Bathymetry and seafloor mapping via one dimensional inversion and ...

Exploration Geophysics (2000) 31, 603-610

Bathymetry and seafloor mapping via one dimensional inversion and conductivity depth imaging of AEM Julian Vrbancich1 Peter K. Fullagar2 James Macnae3 Key Words: bathymetry, airborne, electromagnetic, inversion, conductivity-depth-imaging, EM FLOW, seafloor

ABSTRACT

INTRODUCTION

This study examines the application of airborne electromagnetic (AEM) methodologies to bathymetry in shallow seawater and to map seafloor conductivity. Conductivity versus depth sections have been generated from a recent helicopter-borne DIGHEMV survey (operating vertical coaxial and horizontal coplanar transmitter-receiver coil geometries) of lower Port Jackson, Sydney Harbour. The sea depth ranges from about 1 to 30 m. Acoustic bathymetric soundings and marine seismic survey data provide the true seawater layer thickness and estimates of depth to bedrock respectively over most of the EM survey region. This complementary data can be used to evaluate the accuracy of airborne electromagnetic bathymetry. The efficacy of 1D conductivity inversion and rapid conductivity-depth imaging was investigated for shallow seawater overlaying marine sand sediments and sandstone. The inversion constructs layered conductivities which satisfy the AEM data to an accuracy consistent with the observational uncertainties. Inverted frequencies ranged from 328 to 55300 Hz. Resolution of the sea depth gave good agreement with known bathymetry (within about 10% or better) when inversion was unconstrained. Approximate conductivity-depth images obtained using program "EM Flow" gave similar agreement. Both inversion methods clearly identify the location and burial depth of higher resistivity regions associated with shallow marine sandstone bedrock. In addition to measuring water depths to about 30 m, this study has shown that the AEM DIGHEM technique provides a capability for remote sensing of seabed properties and offers the potential to detect areas of shallow bedrock and differentiate between consolidated and unconsolidated sediment in areas of seawater deeper than 25 m.

The application of AEM methods to shallow water bathymetry is currently under investigation by the Defence Science and Technology Organisation (DSTO) under the sponsorship of the Royal Australian Navy (Vrbancich et al., 2000). This communication describes work in progress on data from a recent airborne electromagnetic bathymetry (AEMB) survey. The survey was undertaken over the lower section of Port Jackson, Sydney Harbour, with a five-frequency DIGHEM heliborne system. The Sydney Harbour survey area was chosen because of its varying seafloor terrain. The area includes a rock reef, straddled by two shipping channels, and plane areas, relatively deep "holes" and an area of shallow pot-holes gouged into the sediment alongside the rock reef. Water depths vary from a few metres to about 32 m. Accurate ground truth data derived from conventional sonar bathymetry and marine seismic surveys are available to appraise the accuracy of the EM-based interpretation of the seawater depth (Vrbancich et al., 2000) and sediment thickness.

1

Julian Vrbancich Maritime Operations Division Defence Science and Technology Organisation (DSTO) P.O. Box 44, Pyrmont, NSW 2009, Australia Telephone: (02) 96921 486 Facsimile: (02) 96921 560 E-mail: [email protected]

2

Peter K. Fullagar Fullagar Geophysics Pty Ltd Level 1, 1 Swann Road, Taringa , QLD 4068, Australia Telephone: (07) 3377 6780 Facsimile: (07) 3377 6701 E-mail: [email protected]

3

James Macnae CRC for Australian Mineral Exploration Technologies (CRCAMET) Macquarie University, NSW, 2109, Australia Telephone: (02) 9850 9291 Facsimile: (02) 9850 8366 E-mail: [email protected]

Vrbancich et al. (2000) interpreted depths from the Port Jackson DIGHEM data, using Geoterrex-Dighem proprietary two layer inversion. The focus in this present paper is not only the depth of the seafloor, but also its physical characteristics. Accordingly, conductivity sections have been generated using both layered earth inversion (AEMI) and conductivity-depth imaging (EM Flow) in order to extract information about the nature and structure of the unconsolidated sediment and hard basement. Coastal bathymetry and seafloor mapping pose a challenging problem for AEM because of the high conductivity of seawater (typically 4 S/m) which masks the response from the more resistive sediment and underlying basement. The limit for bathymetric interpretation of AEM is about 70 m using commercial fixed wing time domain systems and about half this value for commercial frequency domain helicopter systems (Palacky, 1988; Palacky and West, 1991; Vrbancich et al., 2000)1. Despite the restricted depth range, AEM surveys can provide useful data over shallow seawater to map the conductivity and thickness of the water column and, possibly, characterise the underlying sediment and bedrock. The identification of unconsolidated porous sediment is difficult because of the weak conductivity contrast between it and seawater. Unlike many terrestrial applications, however, the marine geo-electric section can be assumed to be relatively simple and often one-dimensional. Moreover, the conductivity limits of the upper and basement layers (seawater and bedrock) are well constrained. Neglecting any localised variations in temperature and salinity, the conductivity normally decreases with depth, from seawater, through marine sand or mud, down to bedrock. These general features can be exploited to impose fairly tight conductivity bounds on seawater, sediment, and bedrock during inversion.

