Effects of Highly Laminated Reservoirs On the Performance of ...

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While-Drilling Formation-Tester Sampling with Oval, Focused, and. Conventional Probe Types. Hamid Beik, The University of Texas, Mark Proett, Halliburton, ...
SPWLA 51st Annual Logging Symposium, June 19-23, 2010

Effects of Highly Laminated Reservoirs on the Performance of Wireline and While-Drilling Formation-Tester Sampling with Oval, Focused, and Conventional Probe Types Hamid Beik, The University of Texas, Mark Proett, Halliburton, Carlos Torres-Verdín, The University of Texas, Tony van Zuilekom, and Bob Engelman, Halliburton, Kamy Sepehrnoori, The University of Texas Copyright 2010, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors.

probes in laminated reservoirs. Comparisons of the numerical simulations and a field example provide the basis for conclusions about predictions of probe-type performance and for recommendations about lessons learned.

This paper was prepared for presentation at the SPWLA 51st Annual Logging Symposium held Perth, Australia, June 19-23, 2010.

ABSTRACT

INTRODUCTION

Probe designs for formation testing and sampling tools have evolved from the simple, round, cylindrical snorkel to new shapes and configurations. There are now elongated or oval-shaped probes, as well as probes with a focusing ring and an oval-shaped, focused probe. These new probes were designed to improve fluid sample quality and reduce pumping times; however, their performance in laminated reservoirs may not always meet all desired expectations. Depending on reservoir heterogeneity, the behavior of probes varies with respect to the presence of lamination sequences, borehole deviation, and probe orientation. Moreover, the probe’s potential flow rate is affected by the probe shape, particularly when it is paramount to maintain the formation fluids above the saturation pressure. To achieve an optimum pumpout flow rate, the probe pressure vs. flow rate performance must be considered. The primary objective of this paper is to assess the viability of the new probes in highly laminated reservoirs using simulations and field examples.

Most formation producing intervals have some form of heterogeneity. They are frequently formed in a depositional environment, which leads to laminations, but other types of heterogeneities can arise from carbonates with dual porosities and vugs to naturally fractured rocks. Laminated sands were chosen for this study because the geometry has a consistency and is normally the basis of source rock anisotropy. When the laminations are on a small scale in relation to the size of the producing interval, such as a perforated casing spanning 10 ft or more, the interval can be treated as a homogeneous rock with permeability anisotropy. However, when using formation tester probes, it is not uncommon for the lamination thicknesses to range from a fraction of an inch to several inches, which is on the same size scale as the probes. This is evident when pressure testing; it is not unusual for the mobility (mD/cP) to vary several orders of magnitude within an interval. Sampling is typically performed after a favorable test point is detected that has a relatively high mobility for the interval. Formation pressure testing is also called pretesting because it has traditionally been a precursor to sampling. Because pumpouts can be performed at faster rates and with lower pressure differential in higher mobilities, the pumping times should decrease.

The new simulation study compares probe-type formation testers in various laminated formations. In one case, the probe is deployed between the laminations; in other cases, it spans two or more laminations. For the first time, the focusing effect of focused-sampling probes and oval-focused probes in highly laminated formations are compared. To account for the drilling environment, dynamic mud invasion is invoked to build the mudcake, whereby the filtrate invasion is conditioned by the petrophysical properties of the layered reservoir. Filtrate loss continues during pumping and sampling, except at the probe sealing area. The Dynamic mudcake model is used to simulate the differences between wireline and while-drilling formation-testing by varying the invasion time from 1 to 48 hours.

Pumpout simulations have been performed for probetype formation testers, but difficulties arise in accurately predicting their behavior in laminated intervals. Several recent detailed studies have been made using simulations of formation-tester sampling tools (Alpak et al. 2008; Angeles et al. 2007; Malik et al. 2009). However, these numerical models were limited regarding finely laminated rocks and formationtester probe types. In these studies, the laminations were large compared to the probe size and placement, and had little localized effect on the invasion and sample cleanup other than being placed closer to a

Various in-situ fluid viscosities are also used to compare focused-sampling probes with oval-focused

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transition boundary (Alpak et al. 2004; Wu et al. 2002; Zeybek et al. 2004). These simulations primarily focused on interval pressure transient testing and history matching using straddle packers. Although the assumptions made for history matching were relevant to the case studies presented, they did not address the small features that affect probe-sampling performance, which is the focus of this study.

2005). Reservoir and mud filtrate fluid properties affect the sample cleanup time, pressure drop, and fluid fractional flow rate. Viscosity is a driving factor in the fluid movement, which is inversely proportional to mobility. When selecting the most appropriate formation tester configuration for a given reservoir rock, viscosity is a key factor; its importance was a motivation to investigate the relation between cleanup time and in-situ fluid viscosity for the new generation of focused probes.

Several attempts have been made to study the physical process of mud-filtrate invasion in the drilling environment (Liang et al. 2009; Suryanarayana et al. 2007); However, the assumptions frequently made underestimate the dynamic mud-filtrate invasion in the beginning of the invasion process, which leads to biased results of contamination cleanup times when invasion times are short (Hadibeik et al. 2009). This is the case for the new formation testers that can sample while drilling when invasion times are on the order of hours, rather than days. Using the true dynamic model of filtrate invasion enables the design of the appropriate probe-type formation tester to acquire clean samples. In addition, the difference between wireline formation testers (WFT) and formation testing while-drilling (FTWD) can be compared with the dynamic mud invasion model.

BACKGROUND AND ASSUMPTIONS To accurately estimate the properties of the fluids an equation-of-state compositional fluid flow simulator by Computer Modeling Group Ltd. (CMG) was used to develop the numerical models. Four general cases of reservoir type are defined: homogeneous isotropic, homogeneous anisotropic, thick laminations (heterogeneous isotropic), and thin laminations (heterogeneous anisotropic). Position-dependency of reservoir physical properties, such as permeability and porosity, is identified as heterogeneity; directiondependency of these properties is anisotropy. Thick laminated layers (more than 1 ft) in a reservoir can be assumed to be a heterogeneous-isotropic reservoir if the permeability does not depend on the direction within a layer. A sequence of thin laminations, approximately 1 in. thick, results in a heterogeneous-anisotropic reservoir. Layer thickness, if it is thin or thick, is referred to here in comparison to the probe size, whether a layer is larger than the probe size or smaller. Table 1 summarizes the petrophysical properties for these four rock-type cases. Lamination in synthetic reservoirs 3 and 4 consists of two different layers; one layer has high permeability and porosity, and the other layer has low permeability-porosity and the individual layers are isotropic (i.e., kv/kh=1).

