantage for 2D survey is relatively poor horizontal coverage as electrode spacing increase.

2.4.3 Dipole-Dipole array The use of Diploe-Dipole array in electrical prospecting has been become common since 1950s, particularly in Russia (Zohdy et al, 1974). The arrangement of the electrodes is shown in figure (2-3). The spacing between current electrodes (C2-C1) as well as between potential electrodes (P1-P2), gives as (a), is the same. However, this array has another factor marked as n, which is equal to the number of (a) between the C2, and P1 electrodes (Figure 2-3c) Figure (2-11) shows the sensitivity section for this array for (n) values ranging from 1 to 6. The largest sensitivity values are generally located between (C2-C1) and (P1-P2) dipoles pairs. This mean that this array is most sensitive to resistivity changes below the electrodes in each dipole pair. As n-factor increased, the high sensitivity values become increasingly more concentrated beneath the (C2-C1) and (P1-P2) dipoles, while the sensitivity values under the center of array are decreased. In addition, the sensitivity contour pattern becomes almost vertical. Therefore, it is very sensitive to horizontal changes in resistivity but is relatively sensitive to vertical changes. Thus it is good in mapping vertical structures and is poor in resolving horizontal structures (Dahlin and Zhou, 2004; Loke, 2011). This array has shallow depth investigation compared with Wenner array. For example at n=1 the depth of investigation is 0.416a compared with 0.519a for Wenner array, while for n=6 the depth of investigation is 0.730. So, to get more


21

depth investigation with this array, the a-spacing is initially kept fixed at smallest unit electrode spacing and the n-factor is increased from 1 to 2 to 3 up to about 6. Also this array has better horizontal coverage than the other arrays (Loke, 2011).

Figure (2-11) 2-D sensitivity sections for the dipole-dipole array. The sections with (a) n=1, (b) n=2, (c) n=4 and (d) n=6. (Loke, 2011)


22

Dipole-Dipole array tends to has more risk of noise contamination than other arrays because it has very low signal strength for large of the n-factor. Therefore, it is often not advisable to use more than 6 n-factor in real situation due to the resulting of very low signal-to-noise ratio (Dahlin and Zhou, 2004). In most textbooks, the electrodes are arranged in a (C1-C2) and (P1-P2) that will in fact gives a negative geometric factor. So, it is preferable to arrange the four electrodes in (C2-C1) and (P1-P2) for this array.

2.4.4 Wenner-Schlumberger array. This is a new hybrid between Wenner and Schlumberger arrays (Pazdirek and Blaha, 1996), (Figure 2-12). Actually it is combination of Wenner and Schlumberger arrays adopted for using an arrangement with a line of electrodes with constant spacing (normally used in 2D electrical imaging) (Geotomo software, 2008). The n-factor for this array is the ratio of the distance between the (C1-P1) or (C2- P2) electrodes to the spacing between the (P1-P2) potential electrodes. However, note that the normal Wenner is a special case of WennerSchlumberger array where the n-factor is equal to 1. (Geotomo software, 2008; Loke, 2011). Figure (2-12), shows the sensitivity pattern of Wenner-Schlumberger array as n-factor is increased from 1(Wenner array) to 6 (the classical Schlumberger array). The area of the highest positive sensitivity below the center of array becomes more concentrated beneath central (P1-P2) electrodes as the n-factor is increased. At the n=6, the high positive sensitivity lobe beneath the (P1-P2) electrodes becomes more separated from the high positive sensitivity values near the C1 and C2 electrodes. This means that this array is moderately sensitive to both horizontal (for low n-factor) and vertical (for high n-factor) structures (Loke, 2011).


23

The median depth investigation for this array is similar for Wenner array (0.519) for n=1, but this median depth of investigation increased about 10% larger than that for the n-factor greater than 3 (for n=3 the median depth is 1.318) (Edwards, 1977; Loke, 2011).

Figure (2-12) 2-D sensitivity sections for the Wenner-Schlumberger array. The sections with (a) n=1, (b) n=2, (c) n=4 and (d) n=6 (Loke, 2011).


24

The signal strength for this array is weaker than that of Wenner array, therefor to be in safe side, it should be included all the normal Wenner array measurements when carry out survey with Wenner-Schlumberger array (Geotomo software, 2008). It is higher than that of the Diploe-Dipole array (Loke, 2011). However, the Wenner-Schlumberger array, even with a slight reduction of signal-to-noise ratio, may be offered an improved imaging resolution compared with Wenner (Dahlin and Zhou, 2004). In addition, it has moderately data coverage between Wenner and Dipole-Dipole arrays.

2.4.5 Schlumberger reciprocal array. The Schlumberger reciprocal array, (Figure 2-13b), is chosen because it can easily optimized to allow for maximum number of potential pairs (channels) to be measured with signal current injection (Stanton et al 2007), and to assess the assurance and control of quality data in comparison with the WennerSchlumberger array. The theorem of reciprocity state that no change will be observed in ratio of measured voltage to imposed current if the position of potential electrodes and current electrodes are interchanged (Van Nostrand and cook, 1984; Keller and Frischknecht 1966). So, the arrays in figure (2-13a and b) yield the same result (potential difference), but Schlumberger array has the practical advantage that (ΔV) is measured over a shorter distance so it is less influence by natural earth currents, (Figure 2-14). The Schlumberger reciprocal array is more prone to pike up the noise, due to much large potential electrode separation, than the normal array when assessing the data quality using reciprocal measurements (Zhou and Dahlin, 2003; Dahlin and Zhou, 2004). However, the horizontal coverage data, and signal strength for Schlumberger reciprocal are similar to those for Wenner-Schlumberger array (observed note).


(a)

25

2

(b)

Figure (2-13) Sketch showed a) Schlumberger array. B) Schlumberger reciprocal, modified from (Stanton et al 2007).

(a)

(b)

Figure (2-14) Pseudo cross-section for a) Schlumberger array. b) Schlumberger reciprocal, (modified from Bohachev et al 2005).

2.4.6 Summary of arrays. Figure (2-15) show the pattern of data points in the pseudosection for Wenner, Wenner-Schlumberger and Dipole-Dipole arrays, which will be used in this study. Wenner-Schlumberger has slightly better horizontal coverage compared with Wenner array, but it has less horizontal coverage than DipoleDipole array. For the Wenner array each deeper data level has 3 data less than the previous data level, Wenner-Schlumberger array is loss of 2 data points with each deeper level, while Dipole-Dipole array is loss a 1 data points with each

26


deeper level. In other words, the horizontal coverage for Wenner-Schlumberger array is slightly wider than Wenner array but it is narrower than that obtained with Dipole-Dipole array (Loke, 2011). It is worth will to mention that the behavior of Schlumberger reciprocal is similar to Wenner-Schlumberger array in horizontal coverage. However, contrariwise the Dipole-Dipole array, the Wenner array has less noise contamination due to high signal strength. While Wenner-Schlumberger array, even the slight reduction of the signal strength, may be offered an improved imaging resolution compared with Wenner array (Dahlin and Zhou 2004). The Wenner array is good in resolving horizontal structures (vertical change in resistivity); the Dipole-Dipole array is good in resolving vertical structures (horizontal change in resistivity), while the WennerSchlumberger array is good in resolving the both structures (Dahlin and Zhou, 2004; Loke, 2011). The Schlumberger array is widely used for vertical electrical sounding VES. It is less sensitive by lateral inhomogeneity, and the measured apparent resistivity is more representative of deep layers for the farther (P1, P2). (a) n=1 n=2 n=3 n=4 n=5 n=6

1 18 32 43 51

56

(b) n=1 n=2 n=3 n=4 n=5 n=6

1 18 33

46 57

66

(c) n=1 n=2 n=3 n=4 n=5 n=6

1 18 34

49

63 76

Figure (2-15). A comparison of the pseudosections data pattern for a) the Wenner, b) WennerSchlumberger and c) Dipole-Dipole arrays. (Modified after Loke, 2011).


27

2.5 One-Dimension (1D) resistivity technique. There are two techniques of field survey used with 1D resistivity technique, Constant Separation Travers (CST) and Vertical Electrical Sounding (VES).

2.5.1 Constant Separation Travers (CST). In this technique, the spacing between the electrodes is fixed and the whole array is moved along profile after each measurement (K will be constant) to get the lateral variation of apparent resistivity values within the same depth (Kunetz 1966; Battacharya, and Patra. 1968). However, to obtain maximum apparent resistivity anomaly, the Travers must be at right angle to the strike of the geological structures. It is recommended, to make CST profiles, that at least two different electrodes spacing can be used, in order to aid in distinguishing the effect of shallow geological structures from the effect of deeper ones (Zohdy, et al., 1974). The results can be represented as horizontal resistivity profiling or horizontal resistivity maps. In the case of horizontal resistivity profiling, with one or more electrode separation, it will be one curve for each electrode separation used. Where the midpoint of the array at each measurement is plotted on the abscissa and the apparent resistivity values is plotted on the ordinate using liner or logarithmic scale as appropriate. In the case of horizontal resistivity maps, the results of group of profiles can be showed in the form of map, one for each measurement is plotted and the corresponding value of apparent resistivity contours are then drawn representing points of equal resistivity, (Kunetz 1966). The most arrays used for this technique is Wenner array, (Kunetz 1966).

2.5.2 Vertical Electrical Sounding (VES). Electrical sounding is process by which depth investigation is made (Zohdy, et al., 1974). The basic idea for resolving the vertical resistivity layering is to stepwise increase the current-injection electrodes (C1-C2) spacing, which


28

leads to increase the penetration of the current lines and in this way to increase the influence of deep layers on the apparent resistivity ( a), (Figure 2-16). In the other words, the center point of electrode array and its orientation remains fixed, but the spacing between the electrodes is increased to obtain more information about the deeper sections of subsurface (Kunetz, 1966). If the ground is comprised of horizontal homogenous and isotropic layer, the electrical sounding (VES) data represent only the variation of resistivity with depth. In practice the (VES) data are influenced by both vertical and horizontal heterogeneities. Therefor the execution, interpretation, and presentation of sounding data should be that the horizontal variation in resistivity can be distinguished easily from vertical ones (Zohdy et al 1974). The results of (VES) data are represented in log-log graph paper in which the half length of array (C1C2/2) is plotted on the abscissa and the corresponding apparent resistivity is plotted on the ordinate (Kunetz 1966). The data from such survey (apparent resistivity) reflect the vertical distribution of resistivity values in a geological section (Battacharya, and Patra 1968). It is normally assumed that the subsurface consist of horizontal layers. In this case, the subsurface resistivity is changing only with depth, but does not changing in the horizon direction. A one- dimensional model of subsurface is used to interpret the measurements. The greatest limitation of resistivity sounding method is that it does not take into account lateral variation in the layer resistivity. Such variations are probably the rule than exception. The failure to include the effect of such lateral variation can be resulted errors in the interpretation of layer resistivity and/or thickness. It causes changes in the apparent resistivity values. This method has given useful results for geological situations where the 1D model is approximately true (Loke, 2011). The best array can be used for this technique is Schlumberger array, (Kunetz 1966).


29

Figure (2-16). Apparent resistivity measurements, with increased current electrode spacing, are leading to increased penetration depths of the injected current. Results are compiled in the sounding curve (Kirsch 2006)

2.5.2.1 Displacements in Schlumberger VES curve. Lateral inhomogeneity in the ground effects on resistivity measurements in different ways. This effect depends on (1) the geometric and the size of the inhomogeneity with respect to its depth of burial and to the size of the electrode array, (2) the resistivity contrast between the inhomogeneity and the surrounding media, (3) orientation and type of electrode array (Zohdy et al, 1974). However, many kinds of displacements (or distortions) may occur in Schlumberger VES carve. 1. Curve displacement: This displacement can be observed between the segments of Schlumberger VES curve when increasing the spacing of (P1-P2), (Kunetz 1966; Battacharya, and Patra. 1968). Such displacement can be caused due to near surface inhomogeneity (NSI) and/or by theoretical effects of the ratio (P1P2/C1C2). It occurs because getting two different apparent resistivity values from different apparent depth. Therefore, decreasing the displacement due to theoretical effect in the field as much as possible is better than making correction to the field curve. It is done through keeping the ratio of (P1P2/C1C2) between (1/5-1/12). So, the residual


30

displacement can be removed by shifting the segment of the curve upward or downward to smooth the field curve (AL-Ane 1998), (Figure 2-17). Another displacement type, which is called discontinuity, occurs during the expansion of the current electrodes spacing. As a result of this displacement, the VES curve is displaced downward because the value of apparent resistivity at the large (C1C2) is much less than the previous reading (Zohdy et al, 1974). It is caused by dike like structure. However, to obtain such a discontinuity, it must that the width of dike is infinitesimal in comparison the C1C2/2 and the dike either intersect the earth surface or buried under a cover of thickness very small in comparison to the C1C2/2, in addition the resistivity of the dike is more than the surrounding media (Zohdy, 1969).

Figure (2-17) Smoothing of field curve displacement for Schlumberger vertical electrical sounding (Zohdy et al, 1974)

2. Cusp: The most important feature on the sounding curve that indicates the presences of the lateral inhomogeneity is appearing of cusps on them (Zohdy et al, 1974). This Cusp appears on the segment of curve when one or more values of apparent resistivity deviate from the general trend of apparent


31

resistivity curve, (Figure 2-18). It may be repeated many times on the whole VES curve. According to Zohdy et al, (1974), if there is a resistive lateral inhomogeneity, such as sand lenses, then the cusps will be as shown in figure (2-18). 3. Scattering: The mean of scattering is the dispersal some of resistivity values in the field curve. It is caused by lateral inhomogeneity of rocks or sediments. This phenomenon can be appeared when some of measurements are scattered in the VES curve. However, highly distortion is indicating the effect of strong lateral heterogeneities on VES curves of Schlumberger array (Zohdy, 1969).

Figure (2-18) Cusps types on VES curves. (modified from Zohdy et al, 1974)

2.5.2.2 Cross Vertical Electrical Sounding technique. This technique is used to study of any anisotropy underground surface in different direction. The survey is conducted using the same array spacing and with the center of electrode spreading on the same position. It is used with any electrode array. Actually, this technique type is derived from azimuthal survey, where its measurements are taken in two directions. This technique is sensitive


32

to lateral subsurface inhomogeneity as well as the fractures (Taylor and Fleming., 1988). The results of this technique are represented on polar or elliptical diagram by draw the resistivity values for each (C1C2) separation in specific scale for two directions (Dutta. 1969; and Mallik et al., 1993)

2.6 Two-Dimensional (2D) resistivity technique. Two-dimensional (2D) resistivity imaging can be achieved by integrating the techniques of Vertical Electrical Sounding with that of electrical profiling (Constant Separation Travers). The 2D resistivity survey are usually carried out using large numbers of electrodes, 25 or more, connected to multi-core cables. However, 2D resistivity model is more accurate model of subsurface than 1D resistivity model, where the resistivity changes in the vertical direction as well as in the horizontal direction along the survey line. In this case, it is assumed that the resistivity does not change in the direction that is perpendicular to the survey line. Typically 1D resistivity sounding survey may involve about 10-20 readings, while 2D imaging survey involve about 100-1000 measurements or more (Loke, 2011). Because of the large amount of data needed, the survey is performed by an automatic manner. So that, as few as possible, to get best results, all possible measurements are made. This will be effected on the quality of the interpretation model obtained from the inversion of apparent resistivity measurements (Dahlin and Loke 1998).

2.6.1 Data processing and presentation. There are number of steps need to performance to get the final true resistivity model of subsurface ground from measured apparent resistivity data. These steps, according to quality of data, may sometimes be rather complicated.


33

2.6.1.1 Measurements error (Bad Data). Measurements error or noise contamination mainly effects on the resolution and reliability of the 2D resistivity technique. To apply the imaging technique successfully, great attention must be paid to controlling the observed data quality in the field work, and data processing, and any possibility of minimizing the effects from all kind of errors must be taken. For this reason it is important to investigate the properties of data observation errors and to understand their effects on the imaging results (Zhou and Dahlin, 2003). In general, there are two kinds of measurement errors that cause noise contamination according to Zhou and Dahlin (2003): 1. Electrode spacing errors. The electrode spacing error is caused by the measurement error in electrodes position or inadvertent electrodes sitting up. In most cases of 2D resistivity imaging survey, multi-electrode cable with spacing (e.g. 5m or 10m) are employed along a measurement line. However, it is not uncommon that some portion of the cables cannot be straightened due to rough terrain, vegetation, or positions are shifted to improved electrode contact with the ground. Sometimes the electrode positions are measured with string or tape, with associated risk of electrodes spacing errors to human factor. The magnitude of error in data due to spacing errors, which is relatively low (Szalai et al, 2007), is depending on different electrode array. For as example, 10% spacing error may be produced 20% effect on values for Dipole-Dipole array whereas the Wenner and Wenner-Schlumberger arrays may be given small errors. The small fixed perturbing sources, such as block rocks or small clay lenses, may have the same effect patterns as the spacing


34

errors, but the magnitude may be different. It depends on the difference in electrical properties.