1

These AEMB depths do not necessarily represent ultimate technical limits.

Exploration Geophysics (2000) Vol 31, No. 4

603

Vrbancich et al.

Airborne bathymetry - inversion and CDI

Numerous seawater electrical conductivity soundings were taken at various locations within the survey region immediately prior to and after the DIGHEM survey. In depths greater than 10 m, the soundings revealed a warmer lower layer of increased salinity. Typically, in 18 m deep water, the top 10 m has a conductivity of 4.45 to 4.50 S/m, while the underlying warmer layer (about 0.5°C increment) has a conductivity of about 4.60 to 4.65 S/m. LAYERED EARTH INVERSION A modified version of a 1D inversion program developed for horizontal loop EM (Fullagar, 1981; Fullagar and Oldenburg, 1984) was applied to the Sydney Harbour DIGHEM data. The program was recently extended to invert vertical coaxial data as well as horizontal coplanar data, and to adjust layer depths as well as conductivities. Three inversion options are available: depth inversion with layer conductivities fixed; conductivity inversion with layer interfaces fixed; and depth inversion followed by conductivity inversion. The third option is the only one used in this study. Upper and lower conductivity bounds can be imposed on each layer during conductivity inversion.

Fig. 1. Flight paths for AEM survey over Port Jackson, Sydney Harbour. Lines L20010, L20020, lie on the western side, followed by L20030, …, L20210 (eastern side). The northeast section of the survey cuts across the harbour entrance. Depth to bedrock contours (Emerson and Phipps, 1969) are shown at 15 m intervals. The insert shows an enlarged area (scaled by a factor of 2) surrounding the Sow and Pigs reef. The headlands Bradleys Head, Chowder Head, Georges Head, Middle Head and North Head are marked as BH, CH, GH, MH and NH respectively.

EXPERIMENTAL METHOD The 115 line km DIGHEM survey was flown in June 1998 and covers a rectangle 1 km wide and 5.5 km long. The south-west edge lies between Bradleys Head and Shark Island, and flight lines extend north-east, sweep along the major shipping channel, cross the Sow and Pigs reef, and finish near North Head (see Figure 1). Twenty one profiles were flown at 50 m nominal line spacing. The helicopter borne DIGHEMV system used 3 horizontal coplanar (HCP) and 2 vertical coaxial (VCX) transmitter-receiver coil pairs operating at 328 Hz, 7337 Hz, 55300 Hz and 889 Hz, 5658 Hz respectively. Coil separations were all 8.1 m except for the 55300 Hz coils, for which the coil spacing was 6.3 m. Nominal bird height was 30 m.

604


The inversion is initiated with a starting model, consisting of layers on basement, defined by the user. During conductivity inversion, the layers can be split in half if the rate of convergence does not satisfy certain criteria. Layer splitting can occur more than once, until a specified maximum number of layers is attained. Basement conductivity, SIG1, does not vary during inversion. The SIG1 conductivity value is chosen to represent an arbitrary lower conductivity limit of the underlying basement half-space. (In this discussion, the non-aqueous layer(s) above the basement will be referred to as seabed or sediment layers.) Since depth inversion may result in a correction to the receiver altitude, the output depths are adjusted so that the sea surface is always at zero depth. The degree of correspondence between observed and calculated data is gauged by an L1-norm misfit, L1, defined by (Parker and McNutt, 1980),

where {on} are the observed data, {cn} are the calculated responses, and N is the total number of data involved in the inversion. The residuals are normalised with respect to the corresponding standard deviations, {εn}. For convenience, the nth standard deviation, εn, is defined as some percentage, PCERR, of the nth measurement, on, with the proviso that εn must not be smaller than a specified noise threshold, SDMIN. If the errors in the data are realisations of independent normal random variables, with mean zero, the expected value of L1 is unity. The program is deemed to have converged if L1 is less than 1. Failure to achieve convergence may simply mean that the assumed level of error is too small. Clearly, the quality of the data and the assumption of a layered sub-surface will govern the achievable degree of fit.

Vrbancich et al.