Reliable reservoir assessment involves complexities in dealing with heterogeneous anisotropic reservoirs. Previous studies assumed that the sampling probe is in contact with a single layer (Proett et al. 2001; Xu et al. 1992; Angeles et al. 2007). Some studies accounted for reservoir heterogeneity when a permeability barrier is set across the probe (O’Keefe et al. 2006). Angeles et al. (2009) interpreted the focused-sampling probe measurements in a laminated reservoir; however, the efficiency of various sampling probes in laminated reservoirs must be compared. The performance of each probe varies in thin or thick laminated formations when the probe is set across the layers arbitrarily.

Table 1 Petrophysical properties assumed for synthetic reservoirs. Difference between reservoir type 3 and 4 is the thickness of their layers as shown in Fig. 1. kH kV Swirr φ Reservoir Type (mD) (mD) 1. Homogeneous 100 100 0.2 0.11 Isotopic 2. Homogeneous 100 10 0.2 0.11 Anisotropic 3. Thick (1 ft) 100 100 0.2 0.11 Laminations 1 1 0.1 0.11 100 100 0.2 0.11 4. Thin (1 in) Laminations 1 1 0.1 0.11

In real-world circumstances, the pumpout flow rate varies as a result of reservoir heterogeneity and mobility variation (Sarkar et al. 2000; El Zefzaf et al. 2006; Jones et al. 2007). To obtain clean fluid samples, the operator adjusts the pumping rate to insure the single-phase flow of reservoir fluid into the sample chamber. Another practical aspect of this study is to consider the rate adjustment for fluid sampling to result in a constant drawdown pressure drop at the formation sand face. Pristine low contamination samples are required for meaningful laboratory PVT fluid properties in which the effects of filtrate contamination are eliminated from the in-situ fluid (O’Keefe et al. 2007; Canas et al.

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95.0

96.0

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101.0

102.0

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where xmc is mudcake thickness (in.), t is time of invasion (sec), kmc is mudcake permeability (mD), ΔP is pressure drop across the mudcake (psi), μm is mud viscosity (cP), and λ is growth factor. The flow rate of mud-filtrate invasion is:

104.0

9,189.0

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100 90 80 9,190.0

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70

q (t ) =

60 50 41

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1.00 0.50

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2.00 feet

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1.00 meter

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Relative Permeability, fraction

(a) Reservoir with Thick Laminations (1ft) 94.0

100 90 80 9190.0

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70 60 50 41

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1.00

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1.00 meter

31 21

,

0.8

Layer 1 Layer 2

kro

0.6 0.4

krw

0.2 0

0

0.2 0.4 0.6 0.8 Water Saturation, fraction

1

(a) Relative permeability

20 Capillary Pressure, psi

Layer 1 Layer 2

15 10 5 0

0

0.2 0.4 0.6 0.8 Water Saturation, fraction

1

(b) Capillary pressure

Chin (1995) described the dynamic mud-filtrate invasion process. In this model, dynamic mudcake growth and filtrate loss depends on both mud and formation properties. Fig. 3 shows the mudcake growth and filtrate loss into the formation. The simplified form of the mud invasion model is:

2.54 14, 696 μ m

(2)

1

To study the effect of lamination on sample cleanup time, we assume that the reservoir models are at constant irreducible water saturation; however, relative permeability and capillary pressure curves are different for each layer (Fig. 2). In this study, the capillary pressure data for the drainage and imbibition processes are the same.

2t ΔPλ kmc

,

1

104.0

Fig. 1 Lamination thickness vs. probe size. Physical layers that have thick laminations (i.e., ~1 ft) that are larger than the probe diameter are shown in (a); and fine laminations (i.e., ~1 in) that are smaller than the probe diameter are shown in (b). The number of numerical grids is 317,580 blocks to define these cases.

1

14, 696 μ m xmc (t )

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(b) Reservoir with Thin Laminations (1 in)

xmc (t ) =

ΔP

where q(t) is mud invasion flow rate (cm3/sec/cm2). This mudcake model enables the comparison of WFT with FTWD. Table 2 summarizes the mudcake properties used in the simulations.

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0.00

2.54 k mc

Fig. 2 Relative permeability and capillary pressure data used for synthetic layers. Layer 1 has small permeability and porosity, and the permeability-porosity for layer 2 is larger than layer 1. krw is the water relative permeability, and kro is the oil relative permeability.

(1)

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

This convergence is particularly sensitive to the concentration of grid points at or near the probe. Fig. 4 shows the grid refinement study for the heterogeneousanisotropic reservoir case when the number of grids increased from 317,580 to 635,160 blocks. To incorporate the dynamic mud filtrate invasion, the filtrate loss was modeled with a stepped invasion rate curve. These step changes cause the contamination and pressure drop shown in Fig. 4 to have small step changes. When the step functions for invasion become smaller and approach a smoothed curve, the contamination and pressure drop histories develop into smoothed curves.

Invasion rate, cm3/sec/cm2

0.06 0.05 0.04 0.03 0.02 0.01 0 10

-4

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-1

0

10 10 10 Time, hr

1

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10

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(a) Filtrate loss

This study compares the cleanup time and efficiency of each probe in the laminated reservoir. The numerical method is valid to use while pressure drop during pumpout has a certain minimum constraint. The relative error of the pressure profile is estimated to be approximately 4% for homogeneous-anisotropic and 8% for thin laminations cases without any significant change in the contamination fractional flow rate.

