IPTC Copyright 2014, International Petroleum Technology Conference

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1 IPTC Flow Modeling and Comparative Analysis for a New Generation of Wireline Formation Tester Modules Morten Kristensen, SPE, Cosan Ayan, SPE, Yong Chang, Ryan Lee, Adriaan Gisolf, SPE, Jonathan Leonard, SPE, Piere-Yves Corre, and Hadrien Dumont, Schlumberger Copyright 2014, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Doha, Qatar, January This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box , Richardson, TX , U.S.A., fax Abstract Wireline formation testing (WFT) is an integral part of reservoir evaluation strategy in both exploration and production settings worldwide. Application examples include fluid gradient determination, downhole sampling, fluid scanning in transition zones, as well as interval pressure transient tests (IPTTs). Until recently, however, formation testing was still challenging and prone to failure when testing in low-mobility, unconsolidated, or heavy-oil-bearing formations, especially with single-probe type tools. A new-generation WFT module with a 3D radial probe expands the operating envelope. By using multiple fluid drains spaced circumferentially around the tool, the new module can sample in tighter formations and sustain higher pressure differentials while providing mechanical support to the borehole wall. We performed a detailed flow modeling-based analysis of the contamination cleanup behavior during fluid sampling with the new module. Using both miscible (sampling oil in oil-based mud) and immiscible (sampling oil in water-based mud) contamination models we studied the cleanup behavior over a wide range of formation properties and operating conditions. Comparison of the cleanup performance of the new module with the performance of conventional single-probe tools demonstrates that the new module is 10 to 20 times faster than the single-probe tools when sampling in tight formations. Finally, we also compared the new module against the sampling performance of dual packers and a focused probe. This work is directly relevant to the planning and fundamental understanding of wireline fluid sampling. The key contributions are miscible and immiscible contamination cleanup models that include the effect of tool storage, a comprehensive analysis of contamination cleanup behavior for the new-generation WFT module with comparisons against conventional single-probe, focused probe, and dual-packer tools, and a characterization of fluid sampling conditions versus the preferred type of sampling tool. Introduction A logical start for any wireline formation testing (WFT) operation is a tool string design that considers the formation evaluation objectives and expected formation and fluid properties. With the current availability of an arsenal of probes having different shapes, focused probes of circular or elongated design, and dual packers, this planning stage has now become a more complex process. The recently introduced 3D radial probe (Al Otaibi et al. 2012; Flores de Dios et al. 2012) adds another choice for the engineers in planning WFT surveys. Successful WFT operations demand that toolstrings be designed to meet specific formation and fluid challenges (Weinheber et al. 2008). The selected downhole pump and probe or dual-packer combination must be able to induce and maintain flow from the formation without causing excessive drawdown to stay above expected phase-separation envelope. It must achieve and keep a seal with the borehole face and must not plug during the cleanup operation. While achieving these performance goals, it must work effectively with the downhole pump to deliver high rates that reduce cleanup time. For transient testing, the tool system must have a small storage volume, flow should be smooth and stable, and buildup transients should be free of bore-hole or tool-induced noise. A major challenge for downhole sampling and downhole fluid analysis (DFA) is mud filtrate contamination. Acquired samples must be of sufficiently low contamination for reliable laboratory analysis, as well as better DFA. High miscible contamination (oil/gas and oil-based mud filtrate, water and water-based mud filtrate) or emulsions formed in immiscible fluids (oil and water-based mud filtrate, or water and oil-based mud filtrate) can make acquired samples unusable and reliable DFA may not be possible. Knowledge of tool interaction with the sandface, pump selection, flowing time and rate, and