Inversion of synthetic data The operation of the 1D inversion program, AEMI, is illustrated on three synthetic examples (models). These are typical of shallow water bathymetric applications, but do not represent an exhaustive appraisal of the inversion program. Synthetic data were computed for each model as a ppm EM response for each of the five DIGHEM frequencies for a bird height of 32.77 m. The in-phase and quadrature components at all five frequencies were inverted in each case. The synthetic data were noise-free, but 1% or 2% error (or 1 ppm, whichever was larger) was assumed when judging L1 misfit, as per equation (1). Starting model parameters, conductivity bounds, and misfit errors are summarised in Table 1. Synthetic modelling shows that layer depths and conductivities are predicted with reasonable accuracy in shallow seawater less than 40 m deep. Figure 2a shows the result of inverting data from a 40 m thick 4 S/m seawater layer over a 0.1 S/m sediment layer, using a 20 m thick 2 S/m layer over a 30m thick 0.5 S/m sediment layer as the starting model. Inversion has recovered the correct seawater conductivity (4.0 S/m), and has increased the water depth to 30.6 m. (The third layer arises from the basement layer which had an arbitrary conductivity (SIG1) value set at 0.1 S/m, see Table 1.) DIGHEM does not have sufficient penetration to constrain basement conductivity in this case. This example illustrates the limits of penetration of DIGHEM. The effective penetration of the system is governed by the lowest frequency. At 328 Hz, the skin depth is 14 m in seawater (4 S/m) and the useful bathymetric range is typically about 2 skin depths. DIGHEM does not detect the seafloor beneath 40 m of 4 S/m seawater. For shallower seawater (10 m at 4 S/m) over 0.1 S/m seabed, the inverted conductivity constructed from a starting model with 15 m deep 3 S/m water, 15 m thick 0.5 S/m sediment, and a fixed 0.001 S/m (SIG1) basement is shown in Figure 2b. In this case a 2 m receiver altitude error, deliberately introduced by using a bird height of 34.77 m as an input parameter to the inversion program, was substantially corrected by the inversion program which inferred a bird height of 32.70 m. The convergence condition was more stringent than in the previous case, since 1% errors were assumed, c.f. 2% errors above. The conductivity of the seawater has been correctly determined (4.0 S/m) from the surface to 7 m depth. However, the model conductivity is 2.5 S/m between 7 and 14 m, straddling the actual seafloor at 10 m. This is a direct illustration of non-uniqueness, and highlights the importance of a priori constraints in order to better determine the conductivities and depths. In the third case, the true model comprises 10 m deep 4 S/m seawater over 10 m of 0.5 S/m sediment overlying 0.01 S/m basement (Figure 2c). The starting model consisted of 15 m of 4.5 S/m seawater, 10 m of 0.2 S/m sediment and 10 m of 0.05 S/m consolidated sediment on a 0.005 S/m basement. The starting model parameters are reasonable estimates for seawater and unconsolidated and consolidated sediments. The inversion predicts seawater to a depth of 9 m (using 4.0 and 4.4 S/m layers). The sediment layer conductivity has increased to 0.3 S/m, from a 0.2 S/m starting value, but remains underestimated. The sediment lies between 9 m and 25 m, overestimated in layer thickness. Accurately characterising a weakly contrasting sediment layer sandwiched between conductive seawater and resistive basement requires a priori information.

Fig. 2. Inverted conductivity for synthetic models. (a): deep seawater 40 m 4 S/m seawater layer over 0.1 S/m basement; (b): shallow seawater - 10 m 4 S/m seawater layer over 0.1 S/m basement with a 2 m altimeter error (34.77 bird height); (c): shallow seawater and sediment - 10 m 4 S/m seawater layer over 10 m 0.5 S/m sediment layer over 0.01 S/m basement.

CONDUCTIVITY-DEPTH IMAGING Stolz and Macnae (1998) and Macnae et al. (1998) describe a method by which arbitrary waveform data can be transformed into a form that is independent of the EM system. This key step allows

Table 1. Starting model parameters and misfit errors for layered earth inversiona.


605

Vrbancich et al.

fast processing and interpretation tools, as generic rather than system waveform-specific algorithms are implemented. There is a trade-off in the time taken to transform the data, a requirement that the transformation adequately and stably represents the original data, and in practice there are problems accurately defining the actual system waveform and transformation parameters.


CONDUCTIVITY SECTIONS

In the frequency domain the procedure involves fitting a linear sum of single-pole, single-zero responses (Grant and West, 1965) to the observed data. This is mathematically equivalent to fitting exponential decays in time domain. Following the fitting procedure, the time or frequency data are reduced to a set of amplitudes with associated time constants. The range of time constants (tau values) that can be resolved is determined by the DIGHEM EM system frequencies and the noise levels in the data. For this data we varied the tau range between about 0.5 µs and 0.01 s. Time constants much shorter or longer than these lie outside the range of sensitivity of the EM system, and are not well constrained by the data.