0.1

Xmc, in

0.08 0.06 0.04

PUMPOUT RATE SELECTION

0.02 0 10

-4

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0

10 10 10 Time, hr

1

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There are two limitations on the pumpout rate selection. First, the pumping differential pressure should not cause a two-phase flow region near the sampling probe which can limit the pumping pressure differential. Second, the rate is varied to maintain the desired pressure differential but can not exceed the pump′s performance curve. By monitoring the pressure gauges in real-time, it is possible to adjust the flow rate and prevent the flowing pressure from going below the saturation pressure and forming gas. Moreover, the overbalance and hydraulic pressure bounds the pump performance. To effectively simulate the real environment, we consider the maximum pressure drop constraint to be 500 psi, whereas the reservoir pressure is 4,000 psi with a 1,000 psi overbalance.

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(b) Mudcake growth Fig. 3 Dynamic mud-filtrate invasion and mudcake growth vs. time. Flow rate of invasion decreases with time as mudcake thickens.

Table 2 Sealing mudcake properties. Variable Units Maximum thickness in. Overbalance pressure psi Filtrate viscosity cP Growth factor Mudcake permeability mD

Value 0.1 1000 1 0.01 0.0001

According to Proett et al. (2000), the spherical flow for a single probe can be estimated as: 14, 696 μ qo ΔPss = , (3) 2π rs k s

NUMERICAL MODEL

where ΔPss is the steady-state drawdown pressure (psi), rs is the equivalent probe radius (cm), ks is the spherical permeability (mD), μ is fluid viscosity (cP), and qo is the pump flow rate (cm3/sec).

A grid refinement study was performed to appraise the simulation results and to choose the grid sizes for convergence. This was performed similarly to that described by Hadibeik et al. (2009); however, additional study is needed for the laminated reservoir. Previously, a numerical study was performed wherein the results in specific time intervals were compared. An accurate model is determined when the response of the reservoir model during the sampling test converges and becomes unaffected by the addition of more grid points.

The spherical permeability is obtained by using the geometric average: ks = 3 kr2 k z , (4) where kr is the radial permeability (mD), and kz is the vertical permeability (mD).

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Contamination, fraction

10

10

10

10

pressure difference; otherwise, the flow rates decrease with the same ratio to secure the pressure drop constraint.

0

SP-C1 GR-C1 SP-C2 GR-C2

-1

Table 3 Pumpout flow rate of different probes in base-case model. Pumpout flow rate cc/sec Probe Type Sample Guard Total Single probe 7.5 Oval probe 22.6 Focused-sampling 1.875 5.625 7.5 probe Oval-focused probe 11.3 11.3 22.6

-2

-3

0

0.5

1 1.5 Time, day (a) Water cut, SC

2

2.5

Sealing Areas

5000

Pressure, psi

4000 1"

3000 2000

SP-C1 GR-C1 SP-C2 GR-C2

1000 0

0

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1 1.5 Time, day (b) Pressure drop, psi

2

Guard Probe (Ring)

(a) Focused-sampling probe

2.5

Sealing Area

Fig. 4 Grid refinement study for laminated reservoir. Water cut at standard condition (SC) indicates an independent response, regardless of the grid blocks in case 1 (C1) and case 2 (C2) for sample probe (SP) and guard ring (GR). However, the pressure drop for case 1 (317,580 grids) is less than case 2 (635,160 grids) for both sample probe and guard ring.

∑h k

i i

,

8"

Guard Ring 7"

Sealing Area 6"

Sample Probe

Equation (3) can also be used for other types of probes by modifying the equivalent source radius. For laminated reservoirs, the arithmetic mean is used to estimate the up-scaled radial permeability:

kr =

2"

Sample Probe

1" 2"

(5)

3" (b) Oval-focused probe

ht where hi is lamination thickness (ft), ki is layer permeability (mD), and ht is the total reservoir thickness (ft).

Fig. 5 Schematic of focused-type formation testers with numerical grid blocks used for modeling. The single probe is basically configured with a similar grid definition, and is equivalent to a 1-in. diameter probe. The standard oval probe follows the same grid pattern as the guard area of the ovalfocused probe.

The up-scaled vertical permeability can be estimated using a harmonic average: h kv = t , (6) h ∑ kii where kv is the vertical permeability (mD). Table 3 summarizes pumpout flow rates for homogeneousanisotropic reservoir, including reservoir rock property assumptions. These flow rates apply until the pressure drop constraint satisfies the maximum of 500-psi

WATER-BASED MUD MODELING

Vertical Well – The base model is used to compare four types of probes (single, oval, focused-sampling, and oval-focused probe) in a laminated reservoir (Fig. 5). Four cases are modeled, including homogeneous-

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

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Fig. 6 Pumpout time to achieve 10% mud-filtrate contamination in the vertical well. Four cases (homogeneous-anisotropic, thin lamination with 1 in. layering, thick lamination with 1 ft layering, and probe “straddling” two link lamination case) are compared for various probe type formation testers.

anisotropic: thin (1 in.), thick (1 ft), laminated reservoirs, and finally the straddle case when the probe spans between a poor and a good quality layer of the thick laminations. Fig. 5 shows the two new focused probes and their numerical mesh grids. Table 4 and Table 5 describe the reservoir and fluid properties for water-based mud (WBM).

Table 4 Assumed reservoir properties. Property Units Wellbore radius ft External radius ft Reservoir thickness ft Rock compressibility 1/psi

Value 0.354 160 30 3.0e-10

Table 5 Assumed fluid properties for base case WBM. Property Unit Value Oil density gm/cm3 0.839 Water density gm/cm3 1.000 Oil compressibility 1/psi 3.0e-6 Water compressibility 1/psi 2.5e-6 Oil viscosity cP 0.5 Water viscosity cP 1.0 Oil bubblepoint pressure psi 500

The mud-filtrate invasion occurs from 1 to 48 hours to encompass the framework of wireline and whiledrilling formation testers. The time in which a probe acquires a fluid sample with 10% contamination is used to compare the efficiency of probes. Normally, samples of less than 5% contamination are required, but 10% was used here because, in some cases, this level of contamination was not possible. Fig. 6 compares the WBM results in a vertical well.