2. Observed potential errors (outliers). The potential errors may be arise from different sources, such as bad electrodes contact, cable insulation damage, site background noise (telluric current, power lines noise and perturbing sources), instrument problems (the wrong current injection) and improper instrument operation. In addition, errors are always possible and become more likely as separations increase (Milsom, 2003). Furthermore, the sufficiently high data density is fundamental important for the resolution of complicated structures. The potential errors may be estimated by normal and reciprocal measurements. However, the analyses of potential errors for different sites and arrays show that the potential errors increases as power of decreases in measured potential, which means that the signal strength of the measurements is very important in controlling the data quality. Therefore, the potential errors depend on strength of signal and vary with sites, times and electrode array. All types of noise contamination (bad data) can be removed by using the commercial resistivity imaging software, RES2DINV, (Loke, 2011). The smooth-constrained least-square inversions is more sensitive to the potential errors than the robust inversion, but the two inversion schemes can produce very similar images except that the robust inversion obtained more blocky and slightly better data misfit (Zhou and Dahlin 2003).

2.6.2.2 Apparent resistivity pseudosection Pseudosection is contoured section, grey scale or colure (Dahlin 1996), of apparent resistivity that look like resistivity section of ground but they are not. It is simply geophysical representation of data (Morison et al, 2004). The pseudosection can be performed on-the-spot in the field for the data quality


35

control and for first interpretation of data, which often provides very valuable guide for the data acquisition (Dahlin, 1996). It gives an idea of 2D distribution of resistivity and can sometimes be used to qualitatively assess geology. One common mistake made is to try to use the pseudosection as final picture of the true subsurface resistivity (Loke, 2011). Therefore, pseudosection can be proved to be very difficult to interpret directly, with different arrays yielding very different results. The pseudosection is made to present raw data, so large inconsistent changes between adjacent data points in pseudosection are often a sign of bad data in the measurements. The more data, the better control over the noise can be (Dahlin and Loke, 1998). It is essential to remove such incorrect data points before moving on to next step in achieving final resistivity model. Moreover, pseudosection is built from apparent resistivity and it is differ largely from true resistivity model of subsurface, therefore, the inverse modeling is needed for farther interpretation. The conventional presentation of pseudosection is placed each measured value at the intersection of two 45 degrees lines through the centers of the dipole (halof 1957 in Edwards, 1977). Thus the presenting of apparent resistivity of data from 2D resistivity survey is plotted them in a section where the electrode separation or effective depth penetration is used for depth (Roy and Apparao 1971). However, Edwards, (1977) used median depth of investigation or pseudo depth to plot the pseudosection, where x-axes is the distance along the line survey which the value of apparent resistivity is plotted at the med point, and the y-axes, the pseudo depth is represented, (Figure 2-15).

2.6.1.3 Interpretation by inversion method The inversion method is used to determine the true resistivity of subsurface from apparent resistivity pseudosection calculated in the field. This method may be divided into three main steps for each iteration (Loke and Barker, 1995).


36

− The first step is to calculate the apparent resistivity values for present model. This normally done by using finite-difference and finite-element, (Loke and Barker, 1995), where the subsurface is divided into large number of rectangular blocks (cells) (Look and Barker, 1996a, Loke et al, 2003). The cells are fixed in position and dimension but they are different in resistivity values. The cell size is normally increased with depth, (Dahlin, 2001), (Figure 2-19). In the “RES2DINV”program the finite differences method used as default except when it has topography, then the finite element method is preferred due to more flexibility in arranging the cells. Actually, these methods are represented the forward modeling subroutine, which is in fact an integral part of any inversion routine, since it is necessary to calculate the theoretical apparent resistivity for model produced by the inversion routine. Then the measured and calculate apparent resistivity values are compared to determine the root main square (RMS) error between them (AL-Menshed, 2011). However, as an example, in the first iteration of inversion routine, the forward model (calculate apparent resistivity) results based on an initial model of 2D distribution of resistivity is compared with actual field data and the initial model is adjusted based on the difference.

Figure (2-19): Rectangular cells with their resistivity points for 2D resistivity survey.


37

For the second iteration of inversion routine, the forward model (calculate apparent resistivity) results based on adjusted model are compared with actual field data, and the model will be modified farther to minimizes error between the two (Barker, 2003), and so on until a specific level of convergence or maximum number of iterations are presented. − The second step is to calculate the Jacobian matrix of partial derivatives. Generally this step can be done by using Gauss-Newton or quasi-Newton methods. Dahlin and Loke, (1998); and Loke and Dahlin, (2002), were mentioned that the quasi-Newton method is based on an analytical calculation of Jacobian matrix of partial derivatives for homogenous half space for the first iteration and then the Jacobian matrices for subsequent iterations are estimated by updating technique. While Gauss-Newton method tends to recalculate the Jacobian matrix of partial derivatives for all iterations. So that it is required more time to calculate but fewer iterations than that of the quasi-Newton method. Furthermore, the Gauss-Newton method gives significantly more accurate results than the quasi-Newton especially for large resistivity contrast. − The third step is to solve the least-square equation where the Gauss-Newton or quasi-Newton methods are commonly used in least-square equation. In general, inversion technique use for 2D and 3D resistivity inversion is regularised leastsquare optimisation method (Loke and Barker, 1996b). Two ways of constrain of regularised least-square optimisation method. Firstly is smoothness constrain least-square method or L2 norm (deGroot-Hedlin and constable, 1990). Secondly, is blocky constrain least-square method or L1 norm (Clarbout and Muir, 1973). According to Loke et al, (2003), the equation of L2 norm is given by:(JTi Ji + wt w)∆ri = JTi gi +λi wt w ri-1

38


Where gi is the data misfit vectors containing the difference between the logarithm of measured and calculate apparent resistivity values (first step), Δri is the change in the model parameters for the (i) iteration, and

−

(the logarithm

of the model resistivity values) is the model parameters vector for previous iteration. J is the Jacobian matrix of partial derivatives. A first-order finitedifference operator is used for roughness filter (W). λ Is the damping factor, it is initially set at a large value and with each iteration the damping factor is reduced until it reaches the minimum value. Furthermore its value depends on the level of the random noise present in the data (Sasaki, 1992). A large value of damping factor is used for higher level of noise (Loke and Dahlin, 2002). The equation of L1 norm is given by:-

Where R

(JTi R Ji + wT R w)∆ri = JTi R gi +λi wT R w ri-1

and R

are weighting matrices introduced. So, the difference

elements of data misfit and model roughness vectors are given approximately equal weight in the inversion process (Loke et al, 2003). However, as a comparison, L2 norm method attempts to minimize the sum of squares of the spatial change in the model resistivity. The resulting inversion model has smooth variation in the resistivity values. While the L1 norm method attempts to minimize the sum of the absolute values of the spatial change in the model resistivity. It tends to produce model with region that are piecewise constant and separated by sharp boundaries. In contrast, L2 norm prone to smear out the boundaries and give resistivity values that are too low or too high if the subsurface region with sharp boundaries (Loke et al, 2003). Finally, from above approach it can be seen that the least-squares equation is represented the inversion method as a whole. While the first and second steps play as change parameters using to solve this equation in the one iteration. The whole process can be carried out in the field on a modern color notebook computer in less than a couple of minutes (Barker et al, 2001).

Chapter three/ Field work

39

Chapter three/ Field work 3.1 Preface Before carrying out the fieldwork, Geological, Topographical, Hydrological and Hydrogeological maps and studies with satellite images are prepared as a first part of fieldwork. Then visiting the study area to determine the location of points when the comparison between arrays will be done, in addition to determine the locations of the 2D and VES soundings in order to delineate the aquifer in the area, taking in account staying away from noise sources such as high tension lines, main roads, Quarry and factories. Four electrode arrays (Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays) are used to make a comparison between them to choose the best array in delineating the aquifers. Therefore, two locations are selected near two wells, one with depth 220m and another with depth 65m. These wells are used as a reference of lithological data for interpretation and comparison between arrays. All 2D and VES soundings are conducted as much as near existing wells for the same purpose.

3.2 Instruments 3.2.1 SYSCAL pro+ The SYSCAL pro+ unit is a resistivity meter is designed for high productivity survey. It combines a containing transmitter, receiver, 2 internal rechargeable batteries (12V) and booster unit in one single case, (Figure 3-1), with external 1200W DC converter for a higher power can be add. The main features of SYSCAL pro are: − 10 reception channels. − Injection channel.


40

− Selection of constant VMN value (automatic injection (VAB)) or constant VAB value. − Sequences programmed by ELECTRE pro (pc software) or by internal programming. − 1000 reading per hour. − Rho and IP measurements. − Graphic LCD (128 x 140 dots) screen. − Memory: 20000 reading and 12 sequences. − Gps input. − Maximum output capabilities: (250W) power, (800V) voltage, (2.5A) current. − 16 keys designed to be used either in the numeric or in the function mode, (Figure 3-2). However, the main functions of the SYSCAL pro can be reached either from these keys or from options of the master menu. In numeric mode, the meaning of keys is obvious. Each time one has to inter a numeric value, the available range for this value will be indicated in the left bottom part of the screen. In the function mode, the following shows the description of these keys. The SYSCAL pro unit can be also used in automatic switching mode (thanks to internal switching board or external switching pro box) for intensive measurements in 2D and 3D. The complete system for electrical survey consists of resistivity meter (from IRIS company- France), portable computer, 1200W AC/DC converter, 12Vcar battery, generator, 12 segment of multi-core cable (for 2D imaging), each segment has 100m length, 2 reels 500m cable, 2 reels 250m cable (for 1D sounding), 120 stainless steel electrodes and 120 card clips for electrodes.


Figure (3-1) SYSCAL pro resistivity meter.

Figure (3-2) The keys of SYSCAL PRO + resistivity meter

41


42

To transfer the data to the PC To check the voltage level of the batteries To check the reception voltage value without injection (ambient noise + Sp) To select the operating mode and the injection parameters To select the electrode array and the number of measuring channels To check, before running a measurement, the grounding resistance value of the electrodes To visualize the results channel per channel (during and after measurement) To scroll up in a menu, to go up in a range, and to change the result display To visualize the results of the whole channels (during and after measurement) To move to the left in the menu bar, to move to the left in the alphanumeric bar, and to move in the channel range To scroll down in a menu, to go down in a range, and to change the result display To move to the right in the menu bar, to move to the right in the alphanumeric bar, and to move in the channel range To stop the acquisition, and to reach the menu bar (at any step of the process) To start the acquisition To stop the Rs check process, to rub some letters or numbers, and to go out of any blocked function and go back to the menu bar To validate an input or a selected function


43

3.2.2 SYSCAL R2 The SYSCAL R2 resistivity meter is fully automatic equipment designed for DC electrical exploration survey. It allows to study the variations of resistivity with depth (vertical electrical sounding) as well as its lateral variation along lines (electrical profiling); (Figure 3-3). The SYSCAL R2 resistivity meter combines the transmitter and receiver in signal unit case, with six 1.5V D-size dry cells located at the base of the unit. The main characteristics for this device are• A two-line 20 characters alpha-numeric LCD display. • A three pins connector for the PC communication. • A switch ON/OFF. • Plugs to connect the electrodes, (A&B for the current electrodes and M&N for the potential electrodes). • Maximum output: 2A current, 800V voltage, 1600w power. • Data storage in internal memory up to 818 measurements in standard mode. • Automatic staking process (to improve the signal/ noise ratio), and display of the number of stacks. • 16-keys function and numeric modes keypad. The function keys are used for setting the unit up, starting and stopping the measurement, and managing the internal memory the numeric keys are used for introducing data such as the station numbers, lengths of the line, etc... However, no confusion can be done between these modes. The fallowing is briefly description for each key function: − BATT: to check the voltage of the battery. − MODE: to select the operating mode (standard or Multi-Electrode). − SET UP: to select the timing parameters. − E. ARRAY: to select the electrode array.

44


− CONFIG: to select the type of parameters that will be displayed during the acquisition − MONITOR: to visualize the level of noise. − SPACING: to introduce the geometrical parameters. − START: to start the injection of current ; intensity, voltage and dispersion of readings will be displayed at each new stack. − STOP: to stop the injection of current. − RESULT: to read the average values of previous parameters, the apparent resistivity and eventually the chargeability (if Rho and IP

mode).

− MEMORY: to store the data in the internal memory. − SERIAL LINK: to transfer the data and to operate in remote control. The SYSCAL R2 resistivity meter, 250W DC/AC converter, motor generator, two reels of 500m, two reels of 250m, two reels of 90m, and stainless steel electrodes, 30cm length and 18cm diameter, were used to complete fieldwork of this study after SYSCAL Pro resistivity meter broke-down, (Figure 3-3).

SYSCAL R2

Reels

Convertor Figure (3-3) Resistivity meter and their accessories

Electrodes

45


3.3 Select array parameters It is used ELECTRE pro program to create the sequences of different electrode arrays before carrying out fieldwork, as shown in tables (3-1) for 60 electrodes, and table (3-2) for 120 electrodes. In table (3-2), each array has 120 electrodes with a-spacing (unit electrode spacing) equal to 10m between them. Also, this table shows several parameters such as (a-spacing, n-factor, depth of investigation DOI, depth of target to be delineating, acquisition time). The most important parameters are a-spacing, and n-factor. The main object of these tables is to select the suitable sequence to achieve real subsurface imaging. For example, in Dipole-Diploe array, when n-factor change from 1–6, the maximum estimated DOI reaches to 156m with coverage data equal to 4455 reading, but when n-factor change from 1-10, the

maximum estimation DOI becomes

201,2m with 5292 reading. This means that from increasing n-factor, it can be getting more estimated DOI and more horizontal and vertical coverage data. Also, the acquisition time increases from 5:06 to 6:04 hour (about 1 hour) respectively. Table (3-1) parameters of the electrode arrays with 60 electrodes Unit ele. Array type

Spacing (a)

No. electrodes

n-factor

Max. Spacing

Level

Max. DOI

readings

Time

Dipole-Dipole

10m

60

1-6n

1-8a

43

126

1282

1:28

Dipole-Dipole

10m

60

1-8n

1-6a

47

131.7

1368

1:34

Dipole-Dipole

10m

60

1-10n

1-5a

49

133

1425

1:38

Wenner-Schlumberger

10m

60

1-6n

1-5a

27

112.4

789

LTH

Wenner-Schlumberger

10m

60

1-8n

1-4a

27

110.8

804

LTH

Wenner-Schlumberger

10m

60

1-10n

1-3a

28

112.8

814

LTH

Wenner

10m

60

19

98.6

570

LTH

Schlumberger reciprocal

10m

60

1-6n

1-5a

27

112.4

789

LTH


10m

60

1-8n

1-4a

27

110.8

804

LTH


10m

60

1-10n

1-3a

28

112.8

814

LTH

46

Chapter three/ Field work Table (3-2) parameters of the electrode arrays with 120 electrodes Unit ele.

Array type

Spacing (a)

No. electrodes

n-factor

Max. Spacing

Level

Max. DOI

readings

Time

Dipole-Dipole

10m

120

1-6n

1-9a

54

156.1

4455

5:06

Dipole-Dipole

10m

120

1-8n

1-9a

72

201.2

5292

6:04

Dipole-Dipole

10m

120

1-10n

1-9a

90

245

5805

6:39

Wenner-Schlumberger

10m

120

1-6n

1-9a

54

223.2

3240

3:43

Wenner-Schlumberger

10m

120

1-8n

1-7a

56

227.5

3304

3:47

Wenner-Schlumberger

10m

120

1-10n

1-6a

56

225.5

3342

3:50

Wenner

10m

120

39

202.2

2340

2:41


10m

120

1-6n

1-9a

54

223.2

3240

3:43


10m

120

1-8n

1-7a

56

227.5

3304

3:47


10m

120

1-10n

1-6a

56

225.5

3342

3:50

Furthermore, it is not preferable to increase n-factor more than 6, for DipoleDiploe, Pole-Diploe and may be Wenner-Schlumberger arrays. After this value, the accurate measurements of the potential are decreased, and the amount of noise will be increased. Actually, it is not really decreasing in the measuring, but with increase n-factor, all possible readings can be measured without needing to reach to the maximum a-spacing, (Figure 3-4).This procedure will increasing the vertical and horizontal coverage and then increasing the estimated of DOI. Also, it can be seen that with increasing n-factor, from 1-6n to 1-10n, the levels can be increased for all arrays. These levels refer to horizontal lines of readings. It is related with DOI, where the DOI is increased with increasing levels (Figure3-5). Wenner-Schlumberger and Schlumberger reciprocal arrays have the same behavior, but they are not show a significant change in the estimated DOI, although n-factor changed from 1-6n to 1-10n and the coverage data increased from 3240 to 3342 reading respectively.