Three lines of DIGHEM data were processed using both the layered earth inversion (AEMI) and the CDI technique (EM Flow). The resulting conductivity sections are appraised with reference to independent information as follows. Water depth and sediment thickness are determined from conventional bathymetric and marine seismic surveys. Bathymetric soundings were obtained from the Sydney Ports Corporation and from DSTO multi-beam surveys (Vrbancich et al., 2000). The depth to bedrock contours (Figure 8, Emerson and Phipps, 1969; see Figure 1), were resampled at the flight fiducial coordinates2. The limited number of seismic traverses combined with navigational inaccuracies (±30 m), and resampling-gridding errors, could lead to inaccuracies in the interpolated depth to bedrock at the fiducial coordinates in some areas. The bathymetry profiles and depth to bedrock profiles show sediment thickness variations along the flight survey paths. These profiles have been included in the conductivity-depth section images. The depth datum is tide-corrected sea level.

There are a number of methods in the literature for the rapid derivation of conductivity-depth sections from EM data. One group of methods is based on the Maxwell receding image concept, where conductivity is derived from the step response using a predicted depth to an image of the source. This method has been described by Macnae and Lamontagne (1987) and by Nekut (1987).

The character of the seafloor is well known from previous geological studies. The harbour is a drowned river valley estuary eroded into Hawkesbury Sandstone (Roy 1984). The sediment type in the north-east half of the AEM survey area (Figure 1) consists of clean marine sand, while there is both mud and sand in the south-west (Roy 1983).

Given data in the tau domain, it is possible to predict the step response and derive a conductivity-depth-image (CDI) from AEM data by the method described in Macnae et al. (1991). In practice, it is not necessary to predict the step response because mathematically equivalent processing can be carried out directly in the tau domain. The rapid CDI process is encoded into the program EM Flow, (Macnae et al., 1998) developed at the Cooperative Research Centre for Australian Mineral Exploration Technologies (CRCAMET). The in-phase and quadrature EM response at all HCP and VCX frequencies were used in this analysis.

For the purpose of EM interpretation, it will be assumed that the conductivity of clean marine sand and muddy sand are equal, even though the porosity of the two sediment types differs. The geoelectric section is approximated as a 1D model consisting of seawater lying over marine sand deposited over marine sandstone. The sediment layer conductivity will vary laterally. Typical resistivities of the sediment and marine sandstone can be estimated from studies of formation factors and porosity (Kermabon et al., 1969; Jackson et al.,1978; Hutt and Berg, 1968; Schon, 1996), and from direct resistivity measurements using penetrometers in unconsolidated sands (Bennet et al., 1983). Typical conductivity ranges for marine sandstone, sands, and clays are given in Table 2.

Various parameters control the output of the CDI process used. The most critical of these is the choice of time constant (tau) range used in the transformation of frequency domain data to the tau domain. In this case, the earliest tau used was 0.3 µs, equivalent to the time taken for light to travel 100 m in air. The CDI algorithm used makes the quasi-static approximation (that the speed of light is infinite), and fitting shorter taus therefore is not justified by the approximation used. The longest tau of 6 ms was chosen as the smallest value that ensured a good fit to the (lowfrequency) data, even though it corresponds to a tau value twice the period of the lowest frequency used. Because of errors associated with the quasi-static approximation, high-frequency (56 kHz) data was deweighted (by factors of 0.1 and 0.01 for the in-phase and quadrature components respectively) in the fitting process. In the CDI process, fitting errors were of the order of 2 to 3% of the maximum (high-frequency in-phase) response. When the EM system used has a bandwidth appropriate to the conductivity structure to be imaged, and the structure is 1D, absolute errors in depth to top of a conductive layer are typically 10% or less of the depth below the bird. Absolute errors in depth to the bottom of a conductor are greater than this, commonly of the order of 20% of the depth below the EM system (Macnae and Lamontagne, 1987). The CDI image however, shows relative (fiducial to fiducial) errors and depth resolution much better than this. The presence of any 2D or 3D structures gives rise to artefacts and leads to greater relative and absolute errors in the CDI section (Stolz et al., 1995) whose nature is difficult to quantify in general.

606


a

Determined from porosity, formation factor and penetrometer measurements, see text.

Table 2. Typical electrical conductivity ranges for marine depositsa.