In general, the focused probes show faster cleanup times than the unfocused probes in similar conditions. However, the oval probes show a significant improvement in laminated conditions. It is interesting

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that straddling a thick lamination was not that much different from positioning the probe within the high permeability lamination. This is probably because positioning the probe near a boundary helps to focus the flow and reduce the pumping times. Although the primary benefit of the oval pads is partly attributable to their increased flow capacity, it is also evident from Fig. 6 that the oval-focused probe yields a clean fluid sample in less pumping time for all cases. 98.0

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All types of probes achieve clean fluid samples faster in thinly laminated intervals than in intervals with large laminations. The thinly laminated reservoir acts as a homogeneous anisotropic reservoir when the size of the probe is larger than the layer thickness. In thick laminations, the two low quality layers above and below the higher permeability layer where the probe is placed (see Fig. 8) bound fluid flow between the layers, which reduces the efficiency of sampling for this case.

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in invasion radius between the high quality layer and the adjacent low quality layer (Fig. 7). Therefore, the straddle case cleanup process significantly reduces pumping times in FTWD when compared to the wireline case.

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1.00 0.90 0.80

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0.00 0.00

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0.04 0.00

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0.20 0.10

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1.00 meters

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0.32 0.28 0.24

9191.0

(b) Oval -focused probe Fig. 7 Water saturation distribution for straddle case in laminated reservoir. Both probes cannot clean up the low permeability-porosity zone during the sampling test. However, the oval-focused probe secures a larger clean region for sampling than the focused-sampling probe.

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(b) Thin laminated layering, 1 in

As demonstrated by Hadibeik et al. (2009), reducing the invasion time reduces the pumpout time for a given probe in a homogeneous formation. In the case of FTWD, the invasion time is small; therefore, there has been little filtration into the zones. In addition, the radius of the filtrate invasion is larger in the WFT invasion time frames (i.e., 24 to 48 hrs). Consequently, for the straddle case, the cross flow is much greater for wireline than for FTWD because of the greater contrast

Fig. 8 Water saturation profile and evolution of fronts near the wellbore during fluid sampling test with oval-focused probe. (a) Thick laminated layers show that two low quality layers bound the saturation fronts; however, (b) thin laminated layering indicates that as a result of small thickness of layers, low quality layers do not affect the focusing effect of the probe.

Without imposing a pressure constraint, the pressure drop can be compared for the focused-sampling probe

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

and the oval-focused-sampling probe (i.e., inner areas of the probes). Fig. 9 indicates that the pressure drop is larger for the focused-sampling probe than for the ovalfocused-sampling probe. The pressure drop comparison reveals that in thinly laminated reservoirs there is a larger pressure drop while sampling than in other cases. Although saturation evolution is not bound in the thin layers, the cleanup process is still faster, relative to other cases.

both probes in a deviated borehole compared to a vertical well shown in Fig. 6. Fractional flow of filtrate contamination entering the probe also reveals that the focused-sampling probe differentiates among the reservoir layers in various conditions; however, this is not the case for the ovalfocused probe. In this case, the fractional flow curves are more stacked, as shown in Fig. 11. Three horizontal well cases are studied: homogeneous anisotropic, thick laminations (1 ft thick), and thin laminations (1 in thick) reservoir (see Table 1).

5000

4000

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2500 2000

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Pressure, psi

4500

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(a) Focused-sampling probe

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2500 2000

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1

0

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Fig. 9 Pressure drop comparison for oval-focused probe and focused-sampling probe in three cases of thin laminated layers (1 in. thickness), thick laminated layers (1 ft thickness), and straddle case when the probe spans between a high quality layer and low quality layer.

Homg. Lam. 1 in Lam. 1ft Strad.

0

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10 Invasion time, hr

10

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(b) Oval-focused probe Fig. 10 Numerical simulation result for 30 degree deviated well in four different cases of reservoir type (homogeneousanisotropic, thin lamination with 1 in. layering, thick lamination with 1 ft layering, and straddle case). The general trend of cleanup time is the same as for a vertical well (Fig. 6); however, because of the borehole orientation, the cleanup time is slightly longer in a deviated well.

Deviated and Horizontal Wells – Focused type probes were evaluated in a 30 degree deviated well and in a horizontal well. When the invasion time is small (FTWD), the simulations demonstrate that cleanup time is almost independent of formation type for the ovalfocused probe in deviated wells and in vertical wells. Fig. 10 also shows an increase in sampling time for

Fig. 12 shows the numerical simulation results for the focused-sampling probe and the oval-focused probe. The probe position is facing the top of the borehole for fluid sampling. In general, these probes yield a clean

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sample faster in horizontal wells with thick laminations than in thinly laminated reservoirs with vertical and deviated wellbores. This statement is true when the probe is sampling in the high quality layer. In this case, the low quality layers act as barriers in the upper and lower parts of the high quality layer, and prevent the contamination from flowing toward the probe from adjacent layers. However, the probes are not affected by these barriers in the thin laminated formation. Further comparison indicates that fluid sampling is faster in a horizontal well than in a vertical or deviated well with thick laminations when invasion time is short (FTWD), primarily because the radius of invasion is smaller.

permeability becomes more significant for WFT in homogeneous anisotropic reservoirs. However, in the thick laminations case (where kv/kr=1 on each layer), the cleanup times are actually faster than a homogeneous case with anisotropy. A simulation of a thick-layered formation with a horizontal borehole is shown in Fig. 13 where the top and bottom low permeability boundaries help channel the flow into the probe.

Pumpout time, hr

10

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1 Homg. Lam. 1 in Lam. 1 ft Strad.

0.8 0.6

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1.2 1.3 Time, hr

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Fig. 12 Contamination cleanup time to reach a 10% level of contamination for fluid samples in horizontal well. Ovalfocused probe obtained clean samples faster than focusedsampling probe in all cases of homogeneous anisotropic, thin laminated, and thick laminated reservoirs.

1.5

(b) Oval-focused probe Fig. 11 Contamination fractional flow entering the probe after 1 hr of mud filtrate invasion. Focused-sampling probe differentiates among the reservoir types more than ovalfocused probe in fluid sampling.