Figure (3-4) The change in n-factor and its effect a-spacing

Figure (3-5) Pattern of levels and a-spacing from 1a to 9a

47


48

In some cases, the change in the n-factor does not mean increasing in DOI because there are not enough electrodes to cover all possible measurements. It needs more than 120 electrodes to get large DOI. This case can be found also in Dipole-Dipole array. Table (3-2) shows that Wenner array gives less estimation DOI, number of measurements, data coverage and acquisition time in comparison with that of the other arrays. This concedes with the rule that Wenner array is easier in the field, due to the spacing between electrodes is equal for each measurement. However, to get more DOI, it must be increased vertical coverage by increasing a-spacing and/or the number of electrodes. Table (3-1) shows same parameters in table (32) except that the number of electrodes becomes 60. The change in n-factor from 1-6n to 1-10n shows no significant change in the estimation DOI for all arrays, because the increasing n-factor needs more electrodes to measure deeper apparent resistivity. Furthermore, it can be seen that the acquisition time is reduced to less than hour (LTH) in this table. However, for the comparison between arrays, it is needed to pick same parameters for all arrays, which are used in this study. So, n-factor more than 6 may be increased the noise effect especially in noisy area (lateral variation inhomogeneity and near surface inhomogeneity), and reducing acquisition time in the field as much as possible when taking measurements for all selected arrays. So, total length of array 1190m (120 electrodes) and 590m (60 electrodes), with a-spacing of 10m, will be used to comparison between electrode arrays. Therefore, depth of investigation between 100m to 220m is suitable for the purpose of this study. These parameters are used as union parameters for all arrays employ in this study. Furthermore, they are used later in delineating aquifers in the study area.


49

3.4 Fieldwork The fieldwork was carried out in three stages with different periods. However, (6) 2D imaging stations, and (11) vertical electrical sounding (VES) points distributed on two profiles were collected in the studied area. Two 2D imaging stations are selected to make the comparison between different arrays, while the other 2D imaging stations and VES points were used to delineate aquifers in the study area. All 2D stations and VES points were conducted parallel to strike of layers. Also cross Vertical Electrical sounding was applied in the two sites to determine any lateral changes in lithology and to check the reliability of 2D imaging stations, (Figure 3-6).

Figure (3-6) The locations of 2D imaging stations and VES points (modified after state company of geological survey and mining)

50


3.4.1 First fieldwork stage 2D imaging station one (2DS1) was carried out using four different arrays (Dipole-Dipole,

Wenner-Schlumberger,

Schlumberger

reciprocal,

and

Wenner array) near BH5, (Figure 3-6). The total length of this station for each array is (1190m), while the electrodes spacing is (10m). Dipole-Dipole array was the first array conducted near BH5. The minimum a-spacing between electrodes is 10m and the maximum a-spacing is 90m. The data coverage is 4455 readings. The second and the third array applied were WennerSchlumberger and Schlumberger reciprocal arrays. For both, the minimum aspacing between electrodes is 10m and the maximum a-spacing is 90m. The data coverage, for both, is 3240. The fourth one was Wenner array. The minimum a-spacing between electrodes is 10m and the maximum spacing 390m. This stage was carried out in period between 14/11/2011 to 19/11/2011. The well (BH5) is drilled to depth 220m by General Commission of Ground Water (GCGW) to discover AL- Mukdadiya aquifer. Which is same location of 2D imaging station one (2DS1), (Figure 3-7).The well lithology used as a reference to make comparison between the different electrical arrays using 2D imaging technique, (Figure 3-8).

BH5

Figure (3-7) Fieldwork of 2DS1 near BH5

51


0

0

10

20

20

40

30

60

40

80

50

100

60

120

Fn.

Scale 1cm=10m

140 160 180 200 220

Figure (3-8)The lithology sections of BH5 & BH6 (General commission for groundwater, 2011).

The 2D imaging station two (2DS2) was collected in a location about 300m from the BH6, because there are farms and street in the area near this well. The electrode number (20) is the closest to the well. Private company drilled the (BH6) before carrying out the fieldwork. Research team from (GCGW) recorded its lithology as a part of hydrological study in the area. However, well depth is 65 meter. The lithology of BH6 is used as reference to make the comparison between the four arrays, (Figure 3-8). However, the total length for each array employ in 2DS2 is 590m, and the unit electrode spacing is10m. Dipole-Dipole array was the first array applied. The minimum a-spacing is 10m and the maximum is 80m, while the coverage data is 1282 reading. Wenner-Schlumberger and Schlumberger reciprocal were the secondly applied in the field. For both, the minimum a-spacing is 10m and the maximum is 50m with data coverage equals to 789 reading. The last one applied was Wenner array. The minimum a-spacing is 10m and the maximum


52

is 190m. The coverage data is equal to 570. Finally, it must be mentioned that the distance between BH5 and well BH6 is (15) Km. After completing the fieldwork of this stage, the interpretation by RES2DINV program shows that the Wenner-Schlumberger array is the best array in delineating aquifer. Therefore, the remaining 2D imaging stations are collected by Wenner-Schlumberger array to determine the aquifers in the study area.

3.4.2 Second fieldwork stage. This stage was conducted in period between (14/12/2011) to (17/12/2011). This stage is considered as a complement to previous stage. 2D imaging station three (2DS3) and four (2DS4) were carried out near BH4 and BH2 respectively, while the 2DS5 and 2DS6 were carried out along profile (B-B`) and (A-A`) as shown in figure (3-6). The total length for each station was 1190m with unit electrode spacing of 10m. Also, two cross VES were conducted by Schlumberger array. The first cross VES (VES-12, and VES-12`), is applied in the same location of 2DS1with length (900m), while the second cross VES (VES-13, and VES13`) is applied in the same location of 2DS2 with length (300m), (Figure 3-6).

3.4.3 Third fieldwork stage. This stage was carried out in the period between 13/5/2012 to 18/5/2012 to take out (11) VES soundings distributed on two profiles (A-A'), and (B-B'). The VES points were measured using the Schlumberger array. The expanding electrodes distance in all VES points was NW-SE direction. The wells of BH1, BH2, BH3, and BH4, (Figure 3-9), is located within or near these profiles.

53


Top soil Clay

BH4

BH3 Top soil

BH2

Top soil

BH1

0

Sand

Clay Silt

Quaternary deposits

Top soil

10

Clay Silt

20

Sand 30

Sand

Sand Silt

40

Silt 50

Clay 60

Figure (3-9) The lithology of BH1, BH2, BH3, and BH4 (General commission for groundwater).

The VES measurements are collected by modifying table of AL. Ane, (1998)from Bhattacharya, and Patra. (1968), (Table 3-3). This table is used to keep the ratio (1/12 ≤ P1P2/C1C2 ≤1/5) as much as possible to reduce the theoretical displacement between filed branches. Profile A-A' has (6) VES soundings with total length equal to (7.5 km). The distance between VES and another is ranging from (0.8km) as minimum distance to (2.5km) as the maximum distance. The length of profile B-B' is equal to (8.2km). The distance between VES and another is varying from (0.9km) to (1,88km), and the number of VES points is (5). All VES points of the profiles are applied parallel to strike of layers where C1C2/2 =700m for each VES. Finally, it must be mentioned here that: 1. VES-5 is applied near 2D imaging station six (2DS6). 2. VES-6 is applied near 2D imaging station four (2DS4) and well (BH2).

54


Table (3-3) Shows electrodes spacing for apparent resistivity measurements (modified after AL. Ane, 1998 from Bhattacharya, and Patra. 1968) Data: Longitude: Latitude: Elevation: Profile (

)

VES (

)

No.

C1C2/2

P1P2/2

P1P2/C1C1

1

1.5

0.3

1/5

2

2

0.3

1/6.6

3

3

0.3

1/10

4

3

0.5

1/6

5

4

0.5

1/8

6

5

0.5

1/10

7

6

0.5

1/12

8

6

1

1/6

9

8

1

1/8

10

10

1

1/10

11

10

2

1/5

12

15

2

1/7.5

13

20

2

1/10

14

25

2

1/12.5

15

25

5

1/5

16

30

5

1/6

17

40

5

1/8

18

50

5

1/10

19

60

5

1/12

20

60

10

1/6

21

80

10

1/8

22

100

10

1/10

23

120

10

1/12

24

120

20

1/6

25

140

20

1/7

26

160

20

1/8

27

200

20

1/10

28

200

50

1/4

29

250

50

1/5

30

300

50

1/6

31

350

50

1/7

32

400

50

1/8

33

450

50

1/9

34

450

80

1/5.6

35

500

80

1/6.3

36

550

80

1/6.8

37

600

80

1/7.5

38

700

80

1/8.7

Notes


55

3. VES-10 is applied near 2D imaging station five (2DS5). 4. VES-11 is applied near 2D imaging station three (2DS3), and well (BH4). Also it must be mentioned here that the SYSCAL Pro + is broken-down before finishing the fieldwork of 2D imaging, so VES points were completed by using SYSCAL R2 resistivity meter.

Chapter four/ Data processing and interpretation

56

Chapter four/ Data processing and interpretation 4.1 1D resistivity technique 4.1.1 Data quality of 1D technique. The apparent resistivity of the VES field curves are drawn on log-log graph paper. However, the plotted curves show very good quality except the final parts for some curves like VES-6 in figure (4-1), and the others in appendix (1). In addition, the cross VES (VES-12, and VES-12`) shows bad quality, (Figure 42). This bad quality, according to Zohdy et al (1974), occurs by lateral inhomogeneity in the ground lithology, measurement errors or equipment failure. Measurements errors and equipment failure are excluded here, because the resistivity meter shows these errors by RS checking in the key board and the standard deviation of the resistivity (noise indicator) can be observed through monitor during measurements. Therefore, all bad data in the field curves are due to lateral inhomogeneity in the ground. However, bad data appear on the field curves as distortions. These distortions may be divided into three phenomena. − Cusps: this phenomenon appears in VES point 1, 2, 8, 9, 10, and 11, (Figure 4-1 b). − Scattering: this phenomenon appears in VES point 5, 7, and 9, (Figure (4-1c). − While the displacement, which appears in all VES curves due to NSI. Figure (4-1) shows an example of this displacement. In figure (4-2), the curves of cross VES (VES-12 and VES-12`) show good quality up to C1C2/2 = 20m for VES-12 and C1C2/2 = 8m for VES-12`then the two curves become distorted strongly and show high scattering.


57

Figure (3-9) show b) bad quality of final portion for VES 2

Figure (4-1) (a) good quality curve for VES11 and (b, c) show the different distortion phenomenon.


58

The high scattering may be caused by high lateral inhomogeneity in lithology at depth, not error in measurements or equipment failure, because the 2DS1, which had been conducted in the same position of cross VES-12, showed highly infection from lateral inhomogeneity for different arrays. Furthermore, the error is excluded in measurements or equipment failure for the same reason mentioned above. On the other hand, the cross VES-13 curves show good quality data, which are applied near 2DS2, (Figure 4-3). Generally, the process of smoothing on field branches is simple because most field curves have good quality, (Figure 4-4), except the cross VES-12, where the smoothing is confined to the first branch and the effected braches are canceled.

4.1.2 Interpretation of 1D resistivity sounding curves. The aim of interpretation of resistivity sounding data is to determine the thickness and resistivity of different horizons from the study of the VES field curves and to use the results to obtain a complete geological picture of the area under investigation, (Battacharya. and Patra, 1968). After completing the smoothing process of field curves, qualitative and quantitative interpretation can be done. Actually, qualitative interpretation is the first step of field curve interpretation, and it gives a primary evaluation of successive horizons. It can be done using several techniques like evaluate and study the field curves, apparent resistivity profiles, apparent resistivity maps, apparent resistivity section and apparent resistivity pseudo-cross section.


Figure (4-2) The distortion of VES 12 and VES12

59


60


61

Quantitative interpretation is used to determine the resistivity and thickness or depth of electrical horizons. It can be applied manually by matching of field curves with theoretical curves and/or analytically using computer programs. However, geological, hydrogeological and wells recorders together are used to support the interpretation of field curves, and to obtain an accurate results about geological sitting of subsurface.

4.1.2.1. Qualitative interpretation. As mentioned above, the qualitative interpretation gives a primary evaluation of subsurface successive horizons. Here, in this study, two different techniques are used for qualitative interpretation of all VES soundings, distributed on two parallel profiles. These techniques are considered the basis of the qualitative interpretation, which precede the quantitative interpretation of the electrical sounding data, (Zohdy et al 1974). This interpretation is supported by the lithology of BH1, BH2, BH3, and BH4.These techniques are:-


62

4.1.2.1.1 Curves type. Using this technique, the field curves are classified together into several groups according to their shapes, reflecting the variation of apparent resistivity distribution underground surface. The groups generally indicate the presence of five to seven electrical horizons, which are conformable with lithological sections of wells, distributed near VES profiles. However, these groups are:− HKHK group. This group includes five VES field curves. These field curves are 1, 3, 4, 8, and 9. This group consists of HKHK, HKHKQ, HKQHK, and HKQQ types. The HKHK type appears in VES-1 and VES-3. It represents six electrical horizons, (Figure 4-5). The first horizon represents high resistivity values compared with the second horizon. It represents the top soil surface, while the low resistivity of the second horizon is caused by presence secondary gypsum within silt layer. The third horizon has high resistivity value compared with the second horizon. It occurs by disappear of secondary gypsum with silt layer. The fourth horizon shows low resistivity values. This reduction in resistivity values is caused by presence of water table with silt layer according to BH1. The fifth horizon shows high resistivity values compared with that of the fourth horizon because of presence of sand layer. The last horizon shows reduction in resistivity values. It is caused by presence of clay layer. the HKHKQ type appears in VES-4, (Figure 4-6). It is similar to HKHK type mentioned above except it has seven horizons. The fourth, fifth and sixth horizons represent the presence of sand layers, some times with littel clay, while the seventh horizon represents the presence of clay layers as shown in BH1.


63


64

HKQHK type appears in VES-8, (Figure 4-7). It consists of seven electrical horizons. Unlike HKHKQ type, its fourth and fifth horizons show decreases in resistivity values. It may be referred to increase of clay content in sand layers or presence of silt layer. The sixth horizon shows increasing in resistivity values. It may be caused by decreases of clay content with sand layer as shown in BH3. The seventh horizon shows decreasing in resistivity value. It is caused by presence of clay layers.

HKQQ type has six horizons. It appears in VES-9, (Figure 4-8). This type shows decreasing in resistivity values in last horizons. This may be caused by presence silt and clayey silt instead of sand layers, until silt layers change to clay layers with the end of field curve.


65

− KHK group. This group includes two types, KHK, and KHKHK, of field curves. KHK type appears in VES-6. This type consists of five horizons, (Figure 4-9). The first horizon shows low resistivity value compared with that of the second horizon. However, it represents the top soil of surface with secondary gypsum, while the second horizon represents the silt layer above water table, which is dry compared with beneath layer. The third horizon shows decreases in resistivity values due to presence of water table according to BH2. The fourth horizon shows increasing in resistivity compared with that of the third horizon. However, the third and fourth horizons represent the same layer. The fifth horizon shows rapidly decreases in resistivity value due to presence of clay layers or clayey silt layers. KHKHK type consists of seven horizons. It appears in VES-2, (Figure 4-10). This type is similar to KHK type in first fourth horizons. The fifth horizon shows relatively low resistivity values due to increasing in clay content within sand layers.

66

ρa (Ω.m)


VES-2 KHKHK Type

C1C2/2 (meter)


67

Then the resistivity values rise up in sixth horizon. It is caused by decreasing in clay content within sand layers. The seventh horizon shows very low resistivity compared with that of the previous horizon, due to presence of pure clay layers. − HAKH group. This group includes two types of field curves. These types are HAKH, and HAKQ. HAKH type represents in VES-10, and VES-11, (Figure 4-11). It consists of six horizons. The low resistivity values of first horizon represent the top soil surface, while the second horizon shows high resistivity values compared with that of the first horizon. This may be done by presence of changing in the lithology of subsurface to silt layers, although the water table presences in this horizon according to BH4. If it is compared with the third horizon, it will be seen that this horizon has low resistivity values than the third horizon. Also, the fourth horizon shows high resistivity value than that of the third horizon. However, these three horizons present one layer (silt layer).


68

The fifth horizon shows decreasing in resistivity values. It is caused by presence of clay or clayey silt layers. The sixth horizon shows rising in resistivity values. This phenomenon may be caused by presence the pebbly sandstone of Mukdadiya (Lower Bakhtiari) Formation. HAKQ type appears in VES-5, (Figure 4-12). This type is similar to previous type, has six horizons, except that the sixth horizon shows low resistivity compared with that of the fifth horizon. The presence of clay layers is caused this decrease in resistivity values in sixth horizon.