Three DIGHEM survey lines, L20010, L20020 and L20140, were chosen as representative of the Sydney Harbour survey. L20010 and L20020 run along the western side of the survey area. L20140 passes over the Sow and Pigs reef near the centre of the survey area, see Figure 1. For layered earth inversion, the same starting model parameters were adopted for all three lines, specifically3: SIG1 = 0.01 S/m, PCERR = 2%, σ1= 4 S/m (σ1+ = 6, σ1−= 2), ∆1= 10 m; σ2 = 1 S/m (σ2+= 2, σ2−= 0.5), ∆2= 10 m; σ3 = 0.5 S/m, (σ3+= 1, σ3−= 0.1), ∆3= 10 m; σ4= 0.1 S/m, (σ4+= 0.5, σ4−= 0.01), ∆4= 10 m; where σξ+(σξ−), is the upper (lower) conductivity bound, and ∆ξ is the thickness for layer ξ. Rapid CDI was performed on these same lines using EM Flow. The 2

Depth to bedrock was also estimated from a recent marine seismic study (Northside Storage Tunnel, unpublished) in a limited area covering the north-east segment of the AEM survey.

3

The choice of starting model is experimental and is not necessarily optimal.

Vrbancich et al.

conductivity sections for the survey lines, projected onto the northing coordinate (m), are shown in Figures 3 and 4 for AEMI and EM Flow respectively. These are "stitched" from individual independent 1D conductivity versus depth estimates at each fiducial, with a fiducial separation of about 3 m. The same conductivity colour table is used for all conductivity sections. The depth to bedrock (red), accurate echo sounding bathymetry (black), and bathymetry derived from Geoterrex-Dighem proprietary inversion (GD-inversion) (white, Vrbancich et al., 2000) profiles can be used to appraise the accuracy of the depth inversions. The inverted conductivity has the potential to define lateral and vertical variations in seawater and seabed conductivity, characterising sea bottom type and identifying the presence of shallow bedrock as well as defining water depths. Bathymetry Layered earth inversion: - If conductivities greater than about 2.5 S/m are attributed to seawater, the inverted conductivity versus depth sections for all 3 lines (Figure 3) are in good agreement with the known water depth over most of the survey area, even in the deepest regions (about 30 m). For L20010 (Figure 3a), independent echo-sounding measurements are unavailable over most of the flight path (between 6252400 m and 6255600 m). However, the GDinversion bathymetry was shown to be accurate, on average, to within about 2.6% in areas shallower than 10 m (Vrbancich et al. 2000). Thus the GD-inversion bathymetric profile (white) between 6254200 m and 6255400 m in Figure 3a is expected to be reliable. The depths between 6253000 m and 6254000 m, Figure 3a, can be estimated from chart soundings (Royal Australian Navy chart AUS201, Port Jackson). Between 6253400 m and 6253900 m the water depth is 25 m, with a 32 m hole at 6254000 m, in close agreement with the inverted conductivity (Figure 3a) and GDinversion (white). Between 6253000 m and 6253400 m, the depth is about 18 to 20 m, and the inverted conductivity overestimates the depth by about 10%. For L20020 (Figure 3b), conventional bathymetry (black) covers most of the survey line, and for L20140 (Figure 3c) there is almost total coverage. Figure 3 shows that overall, there is very good agreement between the water depths and the base of the conductive surface layer in the inverted conductivity sections. EM Flow inversion: - The EM Flow results are similar to the AEMI results (Figure 4). The interpreted seawater layer has a higher average conductivity than the layered earth inversion typically about 6 S/m. For L20010, Figure 4a, between 6253000 m and 6253400 m, the agreement with estimated depth of about 18 to 20 m is very good, as is the agreement with single beam soundings between 6255600 m and 6256300 m at about 15 to 20 m depth. The estimated 32 m depth (hole) at 6254000 m and estimated 25 m depth between 62534000 m and 6253900 m is underestimated by EM Flow. For L20020 and 20140 (Figure 4a,b), there is generally very good agreement with measured depth soundings, especially down to about 20 m. Sediment and bedrock The conductivity sections (Figures 3 and 4) can be used to identify shallow regions of bedrock and layers of sediment. The conventional bathymetry (black) and marine seismic bedrock (red) profiles define the actual upper and lower sediment boundaries reasonably well. It is assumed that for the purpose of this analysis, unconsolidated marine sand has a conductivity range between about 0.3 S/m and 2 S/m and that marine sandstone has a conductivity less than 0.3 S/m (see Table 2). Line L20010 passes closest to the four major sandstone promontories on the western side of Sydney Harbour, namely