OIL-BASED MUD MODELING To model oil-based mud (OBM) invasion, we use the same numerical mesh as in the WBM case. The main difference is the change of reservoir simulator from a black oil model to a compositional model. This change enables an equation of state (EOS) to be incorporated and the miscibility of OBM into the reservoir oil to be accurately simulated. The Peng-Robinson EOS is used to track phase behavior, and Lohrenz-Bray-Clark’s

In comparing the homogeneous anisotropic case with the thick laminations case in the horizontal well, it is apparent that FTWDs acquire clean samples in homogeneous anisotropic reservoirs faster (Fig. 12). However, this effect is reversed for long invasion times (WFT). This is because the effect of vertical

9

SPWLA 51st Annual Logging Symposium, June 19-23, 2010

(LBC) method to calculate the fluid viscosities. Table 6 and Table 7 summarize the oil component properties used for in-situ oil and OBM.

INFLUENCE OF CLEANUP TIME

For the base model, the properties for OBM assume a free gas mixed with a dead oil, and the in-situ oil is a light oil with solution gas. A molar-based contamination function is necessary to determine the contamination of fluid sample (Hadibeik et al. 2009). Molar-based functions yield the contamination fractional flow based on conservation of mass. Because there is no volume conservation in general, volumebased contamination functions may not always be accurate. Therefore, fluid density is a reliable molarbased contamination function and used in this work.

WBM – The black oil model varies with four different viscosities from 0.5 to 15 cP to encompass a large range of reservoir fluids, but the viscosity of WBM remains constant. The pressure drop is set to be no more than 500 psi, and the sampling pumpout rate is varied during the fluid withdrawal test. Fig. 15 shows the pumpout rate for the sample probe with variations of in-situ fluid viscosity. High in-situ fluid viscosities increase the pumpout cleanup time (see Fig. 16). In this case, the invasion time is 1 hr, and pumpout time is measured when the probe acquires a sample with 10% contamination.

where ρ(t) is measured density, ρo is formation oil density, and ρm is mud density. Fig. 14 indicates the comparison of miscible OBM in the oil reservoir for two focused-type probes. Table 6 Mole fractions and equation of state properties of the assumed in-situ hydrocarbon pseudo-components. Parameter N2C1 CO2C3 C4C6 C7C18 C19+ Molar 0.618 0.079 0.087 0.179 0.036 concent. Critical -126 125.9 359.8 656.2 1060 temp. (°F) Critical 653.3 839.4 498.2 322.3 184.4 press. (psi) Acentric 0.011 0.146 0.230 0.490 0.919 factor Molecular 16.6 36.23 67.73 132.8 303.2 weight (lb/mole) Volume -0.19 -0.131 -0.056 0.171 0.231 shift parameter

90

90

VISCOSITY

100

9193.0 9192.0 9191.0 9190.0 9189.0 9188.0 9187.0 9186.0

9186.0 9187.0 9188.0 9189.0 9190.0 9191.0 9192.0 9193.0 9194.0

The density contamination function is given by: ρ (t ) − ρo C (t ) = , (7) ρ m − ρo

IN-SITU

110

0.00

3.50

7.00 feet

0.00

1.00

2.00 meters

100

110

ON

100 90 80 70 60 50 41 31 21 11 1

9186.0 9187.0 9188.0 9189.0 9190.0 9191.0 9192.0 9193.0 9194.0

Table 7 Assumed oil-based mud parameters and their mole fractions and equation of state properties. Parameter MC14 MC16 MC18 Molar 0.6489 0.2145 0.1364 Concentration Critical 755.1 822.5 878.1 temperature (°F) Critical 261.8 240.2 224.4 pressure (psi) 0.6257 0.7118 0.7842 Acentric factor Molecular 190 222 251 weight (lb/mole) Volume shift 0.0792 0.0666 0.0439 parameter

90

90

100

9193.0 9192.0 9191.0 9190.0 9189.0 9188.0 9187.0 9186.0

(a) Permeability 110

0.00

3.50

7.00 feet

0.00

1.00

2.00 meters

100

110

1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00

(b) Water saturation Fig. 13 Horizontal well with thick laminations, (a) permeability, (b) water saturation profile during pumpout test. Probe is set in the middle of high quality layer.

OBM – The compositional model is used for the case of OBM with 1 cP viscosity invading an oil reservoir with viscosities from 0.5 to 15 cP. Unlike WBM invasion, the OBM contamination is miscible with the reservoir

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

oil. Table 8 and Table 9 list the results of miscible OBM in the reservoirs with different viscosities using the focused-sampling probe and oval-focused probe. The OBM invasion takes place for 1 hr, then the pumpout test begins. Invasion continues around the probe throughout the pumpout process. The contamination level, bottomhole pumpout rate, and cumulative pumpout fluid volume are measured at the end of the pumpout test. The contamination level of the fluid sample increases as in-situ oil viscosity increases, whereas the total pumpout volume and pumpout rate decreases to maintain the 500 psi pressure drop. As a result of maintaining a constant pressure drop, the ratio of sample probe to guard ring flow rate remains almost constant.

10

10

10

Pumpout rate, bbl/day

1 0.8 0.6 0.4 0.2 0

0

0

-1

Homg. Lam. 1 ft Strad.

-2 0

1

10 Invasion time, hr

10

10

2.5

0.5 cp 1.0 cp 5.0 cp 15.0 cp

4 2

2

0

0.5

1 1.5 Time, day

2

2.5

(b) Oval-focused probe Fig. 15 Comparison of pumpout rates between inner clean sample probes of focused-sampling probe and oval-focused probe. The pumpout rate decreases with increased in-situ fluid viscosity.

1

0

10

-1

Homg. Lam. 1 ft Strad.