AKQ group. This group includes one type of field curves, which represents in VES-7, (Figure 4-13). The AKQ type consists of five horizons. The first horizon shows low resistivity values compared with the second horizon. The first horizon represents of top soil of surface, while the second horizon shows the presence of silt layer. The third horizon shows high resistivity values compared with that of the second horizon although of presence of water table. This rising in resistivity values are caused by presence of sand layers. The fourth horizon shows decreasing in resistivity values compared with that of the third horizon.


69

It is caused by increasing of clay content with sand layers. The fifth horizon represents low resistivity values compared with that of the fourth horizon. It is caused by increasing of clay content with sand layers. From all above curves description, it can be concluded the following notes:a) The area under consideration is characterized by high conductivity due to clay content and salty groundwater, effecting on measured apparent resistivity. Therefore, all measured apparent resistivity are relatively low. b) Most field curves have more than five horizons. The first horizon represents of top soil. The last horizon reflects the presence of clay layer. c) The last horizon of VES-10 and VES-11 shows increasing in resistivity values. This may be caused by presence of pebbly sand stone of Mukdadiya (Lower Bakhtiari) Formation. d) The correlation between lithology sequences of wells and VES curves shows that there are variations in lithology from SE to NW direction.


70

4.1.2.1.2 Apparent resistivity section This technique is constructed in two dimensions, where the X-axis, top horizontal ruler, represents the location of VES soundings, while the bottom horizontal ruler represents the coordinates of the sounding points. However, the apparent resistivity values are distributed along vertical lines located beneath the VES soundings. The Y-axis represents the half electrode spacing (C1C2/2), then the apparent resistivity values are contoured. In general, a liner vertical scale is used to suppress the effect of near surface layer. Two apparent resistivity sections, along (A-A`) and (B-B`) profiles, are constructed using IPI2Win software. The apparent resistivity section along profile (A-A`), (Figure 4-14), reveals the following:a) Decreasing in resistivity values under VES-1 from C1C2/2=10m to C1C2/2= 80m. It may be caused by lens of clay or secondary gypsum. b) Different increases and decreases in apparent resistivity values under given VES points from C1C2/2= 1.5m to C1C2/2= 10m. It is caused by near surface inhomogeneity of top surface. c) Increasing in apparent resistivity values under VES points from C1C2/2=40m to C1C2/2=450m. It may be represented the aquifer under the (A-A`) profile. d) Decreasing in apparent resistivity values under given VES points from C1C2/2= 450m to C1C2/2=700m. This is caused by presence of clay layer.

The apparent resistivity section along (B-B`) profile, (Figure 4-15), reveals the fallowing:a) Increasing of apparent resistivity values under VES (7, 8, and 9) from C1C2/2=1.5m to C1C2/2= 250m may be caused by presence of sand layer.


AB/2 (M)

Apparent resistivity section

Figure (4-14) Apparent resistivity pseudo section along (A-A`) profile

AB/2 (m)

Apparent resistivity section

Figure (4-15) Apparent resistivity section along (B-B`) profile

71


72

b) Decreasing in apparent resistivity values under VES-10 and VES-11 from C1C2/2=1.5m to C1C2/2=30m. It may be represented clay or secondary gypsum with sand deposits. c) Decreasing in apparent resistivity values under the given VES points from C1C2/2= 400m under VES (7) and C1C2/2= 200m under VES (11) to C1C2/2= 700m, is caused by presence clay layer. However, from the above two apparent resistivity sections, the following notes can be concluded:1) Increasing in apparent resistivity values from C1C2/2= 1.5m to C1C2/2=10m under VES points (1, 2, 3, and 4) in profile (A-A`) and from C1C2/2= 1.5m to C1C2/2= 250m under VES points (7, 8, and 9) in profile (B-B`) may be referred to presence old channel in study area. 2) The resistivity values in the lower part of the second section are higher in comparison with that of the first section. It may be caused by presence of silt or sand with clay deposits. 3) These sections show general variation in apparent resistivity of the profiles because they have few VES points in each section. Therefore, they did not give a real picture of subsurface.

4.1.2.2 Quantitative interpretation The main purpose of quantitative interpretation of vertical electrical sounding (VES) is to determine the resistivity and thickness of different electrical horizons of the subsurface. The procedure of such interpretation depends on comparing the field curve with the theoretical curves prepared early in albums such as these of (compagnie general de Geophysique, 1963; Orillana, et al., 1966; and Rijkswaterstaat, the Netherlands, 1969). However, there are several methods used in the quantitative interpretation of electrical sounding, but the most used methods are manual (using curve matching process) and analytical (using computer program).


73

The curve matching process can be divided into two methods. The first called complete curve matching, which requires large number of the theoretical master curves. It is based on complete matching between field curve and theoretical curves. However, theoretical master curves can rarely be used in complete curve matching in view of large number of parameters needed to specify the contrasts in resistivity and ratios of thickness when several layers are present. The second method is partial curve matching using Ebert method, (described below), (Keller and Frischknecht. 1966; Battacharya, and Patra, 1968; and AL-Ane, 1983). The computer programs method can be used, such as IPI2Win (Bobachov et al. 2002), and RESID (Loke, 2001) Software.

4.1.2.2.1 Manual interpretation (Ebert method) Partial curve matching is a most common process used in quantitative interpretation of vertical electrical sounding. It is using to interpretation of two, three, four, or more layers of field curves using two or three layer theoretical master curves with the auxiliary curves of (A, K, H, Q) types. However, the field curves are plotted on double-logarithm transparent graph sheet with a modulus of 62.5 mm, where the apparent resistivity values are plotted on the ordinate and the C1C2/2 along the abscissa. This method can be applied using Ebert method, where the field curve is partially matched with theoretical master curves and then the same procedure is applied to other parts of field curve. This method is based on the minimizing the number of layers of field curve where the first and second resistivity are merged to consist fictitious layer. The fictitious layer will be used in place of the subsurface layers when the next part of field curve is analyzed, (Keller and Frischknecht. 1966).The full interpretation procedure by partial curve matching (Ebert method) can be found in (Keller and Frischknecht. 1966; Orillana, et al.,1966; Battacharya, and Patra, 1968) and other several references. Figure (416) and

74


(4-17) show examples of the results of manual partial curves interpretation for field curves of study area. Table (5-1) shows the result of resistivity and thickness using manual interpretation of Ebert method.

C1C2/2 1 1

Figure (4-16) Quantitative interpretation of Ebert method (manual interpretation)

K

Q

H

C1C2/2 1 1

Figure (4-17) Quantitative interpretation of Ebert method (manual interpretation)

75

Chapter four/ Data processing and interpretation Table (4-1) Show the interpretation results of Ebert method VES

ρa1

ρa2

ρa3

ρa4

ρa5

ρa6

1

17

9

14.2

2.7

8.5

1.4

2

12

23

6.5

14.5

6.5

11

3

9.5

7.6

8.5

7

7.6

3.2

4

15

4.7

11

6.4

9.5

5.5

5

3.6

1.9

8

8.3

7

3.7

6

7.8

18.5

4.8

12.7

7

6

11.5

22

8

13.5

9

9

17

10

11

ρa7

h1

h2

h3

h4

h5

h6

1.4

1.12

2.16

12

232

1.09

0.545

4.5

21.78

76.8

1.5

1.05

14.4

13.2

174

1

3

2.85

24.65

46.9

1.25

1.125

11.76

56

188

2.2

1.6

4

41.3

138

KHK

11.9

5.4

1.9

2.85

14.5

96

AKQ

16.2

13.5

5.5

7.5

1.2

1.32

5

14.85

19

8.8

14.5

12.5

8.5

3.8

1

2.5

4.02

44.66

159

HKQQ

6.7

2.2

5

7

5

7.5

1.05

2.94

12.96

122.9

420

HAKH

16

2.5

7.2

8.7

3.4

12.5

1

3.5

15.09

64

385

HAKH

TYPE

.NO

2

1.25

4.2

HKHK

102

KHKHK

HKHK

315.4

HKHKQ

HAKQ

120

HKQH K

4.1.2.2.2 Computer interpretation (IPI2Win program) IPI2Win program is designed for automatic and semi-automated interpretation of vertical electrical sounding and /or induced polarization data obtained with the most popular arrays used in electrical prospecting. It is used to give quantitative interpretation result and is assumed that the user is an experienced interpreter willing to solve the geological problem posed as well as to fit the


76

sounding curves. The fitting error values represent the difference between theoretical and field curves, (Bobachov et al. 2002). The automatic (forward calculation) interpretation depends on the smoothed values of field apparent resistivity and C1C2/2, which is entered to the IPI2Win program manually using the key board of the computer. Then the program gives resistivity and thickness that reflect the best fit between theoretical curve and field curve, (Bobachov et al. 2002). However, there is a danger in that the results of the forward calculation are not reliable because the following reasons:1. The resistivity and thickness results of forward calculation often do not coincide with the real resistivity and thickness of layered formation of subsurface. 2. Sometimes, the automatic interpretation gives unusual resistivity or thickness values for layer formation, (Figure 4-18), because in automatic interpretation, the program tends to make a best fit between theoretical and field curves. Therefore, the program will change the resistivity, thickness, and sometimes adding or cancelling layers to decrease the fitting error as much as possible, (Figure 4-19).

C1C2/2 (m) Figure (4-18) The unusual values by forward calculation of IPI2Win program

77


Manual interpretation

Forward interpretation

VES-3 HKHK Type

Five layers Four layers

Figure (4-19) The cancelling layers by forward calculation of IPI2 Win program for VES-3

Semi-automated (inverse modeling) interpretation is the main mode of data interpretation implemented in IPI2Win program, (Bobachov et al. 2002). The cause of using semi-automatic interpretation is that the interpretation process is depending on a priory geological data available, and experiment interpreter. The inverse modeling can be used by two ways. The first is adjustment of the resistivity and thickness of forward calculation according to the geological data available, then the program will iterate between the theoretical and field curves to get the best fit. The second includes of entering the manual interpretation results of resistivity and thickness of detected layers to software program. Then the program is going to iterate between theoretical and field curves but with minimum fitting error. The VES points of area under consideration were interpreted using IPI2Win program. The most results of forward calculation are unconformable with inverse modeling, and give low fitting errors for forward calculation, (Figure 420). However, the good smoothing of field curve gives good interpretation results. Also the results of inverse modeling are closest to manual interpretation, (Figure 4-21). The small difference between the resistivity of invers modeling


78

compared with manual interpretation were accepted, because the geological layers have the same rang of resistivity as shown in chapter two, (table 2-1). VES-4 HKHKQ Type

A

B

C1C2

Figure (4-20) Results of A) forward calculation and B) inverse modeling by IPI2 Win program for VES-4

Invers interpretation

Manual interpretation

C1C2/2 (m) Figure (4-21) Results of manual and inverse interpretation for VES-7

VES-7 AKQ Type

79


However, all interpreted VES points by invers modeling show errors fitting less than (3) except VES-6, where the error fitting is more than (3). Table (5-2) shows both, the results of invers modeling and manual interpretation

Table (4-2) Show the interpretation results of Ebert method, and IPI2 Win program VES

ρa1

ρa2

ρa3

ρa4

ρa5

ρa6

ρa7

h1

h2

h3

h4

h5

h6

Method

.NO

1

2

3

4

5

6

7

8

9

10

11

17

9

14.2

2.7

8.5

1.4

1.4

1.12

2.16

12

232

23.4

7.9

17.1

2.8

9.93

0.98

0.747

0.84

2.7

14.5

233

12

23

6.5

14.5

6.5

11

1.09

0.545

4.5

21.78

76.8

102

1

0.602

5.04

16.4

73.4

105

2

13.7

22.1

6.24

17.3

6.39

12.7

1.79

9.5

7.6

8.5

7

7.6

3.2

1.5

1.05

14.4

13.2

174

9.92

7.93

8.97

7.12

8.28

3.24

0.95

1.30

11.58

22.04

169.9

Aux. Inv.

Aux. Inv.

15

4.7

11

6.4

9.5

5.5

1.25

1

3

2.85

24.65

46.9

315.4

21.1

4.42

10.9

5.35

10.8

5.51

2.01

0.81

2.34

4.49

17.8

40.2

308

3.6

1.9

8

8.3

7

3.7

1.25

1.125

11.76

56

188

0.86

1.28

15.6

40.3

200.5

4.14

1.4

7.93

9.5

6.53

4.23

7.8

18.5

4.8

12.7

2.2

1.6

4

41.3

138

7.25

20.9

4.79

12.4

1.48

1.32

3.7

30.9

165

Aux. Inv.

6

11.5

22

11.9

5.4

1.9

2.85

14.5

96

11.6

23.7

10.8

4.71

2

2.84

16.5

120

13.5

9

16.2

13.5

5.5

1.2

1.32

5

14.85

19

120

20.4

120

4.2

Aux. Inv.

1.11

0.75

6.43

11.4

3.8

1

2.5

4.02

44.66

159

4.05

0.98

1.79

6.38

64.8

129.3

14.3

6.67

19

9.36

6.83

8.72

17

9.2

14.5

12.5

8.5

18.09

7.76

16.7

11.02

8.07

3.85

Aux. Inv. Aux. Inv.

6.09

7.5

Aux. Inv.

6.7

2.2

5

7

5

7.5

1.05

2.94

12.96

122.9

420

8.11

2.47

5.99

7.55

4.21

8.53

0.83

3.72

8.89

139

389

16

2.5

7.2

8.7

3.4

12.5

1

3.5

15.09

64

385

17.2

3.17

6.71

9.07

3.27

12.26

0.94

4.12

14.4

70.32

356.6

Aux. Inv. Aux. Inv. Aux. Inv. Aux. Inv.


80

4.2 Cross sounding technique The purpose of cross sounding is to determine the variation in resistivity values underground surface because its sensitivity to lateral inhomogeneity (Boris and Merriam, 2002.). The lateral variation of resistivity values may be caused due to change in lithology and/or to change in quantity and quality of the pore water, (Stiench et al, 1997). If this survey is applied to homogenous and isotropic horizontal layers, the resultant curves will show no change on its form and type. But, if there is lateral inhomogeneity, the resultant curves will be different in its form and types, (Chandra et al, 2004.). Cross VES sounding is applied in two sites within the study area. These sites lie in the same locations as 2DS1 and 2DS2 so as to determine the lateral inhomogeneity in subsurface layers, and to check the reliability of results of 2D imaging sounding. However, anisotropic factor (λ) is calculated for each C1C2/2 spacing using equation (4-1), (Stiench, et al, 1997).

=

.

.

…………………( − )

The first cross VES is carried out in the same position of 2D imaging station one (2DS1). This cross includes VES-12 in direction (NW-SE), parallel to strike of layers and VES-12` in direction (NE-SW) vertical to layers strike. Their field curves, (Figure 4-22), show good measured data quality up to (C1C2/2= 20m). However, the field curves show high distortion, which increases with increasing (C1C2/2) distance. Therefore, the anisotropic factor (λ) is calculated, as shown in appendix (2), for smoothed curves only (up to C1C2/2=20m). The relationship between (λ) values and (C12C2/2) is drawn with vertical linear scale, (Figure 4-23). The maximum (λ) value is (1.14Ω.m) shown at (C1C2/2=5m) and the minimum (λ) value is (1Ω.m) shown at (C1C2/2=2m).


81

After C1C2/2=20m there is high scattering (bad data) in apparent resistivity values due to high lateral inhomogeneity and similar phenomena also shown in the 2DS1 measurements. This lateral inhomogeneity may be occurred in lenses of gravel and/or sand deposits.

VES (12)

VES (12`)

Figure (4-22) Filed curves of VES (12) and VES (12`)

VES (12`)

VES (12)

Figure (4-23) Smoothed filed curves of VES (12) and VES (12`) and their anisotropic factor (λ)

82


The second cross VES, includes cross sounding of VES-13, and VES-13`, which are collected in direction (NW-SE) and (NE-SW) respectively, and have the same position of 2D station two (2DS2). VES-13 shows field curve of (HAKQ) type, while the type of VES-13` curve is (AKQ). In spite of high similarity in shape between two types, there is a difference between the two curves caused by differentiation in the subsurface lithology. The value of anisotropic factor (λ) is calculated for each (C1C2/2) spacing, as shown in appendix (2). The relationship between (λ) values and (C1C2/2) is drawn with vertical linear scale, (Figure4-24).The maximum (λ) value is (1.51Ω.m) shown at (C1C2/2=3m), which may be referred to anisotropic or inhomogeneity in sediments near subsurface. The minimum (λ) value is (1Ω.m) shown at (C1C2/2=10 and 15m). It may be referred to no high anisotropic or inhomogeneity in sediments under surface.