Bradleys Head (~6252580 m), Chowder Head (~6253500 m), Georges Head (~6254250 m) and Middle Head (~6255300 m), by 55 m, 160 m, 30 m and 150 m respectively. These headlands are shown in Figure 1. It would therefore be expected that the Hawkesbury Sandstone basement lies closer to the sea surface along the L20010 line than for the other survey lines. The inverted conductivity sections for L20010 (Figures 3a, 4a) correctly identify the locations and approximate depths of the marine sandstone basement ridges extending out from Bradleys Head and Georges Head. Depth to bedrock data is not available for the region around Middle Head, but both AEMI and EM Flow interpretations have predicted shallow bedrock at about 10 to 15 m depth and about 30 m depth respectively near 6255300 m. (The identification of shallow bedrock in this region is more clearly defined by the AEMI interpretation.) The bedrock ridge extending from Chowder Head is at about 30 m depth at its shallowest, beneath ~25 m deep seawater, and is not defined on either L20010 section. The bedrock ridges associated with Bradleys Head, Georges Head and Middle Head are detectable because they peak at much shallower depths (~10 m). Between 6254200 m and 6254800 m, the thickness of the interpreted sediment wedge (orange tones, Figures 3a, 4a) increases from about 10 m, to 40m, in agreement with the bathymetry and seismic boundaries. The bedrock trough centred at 6254800 m (Figure 3a) is detectable, even though its depth is comparable to that of the Chowder Head ridge, presumably because of the relatively shallow seawater (8m versus 25m). On the inverted conductivity section for the next survey line (L20020, Figures 3b, 4b), the bedrock features associated with Georges Head, Bradleys Head and the predicted bedrock ridge associated with Middle Head are still well defined. The marine seismic depth to bedrock profile disagrees with the derived conductivity sections in the vicinity of Bradleys Head. Here, the bedrock is clearly identified from the conductivity section in both L20020 and L20010 and the northing coordinate location is based on accurate navigation using differential GPS. Given the navigational inaccuracy of the Emerson and Phips study (1969) and other inaccuracies associated with obtaining interpolated depth to bedrock at the AEM survey fiducial coordinates, the discrepancy suggests that the marine seismic depth to bedrock profile is incorrect in this region of L20020 adjacent to Bradleys Head. The main feature in L20140 is the bedrock peak associated with the Sow and Pigs reef (see Figure 1) at 6254400 m (Figures 3c, 4c). The flanks of this feature are correctly defined by the sediment-basement contact (orange-blue transition) to a depth of about 40 m. Another bedrock feature at 6252400 m in Figures 3c, 4c, identifies the bedrock ridge between Shark Island and the headland north of Bradleys Head (see Figure 1). The L20140 path traverses deeper sections of the Port Jackson paleochannel, and the bedrock is noticeably deeper than on western side of the AEM survey (Figures 3a,b and 4a,b). It is apparent that the penetration for this data set is limited to a maximum depth of about 50 m. This limit is determined by the noise floor of the EM response which is about 1 to 2 ppm at best, seawater depth and the lowest operating frequency. The EM Flow conductivity versus depth section for L20140, Figure 4c, very clearly outlines the depth to bedrock profile associated with the Sow and Pigs reef to depths of 50 m. The increasing water depth either side of this peak reduces the depth of investigation to less than 40 m in 20 m water. The mean L1 misfits (Equation 1) and their associated standard deviations ( ) for the inverted conductivity models along lines L20010, 20020 and 20140, are 3.5 (0.9), 4.4 (1.0), and 4.2 (1.4), respectively. The confidence with which inferences can be drawn from the model parameters is reduced when the L1 misfit is greater than unity. The fact that the L1 misfit is approximately 4 on


607

Vrbancich et al.


Fig. 3. AEMI conductivity sections (S/m) with profiles of depth to bedrock from seismic surveys (red), echo sounding water depths (black) and GDinversion water depths (white): L20010 (a), L20020 (b) and L20140 (c). Proximity of sandstone promontories in L20010: BH, Bradleys Head; CH, Chowder Head; GH, Georges Head and MH, Middle Head.

Fig. 4. EM Flow conductivity sections (S/m) with profiles of depth to bedrock from seismic surveys (red), echo sounding water depths (black) and GD-inversion water depths (white): L20010 (a), L20020 (b) and L20140 (c). Proximity of sandstone promontories in L20010: BH, Bradleys Head; CH, Chowder Head; GH, Georges Head and MH, Middle Head.