-2

10

2

6

0 10

Pumpout time, hr

Pumpout time, hr

10

1 1.5 Time, day

8

(a) Focused-sampling probe 10

0.5

(a) Focused-sampling probe

1

10

0.5 cp 1.0 cp 5.0 cp 15.0 cp

1.2

Pumpout rate, bbl/day

Pumpout time, hr

10

1.4

0

1

10 Invasion time, hr

10

2

(b) Oval-focused probe

10

10

10

1

0

-1

Oval focused Focused sampling

-2 0

10 10 In-situ fluid viscosity, cp

Fig. 14 Miscible OBM in the oil reservoir indicates the contrast of cleanup times is less than WBM for the focusedsampling probe and oval-focused probe. Fluid sampling time becomes important in comparing homogeneous-anisotropic reservoirs and laminated reservoirs.

1

Fig. 16 Pumpout time to obtain fluid sample with 10% of contamination in homogeneous anisotropic oil reservoirs with different in-situ fluid viscosity. The general behavior of the focused-sampling probe and oval-focused probe is the same with increasing downhole fluid viscosity; however, ovalfocused probe cleanup times are faster than the focusedsampling probe.

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

pressure points varied from the regression gradient line (i.e., residuals). Fig. 18 shows the accuracy of the gradients with the upper and lower variances listed next to each gradient in the overpressure plot. The red curves in the residual plot represent the boundaries of the expected pressure variations for the pressures based on assumed pressure and depth variations (Collins et al. 2007). The blue curves represent the measured boundary variances determined from the regression of the pressure data. Pressure points are selected such that the measured variations fall within the expected variations as a quality criterion.

Table 8 Focused-sampling probe performance with difference of in-situ fluid viscosity. In-situ oil viscosity (cP)

Contamination level (%)

Bottomhole pumpout rate

Pumped fluid volume

(cc/sec)

(liter)

SP

GR

SP

GR

0.5

2.34

2.5

7.5

8.9

40

1

0.68

2.5

5.74

7.0

27.0

5

4.22

1.0

3.0

3.9

12.0

15

15.9

0.36

1.8

1.5

8.2 1st Motor

Table 9 Oval-focused probe sampling performance with difference of in-situ fluid viscosity. In-situ oil viscosity (cP)

Contamination level

Bottomhole pumpout rate

(%)

(cc/sec)

1st Pump

Pumped fluid volume (liter)

SP

GR

SP

GR

0.5

0.42

15

15

53.4

53.4

1

0.45

9.94

9.96

36.5

31

5

1.66

3.98

4.89

9.5

12.9

15

5.8

2.3

3.09

4.4

8.9

Oval Focused Probe Quartz Gauge 2nd Motor 2nd Pump

OVAL-FOCUSED PROBE FIELD EXAMPLE A field test of the oval-focused probe was recently performed. The reservoir interval was moderately low in mobility (1 to 10 mD/cP) and was considered highly heterogeneous. The tool string configuration, shown in Fig. 17, consisted of two pumping sections with one above and one below the probe section. A fluid ID section was located on the outlet of each pump to measure density, pressure, and fluid temperature. Other sensors, such as an NMR fluid sensor, were available but the density was used for the contamination estimates. The direction of the guard ring flow and inner clean probe flow can be selected to be up or down. For lighter oils, it is usually advantageous to pump the clean sample down to the sample chambers. This process enables the lighter formation oil to displace the more contaminated fluid in the flow line in a clean piston-like manner and reduces mixing with the heavier contaminated fluids. For heavy oils or water samples, the direction can be reversed.

Fig. 17 Basic oval-focused probe tool string with pumps above and below the probe section is shown. More modules can be added as needed such as additional fluid sensors and quartz gauge sections.

Overall, the gradients indicated a compositionally graded interval with the oil density increasing with depth over the interval and a lower water contact. However, the gradients were not of sufficient quality to define the density grading because this was a low mobility interval. Using a pumpout WFT, a total of 19 samples were obtained with several logging runs. In one of the logging runs, 12 samples were taken with multiple samples taken at each of the five depth points shown in Fig. 18. The oval-focused probe was used to sample from the top and bottom depth points shown in Fig. 18 and samples were taken from both the center clean probe and from the guard ring to verify the focusing effect. These samples are denoted by C for clean probe and G for guard ring. Notice two samples were taken from the clean probe C.

Initially, a pressure survey was performed as shown in Fig. 18, along with relative gradients. The gradient plot includes an overpressure plot that shows how far the

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

Sample QC Density gm/cm3 @ Sampling Conditions C- 0.X26 C- 0.X43 G- 0.X40

DH Density gm/cm3 @ Sample Cond. C- 0.X28 C- 0.X42 G- 0.X44

0.X28 0.X40

0.X07 0.X13

0.X59 0.X54

0.X56 0.X22

0.X54 0.X45

0.X44 0.X44

C- 0.X36 C- 0.X21 G- 0.X55

Gradient gm/cm3 @ Sample Cond. 0.X26 0.W28 0.X31 0.X23

0.X95 0.W98

C- 0.X24 C- 0.X24 G- 0.X65 0.X54 0.X24

1.192 1.106

Fig. 18 Gradient plot showing measured relative sample density (Sample QC) with the relative downhole density measurements and the relative gradient density (i.e., 0.X… gm/cm3). Two gradient densities are shown in the residual track, which represent the range of the gradient regression uncertainty (i.e., 0.W.. = 0.X..-0.1 gm/cm3). Densities were adjusted based on an EOS to be at a consistent sample pressure and temperature. The oval-focused probe was used to sample at the upper depth and lower depths, and the densities in the depth track were recorded when samples were taken downhole. The middle samples were taken with a standard oval probe. The densities noted as C and G are the center clean probe and the guard ring, respectively. The densities shown on the left were measured after the samples were recovered.