VES (13) ρ (Ω.m)

ρ1=3.2 Ω.m ρ2= 2.6Ω.m ρ3= 48 Ω.m ρ4=75 Ω.m ρ5= 9 Ω.m ρ6= 2 Ω.m

VES (13`) ρ (Ω.m)

Thickness (m)Depth

d1= 1.3m H2= 3.56m d2= 4.86m H3= 2.43m d3= 7.29m H4= 5.52m d4= 12.81 H5= 144m d5= 156.81m

H1= 1.3m

VES (13)

ρ1=4 Ω.m ρ2= 7.8Ω.m ρ3= 42 Ω.m ρ4= 7.5 Ω.m ρ5= 6.2Ω.m

Thickness (m)Depth H1= 1.35m d(m) 1= 1.35m

d2= 4.4.72m d3= 15.22m H4= 131.6m d4= 146.82m H2= 3.37m H3= 10.5m

VES (13`)

Figure (4-24) Interpretation results of VES-13, VES-13`, and the relationship between (λ) and (AB/2) spacing


83

4.3 2D imaging technique 4.3.1 Data quality of 2D imaging technique. Two stations (2DS1 and 2DS2) are selected from six 2D stations to make the comparison between the four different electrode arrays. To achieve high quality data, the electrodes are placed at exact distances with electrode spacing of (10m). Furthermore, all profiles lie on a straight line on flat area. Saltwater is used for each electrode after strongly planted in the ground to reduce the effect of contact resistance, (Figure 4-25). If contact resistance remained high, then saltwater reapplied again. If it is still high, the electrodes are moved slightly and saltwater reapplied. However, to ensure that the bad data is not caused by equipment failure or by electrode spacing error, two cross VES soundings are applied in the same position of 2DS1 and 2DS2. They are discussed in paragraph (4.2).

Figure (4-25) electrode watered by saltwater.


84

Four different arrays (Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays) are applied in the 2DS1 near BH5. The distance between electrodes is (10m), while the total length of the line equals (1190m). The measured data using Wenner array are appeared good quality data, (Figure 4-26). The measured by Wenner-Schlumberger, and Schlumberger reciprocal arrays have less quality, (Figure 4-27and 4-28) respectively, while the measured using Dipole-Dipole are bad, (Figure 4-29). This mean, after decreasing the effect of spacing error and contact resistance, that the Dipole-Dipole array is highly affected by noise, due to near surface inhomogeneity (NSI) and lateral subsurface inhomogeneity, (Figure 4-29). The other electrode arrays are showed less effected. The Wenner array is the lesser one affected by noise, (Figure 426). This noise can be divided into two types, unusual data measurements and negative data measurements. The unusual data measurements are caused due to high lateral and vertical inhomogeneity in subsurface and the effect of NSI near current and potential electrodes. The negative data measurements can be occurred by two reasons. 1) The current or the potential electrodes have been connected with reversed polarities. 2) The noise level may be much higher than the signal level such as long distance between C1 and C2 and low current (ABEM Instrument AB, 2009). For example, the maximum a-spacing between current and potential electrodes for Dipole-Dipole array is (90m), where the n-factor value reaches to (6). Therefore, the total length of Dipole-Dipole array will be equaled to (720m). The electrical current emitting from (C1) or (C2) needs to pass a distance between (550-720m) or (640m) as an average. In Wenner array, the maximum a-spacing is (390m). Therefore, the distance needs to through by electrical current between (C1-P1) and (C2-P2) is (390m), while between (C1-P2) and (C2-P1) is (780m) and so on for Wenner-Schlumberger and Schlumberger reciprocal array.

85 Chapter four/ Data processing and interpretation

Bad data due to lateral inhomogeneity

Figure (4-26) Locations of bad data in Wenner profiles for 2DS1

2DS1/ Wenner array


2DS1/ Wenner-Schlumberger array

Figure (4-27) Locations of bad data of Wenner-Schlumberger profiles for 2DS1


2DS1/ Schlumberger reciprocal array

Figure (4-28) Locations of bad data of Schlumberger reciprocal profiles for 2DS1


Bad data due to NSI

2DS1/ Dipole-dipole array

Figure (4-29) Locations of bad data of Dipole-Dipole profiles for 2DS1


89

Therefore, the signal strength decreases with increase of the distance between current and potential electrodes and/or with the noise level increase. For this reason, Dipole-Dipole array is the most one affected by the negative apparent resistivity data, while the Wenner array is the least affected compared with other arrays, because of the Wenner array has better signal to noise ratio than that of others, (Dahlin, and Zhou, 2004). However, the prosys II program (IRIS Instruments, 2005), is used to download the data measurements from resistivity meter to computer after each survey. Then, exported and saved in .DAT extension to be read by RIS2DINV program. However, it is noted that the prosys II program transforms all negative data to positive during exporting and saving in .DAT extension. Figure (4-26), (4-27), (4-28), and (4-29) show apparent resistivity points of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays in profile form, where the bad data (unusual and negative measurements) stand out from the rest of profiles without changing their values. Also, profiles of Dipole-Dipole array are affected by bad data due to NSI (oblique forms). Actually, the effect of near NSI for different electrodes arrays return to the way of the measurements taken. For example, in Wenner array, the distance between its electrodes increases for each measurement, while in Dipole-Dipole array the distance between potential and current electrodes remains fixed for several measurements. Furthermore, its potential electrodes are always outside current electrodes. For this reason, Dipole-Dipole array is highly affected in all measurement by NIS, (Figure 4-29), compared with other arrays in figure (4-27) and (4-28), while, in Wenner array, the effect of bad data increases from right to left and it increases with depth, (Figure 4-26). However, its profiles are affected by bad data caused by deep high lateral inhomogeneity (as shown in cross VES-12 and VES-12`), and the effect of NSI is small compared with other arrays. The Wenner-Schlumberger and Schlumberger

90


reciprocal arrays, (Figure 4-27, and 4-28) respectively, show same behavior of Wenner profiles but the effect of bad data are more than those of Wenner array for NSI and deep high lateral inhomogeneity. They are less than those of the Dipole-Dipole array. Figure (4-30), shows the effect of bad data on the measured apparent resistivity pseudosections of the four arrays. However, the bad data appears as oblique forms and as spots, caused by NSI, within the pseudosections. They are increased

in

Dipole-Dipole

pseudosection

and

decrease

in

Wenner

pseudosection. In comparison with the cross sounding. The (VES-12, and VES12`) also, shows high distortion in field curves, which are caused by high lateral inhomogeneity. However, they do not show a sign of existence of NSI.


NW

Bad data

SE

Figure (4-30) Lhe effect of bad data on the measured apparent resistivity pseudosections of the four arrays in 2DS1 when using 120 electrodes


92

The four arrays are applied in the 2DS2, but with total length of (590m) and electrode spacing of (10m). However, all arrays show very good quality data except Dipole-Dipole array, which shows relatively bad data in comparison with other arrays, as shown in figure (4-31) and (4-32) and appendix (3). Compared with 2DS1, the negative data numbers are very small because of the noise level is much lower than the signal strength. Figure (4-31) and (4-32) show the profiles of Dipole-Dipole and Wenner measurements respectively. The bad data appear strongly in Dipole-Dipole profiles at a-spacing equal to (20) and they increase with depth up to a-spacing equal to (80m). The Wenner profiles show small oscillations in apparent resistivity under all electrodes. The small oscillations occur due to high change in resistivity of the upper soil. This phenomenon also appears obviously in Wenner-Schlumberger and Schlumberger reciprocal profiles, as shown in appendix (3). Figure (4-33) shows the pseudosections for the four arrays. In Dipole-Dipole pseudosection, the bad data appear as oblique forms and as spots (blue color). The Wenner, Wenner-Schlumberger and Schlumberger reciprocal arrays show clear pseudosections. In comparison with the cross VES, the (VES-13, and VES13`) also, shows very smooth field curves due to the absence of NSI effect and lateral change with depth.


2DS2/ Dipole-dipole array

Figure (4-31) Locations of bad data of Dipole-Dipole profiles for 2DS2 when using 60 electrodes

Bad data


2DS2/ Wenner array

Figure (4-32) Locations of the oscillations in Wenner profiles for 2DS2 when using 60 electrodes

Small oscillation due to near surface variation in resistivity


NW 0.0

0.0

0.0

0.0

160 320

320

320

160

320

160

160

480

480

Bad data due to NSI

480

480

Figure (4-33) The effect of bad data on the measured apparent resistivity pseudosection of the four arrays for 2DS2 when using 60 electrodes

SE


96

4.3.2 Data processing and inversion For data inversion, the RES2DINV program version 3.57.37 is used (Geotomo software, 2008). The RES2DINV is a computer program that automatically determines a 2D resistivity model of the subsurface for data obtained from electrical imaging (Griffiths and Barker, 1993). According to Geotomo software (2008), this program is designed to invert large data sets (with about 200 to 21000 data points) with system within large number of electrodes (about 25 to 16000 electrodes). A forward modeling subroutine is used to calculate the apparent resistivity values, and a non-linear least-squares optimisation technique is used for the inversion routine. The program supports both the finite-difference and finite-element forward modeling techniques, (Loke, 2011). This program can be used for surveys using the Wenner, Pole-Pole, Dipole-Dipole, Pole-Dipole, Wenner-Schlumberger and equatorial Dipole-Dipole (rectangular) arrays. In addition to these common arrays, the program even supports non-conventional arrays with an almost unlimited number of possible electrode arrays. The 2D model used by this program divides the subsurface into number of rectangular blocks. The purpose of this program is to determine the resistivity of rectangular blocks that produces an apparent resistivity pseudosection that agrees with the actual measurements. For Wenner and Schlumberger array, the thickness of the first layer of blocks is set at 0.5 times of electrodes spacing. For Pole-Pole, Dipole-Dipole and Pole-Dipole arrays, the thickness is set to about 0.9, 0.3 and 0.3 times of electrodes spacing respectively. The thickness of each subsequent deeper layer is normally increased by 10% (or 25%). The user can also change the depth of layers manually. The optimization method basically tries to reduce the difference between the calculate and measured apparent resistivity values by adjusting the resistivity model blocks. A measure of this difference is given by root-mean-squared (RMS) errors. However, the model


97

with lowest possible RMS error can be sometimes showed large and unrealistic variations in the model resistivity values and may not always be the best model from geological prospective. In general, the most prudent approach is to choose the model at the iteration after which the RMS errors are not change significantly. This usually occurs between the 3rd and 5th iteration. The inversion routine used by this program is based on regularised leastsquare method. It divides into smooth inversion and blocky (robust) inversion, where the smooth inversion gives better results in areas has gradual changes of subsurface resistivity (Loke et al, 2003). Therefore, it is used to inverse the measured apparent resistivity in this study. One advantage of this method (inversion routine) is that the damping factor and flatness filters can be adjusted to suite different types of data. In this program, large initial damping factor is used for very noisy data (for example 0.3). If the data set is less noisy, the small damping factor can be used (for example 0.1). The inversion routine generally reduces the damping factor after each iteration. However, the minimum limit for damping factor must be set to stabilize the inversion process. The main value should be set to about one-fifth the value of the initial damping factor. For flatness filter ratio, the program uses same weight for vertical and horizontal structures (for example 1.0). However, if the main anomalies in the pseudosection are elongated vertically, it can be used higher weight (for example 2.0) for vertical flatness filter. If the main anomalies in the pseudosection are elongated horizontally, it can be used smaller weight (for example 0.5) for horizontal flatness. The program supports a new implementation of the least-squares method based on quasi-Newton optimization technique (Loke and Barker, 1996a) and the conventional Gauss-Newton method. The program also supports blocky constrain least-square method and other inversion methods. However, more


98

information about the inversion method of this program can be found in (Loke, 2011). Data quality must be enhanced before starting inversion method for 2DS1 and 2DS2 stations. However, two types of filters will be used as pre-inversion process. Each filter will be used to make the inverse model resistivity section, and then the results of two filters will compare to select the best one.

4.3.2.1 Filtering process and inversion of 2DS1 4.3.2.1.1 Manual filtering and Inversion of 2DS1 The bad data can be easily removed manually by switch of the extermination bad data point option in RES2DINV program. The bad data appears as a profiles form. Then it can be selected the bad data points by click on it using mouse pointer. Appendix (4) shows the profiles of the four arrays after manual filtering, where their distortions by bad data appear on them although large data removed from each one. The difficult faced in manual filtering is that the picking of cross data points to remove (in profile form) becomes very difficult in noisy data. Because, it does not have an idea on the value of removed point, which may be considered as good quality data or bad data. In other words, many of good quality data may be removed by this way with the others bad data due to unknown values of their apparent resistivity in the profile form. Therefore, it becomes uncontrolled method with very noisy data. Furthermore, manual filtering removes the selected data only without making any adjustments on remain data values. Because of very noisy data in (2DS1), a large damping factor is used (0.3) and the flatness filter is set to equal (0.3). The results of inversion process for the arrays measurement are shown in figure (4-34) and appendix (5). However, many notes can be concluded from pseudosections and invers models for these arrays after manual filtering:


NW

Figure (4-34) The measured and calculated apparent resistivity and the inverse models of Wenner-Schlumberger array in 2DS1 after manual filtering

SE

100


1. The pseudosections in figure (4-35), show distorted image for all arrays but they have less distortion compared with what shown in figure (4-30). The maximum distortion appears in Dipole-Dipole pseudosection that the apparent resistivity increases from right to left side and with the depth. Also, the apparent resistivity values increase vertically from about (11.4Ω.m) to more than (292 Ω.m).On the other hand, the Wenner pseudosection appears more uniform than that of the others, and its apparent resistivity decreases vertically with range between (57.7 - 292 Ω.m) under electrodes number (0 - 57) to less than (1.00 Ω.m) with increasing of depth. The Wenner-Schlumberger and Schlumberger reciprocal arrays show approximately

same

behavior

in

their

pseudosections,

although

Schlumberger reciprocal appears less effected by noise than WennerSchlumberger array. However, their apparent resistivity values are varied vertically between (2.25-130 Ω.m) for Wenner-Schlumberger and between (5.06-292 Ω.m) for Schlumberger reciprocal. 2. As shown in figure (4-35), the maximum distortion appears on the left side and decreases toward right side. This may be referred that the source of the noise (lateral inhomogeneity) may be occurred at left (under electrodes number between (0-64)). its effect decreases toward right side. 3. Although the horizontal and vertical coverage of Dipole-Dipole array is more than that of others, but the pseudosections of Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays give better primary image of subsurface. 4. The edges of the pseudosections show sharp corners. It is occurred due to manual filtering, (Figure 4-35).


NW

Figure (4-35) The measured apparent resistivity pseudosections of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after manual filtering

SE


102

5. Although Dipole-Dipole array has more data points than that of the others, but its inverse model is completely failed in delineating the subsurface layers, (Figure 4-36). 6. Dipole-Dipole array shows highest RMS error (135%), and gives less DOI than that of the others. The reducing of DOI is due to two reasons. The first is the effect of the removing bad data on the DOI. The second is the relation between a-spacing and n-factor (will discuss later). However, this DOI is conformable with expected DOI in table (3-2) in chapter three. The Schlumberger reciprocal and Wenner inverse models, (Figure 4-36) show relatively good delineating of underlying layers, although there are distortions in their models. For example, Schlumberger reciprocal inverse model shows a resistive lens under electrodes number (61-66). This resistive lens appears as a one mass with the underlying blocks, which they have same resistivity values. They make a distortion in the inverse model, causing difficult in recognize the boundaries between them. Furthermore, the lithological section of BH5 is not completely corresponding with the inverse model Because of this distortion. In Wenner inverse model, the resistive lens appears more elongated but it is still not coinciding with the lithological section of BH5. However, the two models section show good coinciding with the lithological section where the layers become more resistive (e.g. pebbly sandstone of AL- Mukdadiya Formation). 7. Although Wenner-Schlumberger inverse model has relatively high RMS error (53.3%) compared with those of Wenner and Schlumberger reciprocal, (Figure 4-36), it gives excellent delineating of underlying layers and aquifers, which are completely coinciding with the lithological section of BH5. Furthermore, it gives the biggest DOI than the others. It is more than expected DOI in table (3-2). Like this RMS is showed also in (Ahmed and Sulaiman, 2001; and Srinivasamoorthy, et al 2009).


NW

220

220

220

Dipole-Dipole

Wenner-Schlumberger


Wenne r

BH5

Depth = 158m No. data = 2055 Levels = 54




SE

Figure (4-36) The inverse models of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after manual filtering


104

8. The Wenner-Schlumberger array is the best in delineating layers and aquifers comparing with those of other arrays. 9. All inverse models in figure (4-36) show two resistive anomalies except for Dipole-Dipole. They represent lenses of gravel and/or sand belongs to valley fill deposits, (Figure 3-6). The first one, which is the biggest, occurs under electrodes between (0-41) at the left side of the inverse model. The second appears small and occurs under electrodes (84-119). They are surrounding by low resistive layers. Their resistivity are varied between (57.7 Ω.m) to more than (292 Ω.m) and occur at depth between about (3070m). These resistive anomalies may be considered as a source of deep lateral inhomogeneity, causing bad data in all electrode arrays.