608


Vrbancich et al.

average indicates that the differences between observed and calculated voltages, arising from both measurement error and the assumptions inherent in 1D inversion, are equivalent to uncertainties of about 8%. This level of uncertainty is larger than expected. Violation of the 1D assumption will increase the L1 misfit near abrupt changes in seafloor topography. The discrepancies between observed and calculated voltages have not been analysed in detail, but will be explored in a more comprehensive paper in the future. It is possible that one channel was noisy or incorrectly calibrated. Notwithstanding the relatively high L1-misfits, the inverted conductivity models exhibit good agreement with the sonar depth sounding data. For EM Flow, the percentage fitted-errors (L2 norm) are about 2% for all three survey lines. Conductivity decreases with depth, consistent with compaction of sediment leading to lower porosity. Marine sand sediment conductivity is about 1 S/m in regions where there is reasonably good agreement between the seismic bedrock profile and top of resistive basement (less than 0.3 S/m) on the conductivity sections (Figures 3 and 4). In areas with shallow bedrock, the transition from seawater through sediment to bedrock is clearly identified: for example in Figure 3a, 4a, L20010, in the regions closest to Bradleys Head, Georges Head and Middle Head. In some cases, areas of deeper sediment appear to be correctly identified, for example, between Georges Head and Middle Head, 6254200 m to 6255400 m, Figures 3a, 4a, and either side of the Sow and Pigs reef bedrock from 6253600 m to 625500 m, Figure 3c, 4c. In both cases, the depth of investigation is enhanced by the relatively thin layer of conductive seawater overburden. CONCLUSION Conductivity sections have been generated from DIGHEM data over shallow seawater using both layered earth inversion (AEMI) and rapid conductivity-depth imaging (EM Flow). Interpreted seawater, sediment and bedrock boundaries are estimated from loosely defined conductivity ranges associated with each generic layer. The ground truth information (acoustic bathymetry and depth to bedrock) over most of the survey region enables an accurate appraisal of each method. The interpreted water depths from the layered earth inversion have been shown to be in good agreement to within about 10 % over both the shallow and deepest regions (32 m). Variations greater than 10 %, observed in some segments of the survey, most likely arise from noise and levelling errors in the original EM response data set that give rise to artifacts in the inversion process (Vrbancich, et al., 2000). Similar agreement with known water depths were obtained from the CDI sections, however there appears to be better agreement with known depths below 20 m using layered earth inversion, for example, between 6253000 m and 6253350 m, Figures 3c,4c; and at 6254000 m, Figures 3a,4a and 3b,4b.


This implies that with 10 m seawater (45 S) overburden, a residual integrated conductance of 65 S would enable a depth of investigation to 65 m in a marine sand sediment of 1 S/m. These depths are not realised, however the conductivity versus depth sections clearly show areas of relatively deep sediments below shallow seawater to depths of about 40 to 50 m below sea level, e.g., between Georges Head (6254200 m) and Middle Head (6255400 m), Figures 3a,b and 4a,b, and either side of the Sow and Pigs reef bedrock (6254000 m to 6254800 m), Figures 3c and 4c. A direct comparison between the two inversion programs is not straightforward because the results are not necessarily optimised for either program. Inversion produces conductivity models which satisfy the data, whereas CDI transforms data into conductivitydepth space. Once the data have been deconvolved into the tau domain, EM Flow computes the conductivity versus depth sections in a fraction of the time compared to the layered earth inversion. Tau-domain conversion time is comparable to CDI processing time. However, the 1D inversion provides superior definition of conductivity variations. In addition to interpreting water depths to about 30 m, this study has shown that for shallow water depths less than this bathymetric limit, the DIGHEM technique provides a capability for remote sensing of seabed properties. This is an important outcome from this study. The analysis is based on experimental survey data obtained from the use of a standard DIGHEM exploration bird. The technology has since been considerably improved with the introduction of the "resistivity" bird. The new bird provides significantly enhanced in-flight calibration and stability, leading to lower noise EM data, and hence greater penetration and enhanced confidence for parameter estimates. DIGHEM therefore offers realistic potential to detect areas of shallow bedrock and differentiate between consolidated and unconsolidated sediment in seawater depths up to 25 m. ACKNOWLEDGEMENTS J.V. gratefully acknowledges the Sydney Ports Corporation for permission to fly the survey over Sydney Harbour and for generously providing their available bathymetry data for use as ground truth. J. V. also acknowledges Northside Storage Tunnel for releasing marine seismic survey data for use as a ground truth in the north-east section of the AEM survey. J.V. gratefully acknowledges the Royal Australian Navy (RAN) for sponsoring the AEMB investigation through its Science Scholarship scheme. J.V. acknowledges helpful discussions with G. Hodges and M. Hallett (formerly Geoterrex-Dighem) concerning the DIGHEM system and A. Donohoo (DSTO) for assistance in preparation of the Figures. We gratefully acknowledge the sponsors of AMIRA project P407a for permission to use version 5.02 of EM Flow. REFERENCES

Higher resistivity regions associated with the extension of Hawkesbury Sandstone promontories into the drowned river valley are clearly identified. The correspondence between the top of EM basement and the marine seismic bedrock profiles is governed by the seawater depth: bedrock is accurately delineated in shallow water (< 20m). In one region, east of Bradleys Head, the location of shallow bedrock interpreted from EM appears to be more accurate than that derived from marine seismics. The marine seismic data were probably compromised by either an interpolation error and/or a navigational error. DIGHEM bathymetry through 4.5 S/m seawater can be reliably achieved to depths of about 25 m, as confirmed by comparison with sonar bathymetry. The maximum depth of investigation is estimated as that for which conductance is approximately 110 S.