A high accuracy density sensor was used to monitor density throughout the pumpout for both the clean and guard areas of the oval-focused probe. The relative downhole densities are shown in the depth track of Fig. 18 for each sample taken at different time intervals. For the standard oval probes, two densities are shown for the two samples taken. The first density was actually the last sample taken. Also shown are sample quality control (QC) densities on the far left of Fig. 18, which were measured after the samples were recovered (Eyuboglu et al. 2009). These relative densities were adjusted using assumptions for the fluid EOS so that the densities can be compared at reservoir conditions.

variance. The measured QC densities had similar results, confirming the downhole measurements. The oval-focused probe example at the lower depth point is shown in Fig. 19. At the beginning of the pumpout, the flow rates were adjusted to reach and maintain an acceptable pressure differential in both the center clean probe and guard ring. Although the total flow rate was maintained for most of the cleanup period, changes in viscosity increased the pressure differential which began to tax the pump near the end of the pumpout. A sample was taken at 4 ½ hours with an estimated contamination of less than 5%. Similar results were obtained with the oval-focused probe at the upper sample depth.

Although one of the standard oval probe samples was within the range of the gradients, the other two oval probes′ samples were not. Both of the focused samples, however, were well within the gradient measured

If the filtrate density and the uncontaminated formation fluid density are known, then it is relatively simple to determine the contamination by volume fraction. Although these densities can be estimated based on

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

filtrate properties and the pressure gradient, there is usually too much uncertainty to be definitive. However, these estimates are helpful in bracketing the absolute values for a regression trend analysis, which is shown by the smooth dark red and blue curves in Fig. 19. These contamination curves clearly demonstrate the focusing effect in which the contamination from the clean center section of the probe is considerably offset from the guard-ring side.

All but one of the standard oval probe samples′ pumpouts had an estimated contamination greater than 5%. This exception to the trend of lower contamination in the oval-focused samples was probably attributable to the heterogeneity of the formation where the standard oval probe was located at a more favorable test depth.

CONCLUSIONS

Based on the regression trend analysis, the filtrate and sample densities are estimated and used to determine the contamination from the recorded downhole densities (i.e., real contamination curves in Fig. 19). The guard is considerably offset from the clean probe side and is closer to the initial density of the filtrate. Both of the focused fluid samples had this characteristic.

The following conclusions stem from the numerical simulations and interpretation studies considered in this paper: •



Contamination, percent

90



Guard contamination, fit Guard contamination, real Clean contamination, fit Clean contamination, real

80 70 60 50 40 30



20 10 0 0.5

1

1.5

2

2.5 3 Time, hr

3.5

4

4.5



5

(a) Sample and guard contamination history



Volume rate, cc/sec

20 Clean Rate Guard Rate

15



10

• 5

• 0

0

1

2 3 Time, hr

4

5



(b) Sample and guard pumpout rate Fig. 19 Field testing pumpout results for a oval-focused probe showing density-based contamination and flow rate curves for the guard and clean sample probes.

14

In general, laminations increase sampling cleanup times, and it is highly dependent on the lamination thickness and probe position with respect to adjacent layers. Focused probes reduce the cleanup times over nonfocused probes, assuming that at least a portion of the probe is in the high permeability lamination. When comparing probe geometries, the oval probes reduce the cleanup times over circular probes (focused and non-focused), with the most pronounced improvements being in the presence of laminations. This is partly because of the faster pumping rates obtainable in real world sampling conditions. For focused probes, there is a loss of focusing effect in laminated reservoirs, which increases the pumpout time and causes a greater pressure drop. In most cases, the standard oval probe reduces sampling time over the circular focused-sampling probe in laminated reservoirs (thick and thin laminations). Fluid sampling in horizontal wells can be faster than vertical wells in the case of FTWD if the probe is set in the appropriate good quality layer. Pressure drop is larger in thin laminated reservoirs than other cases. Therefore, a pressure constraint is needed to compare the probe type formation testers in real world conditions. In this study, oval-focused probe cleanup time is almost independent of lamination type for FTWD formation testers (low invasion time). The pumpout time increases when the in-situ fluid viscosity is increased, which results in a corresponding decrease in the pumpout rate to maintain the same pressure drop for sampling. Considering the assumptions in this study, the fluid sampling time increases from the homogeneousanisotropic reservoirs to the thinly laminated, then to thick lamination and, finally, the straddle case, which has the largest pumpout time to yield a clean sample.

SPWLA 51st Annual Logging Symposium, June 19-23, 2010



Recent field testing using a oval-focused probe generally confirms the focusing effectiveness in a heterogeneous environment.

REFERENCES Alpak, F., Elshahawi, H., Hashem, M., and Mullins, O., 2008, Compositional modeling of oil-based-mudfiltrate cleanup during wireline formation tester sampling, SPE Paper 100393, Reservoir Evaluation & Engineering, Volume 11, Number 2, pp 219-232.

NOMENCLATURE

λ C(t) ΔP xmc(t) kmc q(t) ρm ρο φ k kro krw ks kr kz kv hi ht

OFP FP OP SP Swirr OBM WBM EOS FTWD LWD

: : : : : : : : : : : : : : : : : : : : : : :

: : : : :

Growth factor Contamination by time variation Pressure drop across the mudcake, [psi] Mudcake thickness, [in.] Mudcake permeability, [mD] Mud invasion flow rate, [cm3/sec/cm2] Mud density, [lb/ft3] In-situ oil density, [lb/ft3] Porosity Formation permeability, [mD] Oil relative permeability Water relative permeability Spherical permeability, [mD] Average radial permeability, [mD] Vertical permeability, [mD] Average vertical permeability, [mD] Lamination thickness, [ft] Reservoir thickness, [ft] Oval-focused probe Focused-sampling probe Oval probe Single probe Irreducible water saturation Oil-based mud Water-based mud Equation-of-state Formation-tester while-drilling Logging-while-drilling

Alpak, F. Torres-Verdín, C., Habashy, T., and Sepehrnoori, K., 2004. Simultaneous estimation of insitu multi-phase petrophysical properties of rock formations from wireline formation tester and induction logging measurements, SPE Paper 90960, Proceedings of Annual Technical Conference and Exhibition, Houston, Texas. Angeles, R., Torres-Verdín, C., Lee, H., Alpak, F., and Sheng, J., 2007. Estimation of permeability and permeability anisotropy from straddle-packer formation-tester measurements based on the physics of two-phase immiscible flow and invasion. SPE Journal Paper 95897, vol. 12, pp. 339-354. Angeles, R., Torres-Verdín, C., Sepehrnoori, K., and Elshahawi, H., 2009, History matching of multiphaseflow formation-tester measurements acquired with focused-sampling probes in deviated wells. Proceedings of SPWLA Annual Technical Conference and Exhibition. Canas, J., Low, S., Adur, N., and Teixeira, V., 2005, Viscous oil dynamics evaluation for better fluid sampling. Proceedings of SPE/PS-CIM/CHOA Paper 97767, International Thermal Operations and Heavy Oil Symposium. Chin, W., 1995, Formation invasion, with applications to measurement-while-drilling, time lapse analysis and formation damage. Gulf Publishing Company, Houston, Texas.