4.3.2.1.2 Automatic filtering and inversion of 2DS1 The measurements for each array in BIN format are filtered using prosys II version 03.02.02 program. According to IRIS Instruments (2005), The Prosys II software allows to run an automatic filtering by the "Processing|Automatic Filtering " menu. This option allows filtering the data in a classical way (it contains, by default, some rejection threshold for the main parameters, and some lateral data smoothing by an averaging on a user specified distance). So, this filtering can be used in most of any standard cases. This option uses the parameters of the "Filter.ini" file present in the Prosys II directory. Structure of the "Filter.ini" file, shows by-default values: VMin=-15001 VMax=15001 Imin=0.5 IMax=99998 Rhomin=0.100000001490116 RhoMax=20000 DevMax=20 Mmin=0 MMax=120 [Median]

(minimum reception voltage value allowed) (maximum reception voltage value allowed) (minimum injection current value allowed) (maximum injection current value allowed) (minimum resistivity value value allowed) (maximum resistivity value value allowed) (maximum deviation factor value allowed) (minimum chargeability value allowed) (maximum chargeability value allowed) (median average)

Chapter four/ Data processing and interpretation NbSpacing=1 [Slide] NbSpacing=0.5 Execute=1

105

(sliding average) (1=overload data rejected)

The removed bad data points by this filter are less than those removed by manual filter. As shown in appendix (6), the profiles appear more smooth and less bad data in comparison with the profiles produced by manual filtering. However, Dipole-Dipole and Wenner-Schlumberger profiles still show the standup of bad quality data points in the first upper profiles and the other has less bad data. Therefore, a companion between automatic and manual filtering is used by removing the remained bad data points manually after automatic filter. However, large damping factor of (0.3) with flatness filter of (0.3) is used to inverse the filtered data. The results of inversion process for these filtered data have high similarity with inversion results of manual filtering, (Figure 4-37 and Appendix 7). However, several notes can be concluded from their pseudosection and inverse models after inversion process, (Figure 4-38 and 4-39) respectively. These notes are: 1. All pseudosections in figure (4-38) appear more uniform compared with those in figure (4-35), and they give clear picture for the distribution of apparent resistivity measurements. 2. Diploe-Dipole pseudosection shows vertical variation in apparent resistivity values, which are between (3Ω.m) to more than (292 Ω.m). Also, between electrodes numbers (0-44), the apparent resistivity values increase rapidly from (57.7 Ω.m) to more than (292 Ω.m), while the low apparent resistivity values appear as small lenses near surface. 3. The edges of Diploe-Dipole pseudosection, (Figure 4-38), appear with corner shapes similar to what shown in figure (4-35).


NW

SE

Figure (4-37) The measured and calculated apparent resistivity and the inverse models of Wenner-Schlumberger array in 2DS1 after automatic filtering


NW

Figure (4-38) The measured apparent resistivity pseudosections of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1after automatic filtering

SE


108

They are caused by filtering process and its mean that many of removed bad data are concentrated on the edges of pseudosection. 4. The Wenner-Schlumberger and Schlumberger reciprocal show some distortion in their pseudosections. The Schlumberger reciprocal appears more affected than Wenner-Schlumberger, although, the removed data from Wenner-Schlumberger are more than removed from Schlumberger reciprocal. However, they are less from those removed by manual filtering. This approach conforms to the other arrays. The maximum distortions are concentrated on the left side and decrease toward right side. The cause of such distortion was mentioned above in paragraph (4.3.2.1.1). Their apparent resistivity values vary vertically between (3-57.7 Ω.m), and increase with depth. 5. On the other hand, Wenner shows a clear and uniform pseudosection compared with the others in figure (4-38). Its apparent resistivity values decrease vertically with depth starting from about (150 Ω.m) and ending with (5.06 Ω.m) at pseudo depth of (187m). Then it increases to (57.7 Ω.m). 6. As shown in figure (4-39), again the Diploe-Dipole inverse model is failed completely in delineating the layers under depth nearly between (20-40m) to depth (158m). Although, it succeeds in delineating the layers and surface inhomogeneity from ground surface to depth ranging between (20-40m) to the surface, but its image still not clear and is not shown obvious delineating between them. 7. The inverse model of Wenner-Schlumberger, (Figure 4-39), gives an excellent and prudent image for subsurface layers, which is coinciding completely with lithological section of BH5. Furthermore, it shows clear delineating between conductive and resistive layers.


NW

220

220

220

Diploe-Dipole

Wenner-Schlumberger


Wenner

BH5





SE

Figure (4-39) The inverse models of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal and Wenner arrays respectively in 2DS1 after automatic filtering


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8. The inverse model of Schlumberger reciprocal, (Figure 4-39), is relatively succeeded in delineating underlying layers. This inverse model does not coinciding completely with lithological section of BH5. Furthermore, the resistive lens, which is appeared in inverse model of this array in figure (4-36), does not appeared in this inverse model due to automatic filtering. The resistivity values of inverse model are between (1.00 Ω.m) to more than (292 Ω.m). 9. Although Schlumberger reciprocal inverse model has higher data number, (equal to 2610), and low RMS error, but Wenner-Schlumberger gives the best inverse model than the Schlumberger reciprocal inverse model, (Figure 4-39).While the Schlumberger reciprocal gives more DOI than Wenner-Schlumberger model. 10. Wenner inverse model delineates the underlying layers, but it is not corresponding with lithological section of BH5. Furthermore, it is failed in delineating of resistive layers at depth nearly (140m). However, these layers are not appeared obviously with depth, and this may mean that its vertical resolution decreases rapidly with depth. This approach is conformable to Dipole-Dipole array also. 11. All inverse models in figure (4-39) show presence of resistive layers (thin layer) except Dipole-Dipole inverse model, and their horizontal extend change from model to another, and generally occur at depth between (10100m). In general, it is characterized by resistivity values range between (40Ω.m) to more than (292 Ω.m). As mentioned in paragraph (4.3.2.1.1), it may be considered as a source of deep lateral inhomogeneity in the left side of the pseudosections, reflecting the gravel or sand deposits. 12. As shown in figure (4-36) and (4-39), the depth of investigation for the four arrays obtained from their inverse models after automatic filtering are more acceptable than those of after manual filtering, which is conformable with the expected DOI for each array (table 3-2 in chapter three). This difference


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in DOI may be occurred due to the effect of bad data in the inverse model sections.

4.3.2.2 Filtering process and inversion of 2DS2 4.3.2.2.1 Manual filtering and Inversion of 2DS2 Because of good quality data obtained from Wenner, Wenner-Schlumberger and Schlumberger reciprocal arrays, the filtering process becomes simple and fast, as shown figure (4-40), and figure (4-41). For example, in the profiles of Schlumberger reciprocal array, seventeen bad data points are removed manually. Therefore, the automatic filtering is canceled. It becomes useless for these arrays. To inverse such data, a small damping factor (0.1) is used with flatness filter that is equal to (0.3). The Dipole-Dipole array shows relatively noisy data compared with that of others. Therefore, manual filtering is used to remove bad data. Then, inversion process is applied for this data, but with large damping factor (equal to 0.3). The inversion results for the four arrays is shown in figure (4-42), and appendix (8). Several notes are concluded from their pseudosections and their inverse models sections. 1. As shown in figure (4-41), the pseudosection of Dipole-Dipole array shows distortion (oblique forms), but the spots are disappeared completely compared with what shown in figure (4-33). The apparent resistivity values decrease vertically, and their values ranges from (0.581Ω.m) to less than (36.5 Ω.m). The high apparent resistivity values between (18.3-36.5 Ω.m) appear as lenses distributed along pseudosection. 2. The pseudosections of Wenner-Schlumberger and Schlumberger reciprocal are showed same behavior in distribution apparent resistivity as shown in figure (4-41). In general, the apparent resistivity values decrease vertically and have range between (5-34 Ω.m) for Schlumberger array, and between (4.93-34.4 Ω.m) for Schlumberger reciprocal array.


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Figure (4-40) The measured and calculated apparent resistivity and the inverse model of Wenner-Schlumberger array of 2DS2 after manual filtering


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Figure (4-41) The measured apparent resistivity pseudosections of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner array s respectively in2DS2 after manual filtering


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The high apparent resistivity values are concentrated between electrodes number (9 to 53), reaching to pseudo depth about (30m). 3. Wenner pseudosection shows vertical decreases in measured apparent resistivity values, which range between about (6.5-30 Ω.m). The high resistivity values are concentrated in the right side of the pseudosection, (Figure 4-41). 4. In all pseudosections in figure (4-41), low apparent resistivity values appear under electrodes number (0-5), which may be indicated the presence of clay layer under these electrodes. 5. As shown in figure (4-42), the Dipole-Dipole inverse model is relatively detected the upper resistive layer only, while there is some difficult in recognize the other layers. In comparison with BH6, the resistive layer represents gravel deposits. 6. Although, Schlumberger reciprocal inverse model gives significant results in delineating layers, (Figure 4-42), But, it does not show completely coinciding between its inverse model and the lithological section of BH6. It is failed in recognize the lower boundary of low resistivity layer. Furthermore, the inverse model of Schlumberger reciprocal array shows shafting in its resistivity zones with increasing depth. The resistivity values of this inverse model range from (3.5Ω.m) to more than (34.4Ω.m). Moreover, it gives the maximum DOI than the other arrays. 7. As shown in figure (4-42), the Wenner and Wenner-Schlumberger inverse models give excellent results in delineating layers (and aquifers). The results obtained from Wenner-Schlumberger inverse model are more significant than those of the Wenner inverse model. Wenner-Schlumberger inverse model shows completely coinciding with the lithological section of BH6.


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Although Wenner inverse model shows small shaft in lower boundary of low resistivity layer and the lithological section of BH6, but it is still able to show significant coinciding between them. However, the two inverse models succeed in recognizing the low and high resistivity layers and give very close images and RMS errors. 8. As shown in figure (4-42). Schlumberger reciprocal array gives the maximum DOI (127m), while Wenner array gives the minimum DOI (106m). Dipole-Dipole and Wenner-Schlumberger arrays appear the same DOI, (122m).

4.3.2.2.2 Automatic filtering and inversion of 2DS2 An attempt is applied to filtering the data measurements of Dipole-Dipole array using Prosys II. However, the inversion results of automated DipoleDipole data show the flowing notes: 1. As shown in figure (4-43), the measured apparent resistivity pseudosection of Dipole-Dipole appears clearer in comparison with that shown in figure (4-41). Its data number is (1198), while the data number of the manual filtering is (1042). Therefore, the removed bad data by automatic filtering are less than removed by manual filtering. The apparent resistivity values decrease vertically and range from (1.29Ω.m) to more than (30.9 Ω.m). Furthermore, the high apparent resistivity values are concentrated in the upper part of pseudosection. 2. The inverse model of Dipole-Dipole delineates the layers and the aquifers (Figure 4-43). But it is failed in recognizing between the layers especially from depth at (30m) to the end of the inverse model (at depth equal to 122m). Because, this inverse model is not coinciding with lithological section of BH6.


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This model is not conceded with the inverse models of WennerSchlumberger, Schlumberger reciprocal and Wenner array in figure (4-42), because the Dipole-Dipole array has bad vertical resolution, (Loke, 2011). The RMS error of the Dipole-Dipole inverse model produced after automatic filtering is less than that of the manual filtering.

4.4 comparisons between manual and automatic filtering As comparison of inversion results for manual and automatic filtering, the following points can be concluded. a. All inverse models for 2DS1in figure (4-39) give low RMS errors and high data numbers compared with those in figure (4-36). It is also shown in figure (4-43), and figure (4-42) for Dipole-Dipole inverse model of 2DS2. This means that the automatic filtering gives significant results and is better in removing bad data. b. The two filters show significant and approximately same results for Dipole-Dipole, Wenner-Schlumberger and Schlumberger reciprocal inverse models. In Wenner inverse model sections, the automatic filtering is better than the manual filtering and the difference between them in recognizing the resistive bed occurs because in Wenner array, the vertical resolution decreases rapidly in comparison with Wenner-Schlumberger and Schlumberger reciprocal arrays. c. The manual filtering is difficult, uncontrolled and take a lot of time especially when bad data increase. While, the automatic filtering is easy and take several seconds during its processing. d. One property is noted in automatic filtering process that the automatic filtering does not remove all bad data. It tends to smooth the values of some bad data to make them conformable as possible as with the others good quality data, while the manual filtering removes bad data and dose not smooth any data.


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e. According to the type of array, quality of data, and the conditions of study area, the interpreter can choose any one of these filters. However, it is preferable to use manual filtering for data with little noise level.

4.5 Array parameters relationship The parameters such as a-spacing, n-factor, DOI and resolution of arrays are effected and affected by others. According to these parameters and/or lithological setting of study area, the array can be succeeded or failed in delineating of under laying aquifers (or layers). However, the results obtained from Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays with long length survey (1190m in 2DS1) or small length survey (590 in 2DS2) are different depending on these parameters. Therefore, it will describe the effect of these parameters for each array. • Dipole-Dipole array Figures (4-36), (4-39), (4-42), and (4-43) show the inverse models of Dipole-Dipole array. It is noted when taking measurements with total length of (1190m), the maximum survey length of this array is (720m). This property effects on DOI and occurs due to fix the a-spacing between (1-9a), and n-factor between (1-6n). Therefore, to reach the maximum survey, (1190m), it needs to enlarge n-factor, for example (n-factor = 1-12n), and gets more DOI. This means that with large n-factor set, all possible measurements can be done. In small length survey, the n-factor is set between (1-6n) and a-spacing between (1-8a). Therefore, the full maximum survey length (590m), and all possible measurements are done by this array for small survey. However if more DOI is the target, larger a-spacing and n-factor can be used. Although it has large horizontal and vertical coverage data, the Dipole-Dipole array has more contamination with noise than Wenner-Schlumberger, Schlumberger reciprocal, and Wenner arrays. In this case, the increasing n-factor and/or a-spacing can be increased the noise contamination and may be


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not given any reasonable results. Furthermore, in comparison with the other arrays, the resolution of its inverse models decreases rapidly with depth especially after depth between (30-40m). Therefore, it is preferable to use for horizontal change in resistivity and shallow investigation, because it has high lateral resolution. • Wenner-Schlumberger and Schlumberger reciprocal array The same parameters are used for Wenner-Schlumberger and Schlumberger reciprocal arrays for long (1190m) and small (590m) survey. Therefore, they show the same coverage data and nearly the same behavior in distributed the apparent resistivity measurements in their pseudosections. This property can be shown obviously in pseudosection in figure (4-40). Therefore, it supposes that the Wenner reciprocal measurements must be included when collected data with Schlumberger reciprocal (Observed note). However, the maximum length reached by them for long survey is (1170m). Therefore, to achieve the total survey length equal to (1190m), larger n-factor and/or a-spacing must be used according to table (3-2). In small length survey, they are reached to total survey length (590m) and all possible measurements are done by these arrays for small survey. As shown in figures (4-39), and (4-42), the inverse models of Schlumberger reciprocal array gives the more DOI than the Wenner-Schlumberger array. They give vertical resolution less than Wenner-Schlumberger, but give best resolution compared with Dipole-Dipole array. However, Wenner-Schlumberger gives the best resolution among the others, because it shows inverse models that completely conformable with the lithological section of BH5 and BH6, and it gives the best resolution with depth than others. • Wenner array The Wenner array characteristics in this survey by less data measurements, less noise contamination, and less DOI than the other arrays, (Figures 4-39, and 4-42). Like Wenner-Schlumberger and Schlumberger reciprocal arrays, the total


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survey line reached by Wenner array is (1170m) for (120) electrodes, while it is (570m) for (60) electrodes. Therefore, to achieve the maximum survey line of (1190m) or (590m) the number of electrodes must be increased. This phenomenon does not showed in the other arrays because; they depend on nfactor and/or a-spacing during taking measurements. In Wenner array, the aspacing is the only parameter controlled the measurements. Therefore, unlike other arrays, the a-spacing of Wenner ranges between (1a-39a) for long survey line (1190m) and between (1a-19a) for small survey line (590m). This approach means that Wenner array levels will be (39) and (19) respectively, which are less than those that occurred in other arrays, (Appendix 2, and 3). The vertical resolution of Wenner array is decreasing with increasing depth. So, it resolution is less than Wenner-Schlumberger, and Schlumberger reciprocal for long survey line, and it is better than Schlumberger reciprocal in shallow depth (small survey line). In general, its resolution more better than Dipole-Dipole array

4.6 comparison between electrode arrays a) Dipole-Dipole array has more vertical and horizontal coverage. But, it is incapable to determine the underlying layers and aquifers due to effect of NSI and lateral inhomogeneity more than other electrodes array. This inhomogeneity appears in the all measurements of this array. Furthermore, its resolution decreases with increasing depth and/or increasing inhomogeneity. Therefore, it is preferable to use for horizontal change in resistivity and shallow investigations. b) Wenner array is less affected by bad data, but its ability to delineate layers and aquifers decreases with increasing the length of array (increasing DOI) due to decrease the vertical resolution with depth. However, this approach depends on the spacing between electrodes and the length of array. Therefore, with small survey line and low noise level, it gives significant results in delineating aquifers. This approach can be applied on the other arrays.