Bennett, R.H., Lambert, D.N., Hulbert, M.H., Burns, J.T., Sawyer, W.B. and Freeland, G.L., 1983, Electrical resistivity/conductivity in seabed sediments, in Geyer, R.A., Ed., CRC Handbook of Geophysical Exploration at Sea: CRC Press. Emerson, D.W. and Phipps, C.V.G., 1969, The delineation of the bedrock configuration of part of Port Jackson, New South Wales, with a boomer system: Geophys. Prosp., 17, 219-230. Fullagar, P.K., 1981, Inversion of horizontal electromagnetic soundings over a stratified earth: unpubl. Ph.D. thesis, University of British Columbia, 264p. Fullagar, P.K. and Oldenburg, D.W., 1984, Inversion of horizontal loop electromagnetic frequency soundings: Geophysics, 49, 150-164. Grant, F.S. and West, G.F., 1965, Interpretation Theory in Applied Geophysics: McGraw Hill. Hutt, J. and Berg, J.W. Jr., 1968, Thermal and electrical conductivities of sandstone and ocean sediments: Geophysics, 33, 489-500.


609

Vrbancich et al. Jackson, P.D., Taylor Smith, D. and Stanford, P.N., 1978, Resistivity-porosity-particle shape relationships for marine sands: Geophysics, 43, 1250-1268. Kermabon, A., Gehin, C. and Blavier, P., 1969, A deep-sea electrical resistivity probe for measuring porosity and density of unconsolidated sediments: Geophysics, 34, 554-571. Macnae, J. and Lamontagne, Y., 1987, Imaging quasi-layered conductive structures by simple processing of transient electromagnetic data: Geophysics, 52, 545-554. Macnae, J.C., Smith, R., Polzer, B.D., Lamontagne, Y. and Klinkert, P.S., 1991, Conductivity-depth imaging of airborne electromagnetic step-response data: Geophysics, 56, 102-114. Macnae, J.C, King, A., Stolz, E., Osmakoff, A. and Blaha, A., 1998. Fast AEM data processing and inversion: Exploration Geophysics, 29, 163-169. Nekut, A.G., 1987, Direct inversion of time-domain electromagnetic data: Geophysics, 52, 1431-1435. Palacky, G.J., 1988, Resistivity characteristics of geologic targets, in Nabighian, M.N., Ed., Electromagnetic methods in applied geophysics-theory (Volume 1): Society of Exploration Geophysicists, Tulsa, Oklahoma, 53-129. Palacky, G.J., and West, G.F., 1991, Airborne electromagnetic methods, in Nabighian, M.N., Ed., Electromagnetic methods in applied geophysics-theory (Volume 2, Part B): Society of Exploration Geophysicists, Tulsa, Oklahoma, 811-879. Parker, R.L, and McNutt, M.K., 1980, Statistics for the one-norm misfit error: J. Geophys. Res., 85, 4429-4430. Roy, P.S., 1984, New South Wales estuaries: their origin and evolution, in Thom, B.G., Ed., Coastal Geomorphology in Australia. Sydney: Academic Press, 99121. Roy, P.S., 1983, Qaternary geology, in Herbert, C., Ed., Geology of the Sydney 1:100,000 Sheet 9130 Sydney: Geol. Surv. of NSW, 41-91. Schon, J.H., 1996, Handbook of Geophysical Exploration, Volume 18, Physical Properties of Rocks: Fundamentals and Principles of Petrophysics: Pergamon, p.421. Stolz, E.S. and Macnae, J.C., 1998, Evaluating EM waveforms by singular-value decomposition of exponential basis functions: Geophysics, 63, 64-74. Stolz, E.S., Raiche, A., Sugeng, F. and Macnae, J., 1995, Is full 3-D inversion necessary for interpreting EM data?: Exploration Geophysics, 26, 167-171. Vrbancich, J., Hallett, M. and Hodges, G., 2000, Airborne electromagnetic bathymetry of Sydney Harbour: Exploration Geophysics, 31, 179-186.

610