ACKNOWLEDGEMENTS The authors wish to thank Halliburton Energy Services for permission to publish this project and for their funding through a summer internship position offered to Hamid Beik in 2009. The work described in this paper was partially funded by The University of Texas at Austin Research Consortium on Formation Evaluation, jointly sponsored by Anadarko, Aramco, Baker-Hughes, BG, BHP Billiton, BP, Chevron, ConocoPhillips, ENI, ExxonMobil, Halliburton, Hess, Marathon, Mexican Institute for Petroleum, Nexen, Petrobras, Schlumberger, StatoilHydro, TOTAL, and Weatherford. A special note of gratitude goes to Petrobras for permission to publish this study and support the work. We are thankful to Mike Bittar (Halliburton Energy Services) for his technical support.

Collins, C., Proett, M., Storm, B., and Gustavo Ugueto, 2007, An integrated approach to reservoir connectivity and fluid contact estimates by applying statistical analysis methods to pressure gradients. SPWLA Paper 2007_HH Proceedings of Annual Technical Conference and Exhibition. Eyuboglu, S., Pelletier, M. Rourke, M., van Zuilekom, T., Saghiyyah, G. et al., 2009, New non-invasive sample chamber testing methods confirm downhole sensor measurements and verify sample quality. SPWLA Paper 2009, Proceedings of Annual Technical Conference and Exhibition.

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SPWLA 51st Annual Logging Symposium, June 19-23, 2010

Hadibeik, A., Proett, M., Torres-Verdín, C., Sepehrnoori, K., and Angeles, R., 2009, Wireline and while-drilling formation-tester sampling with oval, focused, and conventional probe types in presence of water and oil-based mud-filtrate invasion in deviated wells. Paper 2009, Proceedings of Annual Technical Conference and Exhibition.

Sarkar, A., Jaedong, L., and Ekrem, K., 2000. Adverse effects of poor mudcake quality: a supercharging and fluid sampling study. SPE Paper 64227, Journal of Reservoir Evaluation & Engineering, vol. 3 no. 3, pp. 256-262. Suryanarayana, P., Wu, Z., Ramalho, J., and Himes, R., 2007. Dynamic modeling of invasion damage and impact on production in horizontal wells. SPE Paper 95861, Journal of Reservoir Evaluation & Engineering, vol. 10, no. 4, pp. 348-358.

Jones, C., Alta, W., Singh, J., Engelman, R., Proett, M., et al., 2007, Collecting single-phase retrograde gas samples at near-dewpoint reservoir pressure in carbonates using a pump-out formation tester with an oval pad. SPE Paper 110831,Proceedings of Annual Technical Conference and Exhibition.

Wu, J., Torres-Verdín, C., Proett, M., Sepehrnoori, K., and Belanger, D., 2002. Inversion of multi-phase petrophysical Properties using pumpout sampling data acquired with a wireline formation tester. SPE Paper 77345, Proceedings of Annual Technical Conference and Exhibition, San Antonio, Texas.

Liang, L., Abubakar, A., and Habashy, T., 2009. Determination of petrophysical parameters and mud filtrate invasion profile using joint inversion of induction logging and pressure transient measurements. Proceedings of SPE Annual Technical Conference and Exhibition.

Xu, H., Bassiouni, Z., and Desbrandes, R., 1992. 3-D finite difference modeling of wireline formation tests in tight gas sands, 1992. SPE Paper 24886, Proceedings of SPE Annual Technical Conference and Exhibition, Washington, D.C.

Malik, M., Torres-Verdín, C., and Sepehrnoori, K., 2009, A dual-grid automatic history-matching technique with applications to 3D formation testing in the presence of oil-based mud-filtrate invasion,” SPE Paper 109956, Journal, vol. 14 no. 1, pp. 164-181.

Zeybek, M., Ramakrishnan, T., Salamy, S., and Kuchuk, F., 2004. Estimating multiphase-flow properties from dual-packer formation-tester interval tests and openhole array resistivity measurement. SPE Paper 87474, Journal of Reservoir Evaluation & Engineering, vol. 7, no. 1, pp. 40-46.

O'Keefe, M., Godefroy, S., Vasques, R., Agenes, A., Weinheber, P., et al., 2007, In-situ density and viscosity measured by wireline formation testers. Proceedings of Asia Pacific Oil and Gas Conference and Exhibition, 2007.

Zefzaf, T., Fattah, M., Proett, M., Engelman, R., and Bassiouny, A., 2006. Formation testing and sampling using an oval pad in Al Hamd field, Egypt, 2006. SPE Paper 102366, Proceedings of Annual Technical Conference and Exhibition, San Antonio, Texas.

O'Keefe, M., Eriksen, K., Williams, S., Stensland, D., and Vasques, R., 2006, Focused-sampling of reservoir fluids achieves undetectable levels of contamination. SPE Paper 110364, Proceedings of Asia Pacific Oil & Gas Conference and Exhibition. Proett, M., Chin, W., and Batakrishna, M., 2000, Advanced dual-probe formation tester with transient, harmonic, and pulsed time-delay testing methods determines permeability, skin, and anisotropy. SPE Paper 64650, Proceedings of International Oil and Gas Conference and Exhibition in China. Proett, M., Gilbert, G., Chin, W., and Monroe, M., 2001. New wireline formation testing tool with advanced sampling technology. SPE Paper 71317 Journal of Reservoir Evaluation & Engineering, vol. 4, no. 1, pp. 76-87.

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