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c) The Wenner-Schlumberger and Schlumberger reciprocal arrays have the same vertical and horizontal coverage data, but Schlumberger reciprocal array is more sensitive to the noise ratio. d) In general, DOI obtained from Schlumberger reciprocal array is more than those obtained from the other arrays did. e) Schlumberger reciprocal array gives significant results in delineating layers and aquifers than Dipole-Dipole, and Wenner arrays for long survey, but its resolution still less than the Wenner-Schlumberger array. f) Wenner-Schlumberger array gives the best results than the other arrays for the manual and automatic filter. It produces inverse models that are completely coinciding with the lithological section of BH5 and BH6. Therefore, it succeeds in delineating the underlying layers, and it is the best in determine the aquifers, especially in areas with high inhomogeneity. g) If the distance between the electrodes of any array are increased and these electrodes are moved for each measured; the effect of NSI and lateral inhomogeneity will be decreased and vice versa. Therefore, the Dipole-Dipole array is highly affected by NSI and lateral inhomogeneity than the others, while Wenner array is the least one affected.

Chapter five/ Aquifer delineation

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Chapter five/ Aquifer delineation 5.1 Geoelectrical and geological sections Some notes must be mentioned before starting the explanation of geoelectrical and geological sections. 1. All VES points and 2D stations are carried out within alluvial fans (complex sedimentary deposits) area. So, the ratio of some deposits may increase on the account of others. For example, sand deposits used in the geological sections, according to the lithological wells section, means that the amount of sand deposits increase where other deposits decrease. 2. The interpretation results by IPI2Win software program (inverse modeling) are the closest to manual interpretation, Therefore these results are used to build up the geoelectrical sections using IPI-res3 (lite) program, (Bobachov et al. 2002). 3. Four lithological sections of wells (BH1, BH2, BH3, and BH4), are used as supporting data in constructing the geological sections from geoelectrical sections. 4. The low resistivity values are obtained by interpreting the data may be caused by increasing of salt water, or clay content. The range of resistivity values are between about (1-50Ωm), except 2DS1 where the resistivity values range between (1 Ωm) to more than (292 Ωm).

5.1.1 Geoelectrical and geological section along profile (A-A`) Six electrical zones are seen on the geoelectrical section along (A-A`) profile, (Figure 5-1). They are used to convert the geoelectrical section to geological section, (Figure 5-2). The geoelectrical section is supported by the lithological sections of two wells (BH1 and BH2), which are located near or within the (A-A`) profile (near VES-4 and VES-6 respectively).

124 Chapter five/ Aquifer delineation

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Zone (1) has resistivity ranges of (4.1 Ω.m) under VES-5 to (23.4Ω.m) under VES-1, and it represents a thin soil layer. The decreasing of resistivity values to (4.1 Ω.m) may be caused by increasing of secondary gypsum within this layer. The thickness of this zone varies between (0.74-1.32m). The resistivity values of zone (2) range between (1.9-4.79 Ω.m) under VES-5 and VSE-6 respectively. This zone reflects the presence of clay layer deposits according to the lithological section of BH2. However, the thickness of this zone is about (30m) under VES-6, and decreases towards VES-5.The clay layer may be extended toward of the other VES points, but it is not shown here because, it become very thin in comparison with the scale used in build up the geoelectrical and geological sections. According to BH2, the water table is within this zone at depth (8m) underground surface. However, it may be raised from underlying layer by hydrostatic pressure. Zone (3) shows resistivity values with range of (22.1 Ω.m) under VES-2 to (10.96 Ω.m) under VES-4. According to BH1, the sand layer deposits in this zone, with thickness of about (21m), decreases towards VES-1, and VES-4. The decreasing of resistivity values under VES-2 and VES-3, within this zone reflects of presence of water table coinciding with BH1 (about 5m). Zone (4) shows resistivity values ranging between (7.93 Ω.m) under VES-5 to (2.85 Ω.m) under VES-1. The variations of resistivity values are caused by water table level. This zone consists of silt layer deposits according to BH1. The thickness of this zone varies between (15-73m). In zone (5) the resistivity values range between (9.5Ω.m) under VES-5 and (10.8Ω.m) under VES-4. This zone reflects the presence of sand deposits as shown in BH1 lithology. The thickness of this zone reaches to about (40m) under VES-4 and VES-5 respectively, and decreases toward VES-3 and VES-6.


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Zone (6) shows resistivity values ranging between (5.51-12.7Ω.m) under VES-4 and VES-2 respectively. The deposits of this zone are similar to zone (4). They presence of silt layer deposits but the ratio of silt deposits is decreased in front of clay deposits from VES-6 and VES-1 to VES-4, it thickness varies between (100m) to (310m). The zones (3), (4), (5,) and the upper part of zone (6) represent the Quaternary aquifer, which consists of sand and silt deposits. The thickness of this aquifer ranges between (30-250m). It occurs at depth range between (10-30m). Zone (7) occurs under the lower boundary of zone (6). it resistivity values are between (0.98-4.2 Ω.m). These values are conformable with resistivity values of zone (2). Therefore, they may be referred to presence of clay layer deposits, but with unknown lower boundary and thickness.

5.1.2 Geoelectrical and geological section along profile (B-B`) The geoelectrical section along (B-B`) profile consists of six zones as shown in figure (5-3). This section is supported by lithological sequence of two wells, (BH3 and BH4) located near or within the (B-B`) profile (near VES-8, and VES11). Therefore, the geological section can be drawn as in figure (5-4). Zone (1) represents variation in resistivity values between (6.094-14.3Ω.m) under VES-7 and VES-8 respectively with thickness ranges between (0.83-2m). This zone reflects the top soil layer. Zone (2) represents the presence of clay layer deposits, as shown in BH3, where the resistivity values ranging between (2.47-3.18Ω.m) under VES-10 and VES-11 respectively. The thickness of this zone varies between (2.5-12m), and decreases rapidly towards VES-10, depending on the lithology of BH3 and BH4, and this layer disappear toward VES-8. This may be proofed that the clay deposits extend as lenses in the study area and/or in the whole Badra area.


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Zone (3) appears resistivity range between (6.83-28.06Ω.m) under VES-8 and VES-7 respectively. The lithology of the BH3 shows the presence of silt layer deposits. The thickness of this layer decreases rapidly toward VES-9. This zone shows decreases in resistivity values under VES-8 from (19Ω.m) to (6.83Ω.m). It may be caused by increasing of clay content in this position. Furthermore, the presence of water table in this zone and the previous zone is caused the decreasing in resistivity values. Zone (4) shows resistivity values range of (16.7 Ω.m) under VES-9 to (5.9 Ω.m) under VES-10. According to lithological section of BH3 and BH4, This zone reflects the presence of sand and/or gravel layer deposits, where its thickness is between (30-70m), decreasing toward VES-10 and VES-11 and VES-8. The decreasing in resistivity value under VES-9 to (11.02 Ω.m) is caused by presence of water table. Zone (5) appears resistivity values between (7.55-10.68 Ω.m) under VES-10 and VES-7 respectively. This zone and zone (3) represent same layer (silt deposits). The thickness of this layer is between (60-160m) The zones (3), (4), and (5) represent the Quaternary aquifer, which consist of sand (or gravel) and silt deposits. This aquifer has thickness ranges between (90200m) and occurs at depth (10m). Zone (6) shows low resistivity values, which are ranged between (3.272-4.21Ω.m) under VES-11 and VES-10 respectivity. This zone occurs under zone (5). The low resistivity values may be reflected the presence of clay layer deposits. The zone thickness is between (370-389m). Under zone (5), the resistivity values range between (3.85 Ω.m) under VES-8 to (4.39 Ω.m) under VES-7. It may be reflected the presence of clay layer deposits, but it is difficult to recognize its lower contact. Therefore, it is considered as unknown zone thickness under VES-7, VES-8, and VES-9.


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Zone (7), which occurs under the lower contact of zone (6), shows increasing the resistivity values in comparison with that of the upper zone. It may be caused by presence of clastics deposits of AL-Mukdadiya (Lower Bakhtiari) Formation. Finally, as shown in the lithological sections, the aquifer in the study area shows change in the type of deposits from (SE) to (NW) direction. The Quaternary aquifer in the study area consists of sand and/or gravel and silt layers. However, the size of deposits shows decreasing in the middle of the geological sections and with the depth. There is a sign in the geological section along (B-B`) profile to the presence of AL-Mukdadiya Formation. Nevertheless, there is no proof on that, such as deep well.

5.2 Inverse models of 2D imaging stations 2D imaging technique depends on a lot of measurements, which are systematically collected using multi-electrode system. However, six 2D imaging stations are carried out using Wenner-Schlumberger array. The total length of each station is (1200m), except (2DS2) where the total length is (600m). The electrode spacing is (10m). All the 2D stations are taken near wells to make a comparison with VES points and the lithological section of these wells. The RES2DINV program version (3.57.37) is used to create inverse model from measured data of the 2D stations, (Geotomo software, 2008). Automatic filtering is used for 2DS1, 2DS3, and 2DS4 due to high bad data in there measurements, while manual filtering is used for 2DS2, 2DS5, and 2DS6 due to good quality data.


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5.2.1 Station one (2DS1) The inverse model of Wenner-Schlumberger array shows five major horizons, reflecting the presence of five lithological layers according to BH5 section, (Figure 5-5). The first horizon reflects the presence of sand deposits with secondary gypsum. The thickness of this horizon ranges between (15-35m) and its resistivity values range between (5.06-11.4Ω.m). Under electrodes number (5-83) and (98-115), a thin resistive layer appears near the subsurface. Its resistivity values range between (57.7 Ω.m) to more than (292 Ω.m), and it thickness is less than (10m). This thin layer may be reflected dry sand deposits that occur above water table. The second horizon represents the presence of gravel deposits. Its resistivity values range between (15 Ω.m) to more than (292 Ω.m), and it thickness ranges between (10-30m). However, it occurs at depth between (15-35m). As shown in figure (3-6), the first and second horizons may be presented the deposits of valley fill deposits, which consist of gravel and sand deposits. The third horizon shows presence of gravel, and sand, interbedded with clay deposits, which characteristic by low resistivity values compared with that of other horizons due to presence of clay content. It resistivity values range between (1-11.4 Ω.m), while it thickness is between (40-80m) that occurs at depth between (50-70m).


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The fourth horizon shows the presence of gravel and silt deposits. It resistivity values range between (15-55 Ω.m). The horizon thickness is between (30-40m), and occurs at depth (80-90m). The above four horizons represent the Quaternary deposits, which considers as Quaternary aquifer. It may be separated into upper and lower Quaternary aquifer. The fifth horizon presents increasing in resistivity values ranging between (57.7-292 Ω.m). This horizon reflects the presence of pebbly sand stone of ALMukdadiya Fn., as shown in BH5. This horizon occurs at depth about (140m) with thickness is more than (80m). The presence of salt water, (TDS about 9600 ppm), within this horizon may be caused decreasing in its resistivity values from real situation This horizon can be considered as a part of AL- Mukdadiya aquifer.

5.2.2 Station two (2DS2) The total length of this station is (600m). The Wenner-Schlumberger inverse model shows the presence of five horizons according to the lithological section of BH6, (Figure 5-6). The first horizon reflects the presence of tope soil deposits, which are clay and/or sand with secondary gypsum. It resistivity values range between (4.61-9.55Ω.m), and thickness ranges between (1-5m). However, the thickness of this horizon increases in the ends of the inverse model. The second horizon shows the presence of gravel and sand with little clay deposits. The resistivity of this horizon ranges between (15 Ω.m), to more than (40 Ω.m). It occurs at depth between (1-5m), and has thickness between (1220m). The third horizon shows increasing of clay content with gravel deposits, which is caused, beside of the presence of salt groundwater, decreasing the resistivity values of this horizon. The resistivity of this horizon ranges between (3.21-7 Ω.m), and it thickness varies between (20-32m).


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It occurs at depth of about (13-25m). However, under electrodes number (40-43), the resistivity increases to about (9.55 Ω.m). It indicates a decrease of clay content under these electrodes. The fourth horizon shows the presence of gravel deposits with thickness range of (35-55m), and occurs at depth between about (45-50). The resistivity of this horizon ranges between (9.55-19.8 Ω.m). This horizon may consider as the Quaternary aquifer, which occurs within Quaternary deposits, under this station. The fifth horizon presents decreasing in resistivity values from about (7 Ω.m) to less than (3.21 Ω.m). Its lithology may be the same as that of the third horizon. It occurs at depth between (80-100m), with unknown thickness. All above horizons occur within Quaternary deposits.

5.2.3 Station three (2DS3) This station is made near VES-11. The measurements show good quality, as shown in measured and calculated apparent resistivity, where the RMS of the inverse model is equal to (7.8%), (Figure 5-7, and Appendix 9). The inverse model shows four horizons that belong to the Quaternary deposits, (Figure 5-7). The first horizon appears along the whole of the inverse model. This horizon is characterized by presence of sand deposits, as shown in BH4 near electrode number (49), with many lenses of clay distributed within this horizon.


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The clay deposits in BH4 appear as a lens within sand deposits in the inverse model. The thickness of clay lenses in the inverse model varies between (25m) as maximum and (2m) as minimum and resistivity values between (less than 3-5 Ω.m), while the sand deposits thickness reaches to about (20-50m) with resistivity ranges between (5-10 Ω.m). This range of resistivity values, which is less than the underlying horizon, are caused by many reasons, such as presence of groundwater, increasing in clay content and presence of secondary gypsum. The second horizon is characterized by the presence of silt deposits as shown in BH4. The resistivity values of this horizon exceed (12 Ω.m). This horizon occurs at depth between (20m) under electrodes number (86 to 90) to (45m) under electrodes number (48 to 64), and thickness reaches to (50m). The first and second horizon can be considered as upper Quaternary aquifer The third horizon represents decrease in resistivity values horizontally toward (NW) and (SE). This horizon represents impermeable layer (such as clay deposits). The resistivity values of this horizon range between (0.298-5 Ω.m). This horizon occurs at depth between (80-110m) and its thickness is about (80100m). The fourth horizon may be represented a lower Quaternary aquifer, and is not seen in the geological section along profile (B-B`). However, this horizon


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appears also in 2DS4 and will be discussed there. This horizon may be made of silt deposits. The interpretation of VES-11, which is located near electrode number (41), shows approximately coinciding with resistivity values of 2D inverse model especially to depth (90m), (Table 4-2). Beyond this depth, the VES-11 shows very thick horizon with resistivity of (3.272 Ω.m) and thickness of (356.5), while the 2D inverse model shows horizon with approximately same resistivity but with thickness of (100m). This difference is accepted because, in 1D technique, the resistivity value of horizons is calculated from average of resistivity values. However, VES-11 may give a sign of the presence of ALMukdadiya deposits, which are not shown in 2DS3, because it has more depth investigation than that of the 2D technique

5.2.4 Station four (2DS4) This station is measured near VES-6. The difference between measured and calculated pseudosections shows RMS error equal to (15%), (Figure 5-8, and Appendix 9). The inverse model represents three horizons. The first horizon extends along the inverse model with resistivity values range between (0.496-4.83Ω.m). As shown in BH2 near electrode number (90), this horizon consists of clay deposits with thickness reaches to (40m). The top soil deposits do not appear due to large scale used. In some positions (such as under electrodes number (4-38)), the resistivity values increase between (6 Ω.m) to more than (26 Ω.m). It may be referred to presence of sand or silt deposits. The second horizon represents silt deposits, as shown in BH2, and it extends along the inverse model. The depth of this horizon reaches to (40), and it thickness ranges between (50m) to more than (180m).


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It resistivity values ranging between (6 Ω.m) to more than (26 Ω.m). This horizon is not shown in the geological section along profile (A-A`). This means that the 2D imaging technique is better than that of the 1D resistivity technique in delineating the aquifers and in determining the changes in resistivity within the layers and the aquifers. This horizon can be considered as Quaternary aquifer. One note must be mentioned here, that the thickness of this aquifer increases rapidly between electrodes number (55-61). Such case showed in (2DS3), but the aquifer was separated to upper and lower Quaternary aquifer, (Figure 5-7). In 2DS4 inverse model, the aquifer remains without separation, although its extend decreases by the fourth horizon intrusion. However, this case is not shown in the inverse model of (2DS5) and (2DS6). The third horizon shows low resistivity values compared with that of the upper horizon. It consists of two parts, one between electrodes number (18-55) and another between electrodes number (61-92). Its resistivity values range between (0.496-4.83Ω.m), which are coinciding with the first horizon. This horizon may be represented the presence of impermeable layer (clay deposits). This horizon occurs at depth of (90-100m) with unknown thickness. The interpretation results of VES-6 show agreement with inverse model of (2DS4), although the first and second horizons of VES-6 do not appear in the


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model section. However, the VES-6 gives more investigation depth than that of the 2D imaging, although in 1D resistivity technique, the DOI becomes uncontrolled and it is difficult to determine when the distance between electrodes increases, while in 2D imaging technique the DOI is controlled by huge data measurements obtained by this technique.

5.2.5 Station five (2DS5) This station is carried out toward (NW-SE). The VES-10 occurs near electrode (64) of (2DS5). The quality of data is good as shown in measured and calculated apparent resistivity pseudosection, where the RMS of the inverse model is (6.6%), (Figure 5-9, and Appendix 9).The inverse model shows presence of five horizons, (Figure 5-9). The first horizon appears near ground surface and distributed along the inverse model with resistivity values range between (2.11-3.41Ω.m). This horizon affects by irrigation water. It represents a thin sand layer. It thickness reaches as maximum to (10m). The second horizon shows a thin layer extends along the model section, but it is separated under electrodes number (32-37). The resistivity of this horizon ranges between (6 Ω.m) to more than (11.4 Ω.m). This horizon occurs at depth reaching to (10m) and it thickness is between (15-25m). This horizon reflects the presence of sand deposits. The first and second horizons may be represented the occurrences of the same layer. The third horizon shows low resistivity values, which are between (2.68-5Ω.m).This horizon may be represented the presence of clay lenses. Like these lenses is appeared in 2DS2 inverse model. The depth of this horizon is about (20m) and it thickness is between (15-12m). The fourth horizon distributes along model section. Its resistivity values range between (6Ω.m) to more than (11.4Ω.m).


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This horizon represents the Quaternary aquifer. It reflects the presence of silt and/or sand deposits. This horizon has variable thicknesses, which range between (50-90m) at depth varies between (35-50m). The fifth horizon shows the presence of impermeable layer (may be clay). It resistivity values range between (2.4-5.52Ω.m). This horizon occurs at depth between (100-120m). It thickness is more than (120m). The interpretation results of VES-10, (Table 4-2), show coinciding with the 2DS5 inverse model. However, the third horizon in the inverse model does not appear in the interpretation results of VES-10. This indicates that the 2D imaging technique is more accurate and it is better in recognizing more layers or aquifers than that of the 1D. It gives a detail picture on the subsurface ground than that of the 1D resistivity technique.

5.2.6 Station six (2DS6) This station is conducted near VES-5, where electrode number (64) is located near VES-5. The difference between measured and calculated apparent resistivity pseudosection shows very good quality data. The RMS value of the inverse model is (3.8%), (Figure 5-10, and Appendix 9). However, the inverse model shows three major horizons, (Figure 5-10).


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The first horizon shows large variation in resistivity values ranging between (3.42-8.5Ω.m) with thickness ranges between (50-65m).This horizon can be divided into two sub horizons. The first sub horizon has resistivity range between (7-8.5Ω.m). It appears as lenses within the major horizon. These lenses consist of sand and/or silt and their thickness range between (5-30m) at depth reaches to (15m). Second sub horizon is the bigger and has more thickness than the first sub horizon.

It resistivity values range between (3.42-6.0Ω.m).The decrease of

resistivity values may be caused by increase the ratio of clay content within this sub horizon, where the high clay ratio concentration can be shown as lenses form in the inverse model. The thickness of this sub horizon exceeds (50m). The second horizon represents the presence of the Quaternary aquifer, which characteristics by resistivity values ranging between (7Ω.m) to more than (10Ω.m) with thickness between (70-90m). This horizon consists of silt and /or sand deposits. It occurs at depth between (40-65m). The third horizon shows decrease in resistivity values with depth increase. The resistivity values decrease from (6.63Ω.m) to less than (3.42Ω.m). However, it is mean that the ratio of clastic deposits decrease in front of increase


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of clay content to form an impermeable layer (clay deposits). It thickness is more than (90m) and presences at depth about (140). The interpretation results of VES-5 are not shown accurate results. It shows thick horizon, about (200m) with resistivity equal to (7 Ωm), occurs at depth about (76m), (Table 4-2), while the 2DS6 inverse model shows that there are two thick horizons. One occurs at depth (50-65m) with thickness between (7090m). Another with thickness is more than (90m) and occurs at depth about (140m). The cause of such case in 1D resistivity technique is the presence of gradual decreases in resistivity values with depth, while in 2D imaging technique, because of a huge data can be obtained by this way, it gives an accurate picture to subsurface and it is better delineating the changes in resistivity with these layers.

5.3 Aquifer delineating The results obtained from the geological section and 2D imaging stations show the presence of two aquifer types. The Quaternary aquifer, which appears in all the geological sections and 2D imaging stations. This aquifer can be divided into upper and lower aquifer as shown in (2DS1), (2DS3), and (2DS4). In general, the thickness of this aquifer ranges between (30-200 m) which occurs at depth (10-30m) according to geological sections, while it thickness varies between (35-180m) and occurs at depth (10-45m) according to 2D imaging stations. AL-Mukdadiya aquifer, which appears in 2DS1 only at depth (140m), and thickness exceeding (80m).

5.4 Comparison between 1D, and 2D imaging technique 1. 1D resistivity technique gives a general view about the geological setting of subsurface horizons, while 2D imaging technique gives a detailed view of the


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subsurface geology. Because, the 2D imaging technique is requires a huge amount of measurements, therefore, it gives an accurate picture of lateral variation in lithology. 2. 1D resistivity technique succeeds in delineating the boundaries between layers. But, 2D imaging technique is better in delineating the aquifers and in determining the changes in resistivity within layers and aquifers and it succeeds in recognizing the upper and lower aquifers as shown in (2DS1), (2DS3), and (2DS4). Therefore, it is better in recognizing more layers or aquifers than does of the 1D resistivity technique. 3. 1D resistivity technique can give long geological section in comparison with 2D imaging technique using many VES points. 4. 1D resistivity technique shows high DOI in comparison with 2D imaging technique. But, in 1D resistivity technique the DOI becomes uncontrolled and it is difficult to determine when the distance between electrodes should increase, while in 2D imaging technique the DOI is controlled by huge data measurements obtained in this technique. 5. 2D imaging technique succeeds in recognizing layers (or aquifers), while 1D resistivity fails in recognizing them, as shown in 2DS4, and 2DS3 in comparison with the geological section along profiles (A-A`), and (B-B`). 6. 1D resistivity technique fails in detecting the boundary between layers, which have gradual decreases (or increases) in resistivity values, or layers with small thickness, while 2D imaging technique succeeds in delineating these layers. This is shown in 2DS4, and 2DS3 in comparison with the geological section along profiles (A-A`), and (B-B`).

Chapter six / Conclusions and Recommendations

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Chapter six/ Conclusions and Recommendations 6.1 Conclusions 1. The qualitative interpretation of field curves gives five to seven horizons, which reflect the variation in the lithology of the study area for both vertical and horizontal directions. The apparent resistivity sections are obviously shown decrease in apparent resistivity values with depth, and they give a primary image about the distribution of deposits. 2. The cross VES (VES-12 VES-12`) point shows high distortions in their field curves, and reflecting high background noise level, due to the effect of lateral inhomogeneity which concedes with the result of 2DS1. On the other hand, cross VES (VES-13, and VES-13`) point reflects very good quality data which reflect low background noise level (inhomogeneity), and this result concedes with the results of 2DS2. 3. The automatic filtering may give significant results for inverse models, because it is better in removing bad data quality. Also, automatic filtering is easy and takes several seconds in removing bad data. While the manual filtering is difficult, uncontrolled, and takes a lot of time especially with the increase of bad data. 4. It is noted that taking measurements by Dipole-Dipole, Wenner-Schlumberger and Schlumberger reciprocal array with survey line equal to (1190m), the maximum survey length of these arrays is (730m) for Dipole-Dipole array and (1170m) for Wenner-Schlumberger and Schlumberger reciprocal arrays. Therefore, to achieve the total survey length survey equal to (1190m), larger n-factor and/or a-spacing must be used according to table (3-2). In survey line of (590m) total survey length may reach (590m) and all possible measurements are done by these arrays for small survey. However, if more DOI is the target, larger a-spacing and n-factor should be used.


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5. Wenner-Schlumberger and Schlumberger reciprocal arrays for long survey line (1190m) and small (590m) survey show the same coverage data and same behavior in the distribution of the apparent resistivity measurements in their pseudosections. 6. The total survey line reached by Wenner array is (1170m) for (120) electrodes, and (570m) for (60) electrodes. Therefore, to achieve the maximum survey line of (1190m) or (590m) the number of electrodes must be increased. This phenomenon is not observed in the other arrays. Because in Wenner array, the a-spacing is the only parameter controlling the measurements. Therefore, unlike other arrays, the a-spacing of Wenner ranges between (1a-39a) for long survey line (120) and between (1a-19a) for small survey line. 7. Dipole-Dipole array is highly affected by NSI and lateral inhomogeneity than others arrays, while the Wenner array is the lesser one. Therefore, the measured data using Wenner array is the best, and it becomes less quality for Wenner-Schlumberger and Schlumberger reciprocal, for Dipole-Dipole array is bad. 8. Dipole-Dipole array has the biggest vertical and horizontal coverage. But, it is incapable to determine underlying layers due to the increasing effects of NSI and lateral inhomogeneity as compared with other electrodes array, and its vertical resolution is decreased with increasing depth and/or increasing noise contamination. Therefore, it is preferable to use for horizontal change in resistivity and shallow investigations, because it has high lateral resolution. 9. The ability of Wenner array in delineating aquifers decreases with increasing the length of array (investigation depth). This means that the vertical resolution decreases with increasing of the investigation depth. 10. Schlumberger reciprocal array shows significant results in delineating aquifer, as compared with Dipole-Dipole, and Wenner arrays for long survey, but its


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resolution is still less than Wenner-Schlumberger array. Furthermore, it gives DOI more than those obtained from the other arrays. 11. Wenner-Schlumberger array shows the best results in delineating aquifer and the best resolution than the other arrays. So, it is typical to determine the aquifers especially in areas with high background noise. 12. When the distance between the electrodes for any array is increased and these electrodes are moved for every measurement, the effect of NSI and lateral inhomogeneity will decrease and vice versa. Therefore, Dipole-Dipole array is highly affected by NSI and lateral inhomogeneity than that of the others, while Wenner array is less affected. 13. Two aquifer types are recognized, these are: The Quaternary aquifer is appeared in all the geological sections and 2D imaging stations, and it can be divided into upper and lower aquifers as shown in (2DS1), (2DS3), and (2DS4). In general, the thickness of this aquifer ranges between (30-200 m), which occurs at depth (10-30) according to geological sections, while it occurs at depth between (10-45m), and has thickness varying between (35-180m) according to 2D imaging stations. AL-Mukdadiya aquifer appears only in 2DS1 at depth nearly equal to (140m), and thickness exceeds (80m). 14. 1D resistivity technique gives a general lateral view about geological setting of subsurface layers, while 2D imaging technique gives a detailed lateral view about subsurface geology. 15. 1D resistivity technique is good in delineating the boundaries between layers. But, 2D imaging technique is better in delineating the aquifers and in determining the changes in resistivity within layers and aquifers and it is good in recognizing the upper and lower aquifers as shown in (2DS1), (2DS3), and (2DS4). Therefore, it is better in recognizing more layers or aquifers than does the 1D resistivity technique.


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16. 1D resistivity technique shows high DOI in comparison with 2D imaging technique. However, in 1D resistivity technique, the DOI becomes uncontrolled and it is difficult to determine when the distance between electrodes increase, while in 2D imaging technique the DOI is controlled due to huge data measurements of this technique. 17. 1D resistivity technique fails in detecting the boundary between layers, which shows gradual decreases (or increases) in resistivity values, or layers with small thickness, while 2D imaging technique succeeds in delineating these layers. This is shown in 2DS4, and 2DS3 in comparison with the geological section along profiles (A-A`), and (B-B`).

17.2 Recommendations It is recommended to: 1. Make more studies to compare different arrays using 2D imaging technique in delineating different features such as faults, cavities or aquifers in different geological conditions. 2. Use Wenner-Schlumberger array in delineating aquifers (or layers), especially in areas with high inhomogeneity, and/or long line survey. 3. Use the Schlumberger reciprocal, and Wenner arrays in delineating aquifers (or layers) in areas with low inhomogeneity, and short line survey. 4. Make deep resistivity survey or drill deep wells in the study area to determine the depth and thickness of AL- Mukdadiya aquifer.

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Appendices

APPENDIX (1) VES field curves

I

Appendices

II

Appendices

III

Appendices

IV

V

Appendices

APPENDIX (2) shows the anisotropic factor for each C1C2/2 spacing for (VES (12) and (12`)), and (VES (13) and (13`))

Table (1) show the anisotropic factor for each AB/2 spacing for VES (12) and (12`)

Table (2) show the anisotropic factor for each AB/2 spacing for VES (13) and (13`) AB/2

λ

1.5

1.33

2

1.46

3

1.51

4

1.40

1.12

5

1.29

5

1.14

6

1.23

6

1.04

8

1.22

8

1.05

10

1

15

1

10

1.07

20

1.04

15

1.1

25

1.04

20

1.07

30

1.03

40

1.07

50

1.11

60

1,13

80

1.06

100

1.05

120

1.09

140

1.14

160

1.1

200

1.09

250

1.05

300

1.20

AB/2

λ

1.5

1.09

2

1

3

1.07

4

Appendices

VI

APPENDIX (3) The quality data along profiles of Wenner-Schlumberger, and Schlumberger reciprocal arrays for 2DS2 before filtering

2DS2/ Wenner-Schlumberger array

VII Appendices

2DS2/ Schlumberger reciprocal array

Appendices

VIII

APPENDIX (4) The quality data along profiles of Dipole-Dipole, WennerSchlumberger, Schlumberger reciprocal, and Wenner array for 2DS1 after manual filtering

Gravel + clay

Dipole-Dipole array

IX Appendices

Gravel + clay

Wenner-Schlumberger array

X Appendices

Schlumberger reciprocal array

XI Appendices

Wenner profiles

Appendices

APPENDIX (5)

XII

The measured and calculated pseudosection and invers model sections of Dipole-Dipole, Schlumberger reciprocal, and Wenner array for 2DS1 after manual filtering

Appendices

XIII

Appendices

XIV

Appendices

XV

APPENDIX(6) The quality data along profiles of Dipole-Dipole, Wenner-Schlumberger, Schlumberger reciprocal, and Wenner array for 2DS1 after automatic filtering

Dipole-Dipole array

XVI Appendices

Wenner-Schlumberger array

XVII Appendices

Schlumberger reciprocal array

Appendices

XVIII

Wenner array

Appendices

APPENDIX (7)

XIX

The measured and calculated pseudosection and invers model section of Dipole-Dipole, Schlumberger reciprocal, and Wenner array in 2DS1 after automatic filtering

Appendices

XX

Appendices

XXI

XXII

Appendices

APPENDIX (8)

The measured and calculated pseudosection and invers model section of Dipole-Dipole, Schlumberger reciprocal, and Wenner array for 2DS2 after manual filtering

00

00

160

160

160

320

320

480

480

320

00 480

XXIII Appendices

00

00

00

160

160

160

320

320

320

480

480

480

XXIV Appendices

00

00

00

160

160

160

320

320

320

480

480

480

Appendices

XXV

APPENDIX (9)

The measured and calculated pseudosection and invers model section of Wenner-Schlumberger array for 2DS3, 2DS4, 2DS5, and 2DS6

Wenner-Schlumberger array/2DS3

XXVI Appendices


XXVII Appendices


XXVIII Appendices


aquifers 1D resistivity technique

2D imaging technique 2D imaging technique

2D imaging stations Dipole-Dipole (Schlumberger reciprocal) 2DS1

2DS2 2DS1 Wenner-Schlumberger Wenner 2DS2 Cross vertical electrical sounding high background noise level

Schlumberger

VES

2DS2 lateral inhomogeneity

2DS1 near surface inhomogeneity inverse model . 2DS2 2DS1

depth of investigation

good quality Ebert method

(IPI2Win software) (geoelectrical sections) (gravel)

(sand)

geological sections (clay) (silt)

quaternary aquifer (upper and lower aquifer) 2DS4

2DS3

2DS1

AL-Mukdadiya aquifer 2DS1

2DS4

2DS3

2DS1

1434

2013