2 2 IPTC focused flow practices are all important for a successful operation. To understand these parameters comparatively before a survey, a comprehensive investigation of the cleanup behavior of several tools under varying formation and fluid parameters is needed, which is the main focus of this study. The paper is organized as follows. The first section presents the mathematical models used to describe the miscible and immiscible contamination cleanup processes. The second section illustrates some fundamental behaviors observed during cleanup operations by considering a simple comparison between the new WFT module and a conventional probe. In the third section, we validate the mathematical models through comparisons with field data from a focused probe sampling job. The fourth section presents a comprehensive parameter study and performance comparison between the new module and conventional as well as elliptical probes. Finally, in the fifth section, we consider a comparison of the new module with dualpacker and focused-probe sampling. Modeling Mud Filtrate Cleanup The type of model used to describe the contamination cleanup process depends on the miscibility characteristics between the drilling mud filtrate and the reservoir fluid. For sampling oil in the presence of OBM contamination or sampling water in WBM contamination, we used a single-phase model assuming full miscibility between the filtrate and reservoir fluid. The filtrate is effectively modeled as a tracer with the properties (density and viscosity) of the mixture of filtrate and reservoir fluid dependent on the concentration of the tracer. The model equations consist of the single-phase continuity equation and a contamination tracer transport equation:... (1)... (2) where is porosity, is fluid density, is the Darcy velocity, and is the contamination concentration measured as a mass fraction. The mixture density and viscosity are assumed to be linear functions of contamination: ( ) ( )... (3, 4) where and are the viscosity and density of pure filtrate, respectively, and and are the viscosity and density of reservoir oil. We note that other (nonlinear) mixing formulas have been studied. The use of these formulas does not affect the cleanup behavior in a major way and does not alter the main conclusions of this study. Hence, we use the preceding linear mixing formulas throughout this paper. For WBM sampling of oil we assume full immiscibility between the mud filtrate and the reservoir oil. The contamination cleanup model for this case is described by the standard two-phase immiscible flow equations: { }... (5) where denotes the saturation of phase. This model requires the specification of relative permeability and capillary pressure functions between the filtrate and oil phases. These equations are solved numerically on a radial near-wellbore grid using a commercial reservoir simulator (ECLIPSE 2013). Depending on the tool geometry, certain domain symmetries can be exploited, which is illustrated in Fig. 1 along with the grid resolutions. We consider four types of WFT probes in this paper. The primary emphasis is on the new 3D radial probe, which has four elongated drains, spaced circumferentially around the tool, with a total inflow area of cm 2 (79.44 in. 2 ). The cleanup performance of this tool is compared with that of a conventional, extralarge-diameter (XLD) circular probe with a diameter of 4.06 cm (1.6 in.) and of an elliptical probe. The 3D radial probe is also compared to sampling with dual packers as well as sampling with a focused probe, which has two concentric circular drains, where the outer drain acts to guard the contamination from flowing to the inner drain. The size of the inlet area for each of the probe tools is indicated in Fig. 1. Boundary Conditions. We consider a vertical wellbore penetrating a formation of sufficient thickness so that the cleanup is not affected by upper and lower reservoir boundaries. Likewise, the lateral extent of the formation is large enough so that boundary effects are not seen in the pressure response at the wellbore. This is verified by pressure transient analysis of simulated drawdown and buildup tests, as also described in Cherukupalli et al. (2010). Outer reservoir boundaries are closed to fluid flow, and the inner boundary at the wellbore, away from drain inlets, is assumed closed as well; i.e., it is assumed that the mudcake is sealing so that filtration during cleanup can be ignored. This assumption is generally justified for fluid sampling on wireline where enough time has passed after drilling for a proper mudcake to form. The boundary condition at the drain inlets is described using the standard well equation formulation of a reservoir simulator: ( )... (6)

3 IPTC Grid: = 1,079,568 cells Grid: = 737,352 cells Grid: = 957,265 cells Grid: = 1,238,328 cells Fig. 1 Overview of WFT probes included in this study. The left column shows the tools and the size of their inlet areas. These inlet area sizes are similar to, but in some cases not identical to, established tool values. The right column shows the grid resolution used and the domain symmetry exploited in the modeling. where p c is the pressure of a boundary cell at the drain inlets, p bhp is the pressure on the tool side, and denotes the well connection transmissibility calculated for a wellbore at the center of a radial grid (ECLIPSE, 2013). Fig. 2 shows an example of a grid for the 3D radial probe with indication of the cells that connect to the inlet drains. The modeling of the inlet boundary condition assumes that pressure drops in internal flowlines of the sampling tool are negligible compared with the pressure drop between the tool and formation. Also, the model predicts the filtrate contamination as produced at the sandface. Hence, if a significant storage volume exists between the tool entry point and the sandface where the produced fluid needs to flow through before reaching the sampling bottles, the sandface contamination may be overly optimistic compared with the contamination of the fluid observed through DFA. In a subsequent section, we present a simple model for the effects of storage. This is important when comparing the cleanup performance of WFT probes to that of dual packers.

4 4 IPTC Fig. 2 Example of computational grid and numerical solution to miscible contamination cleanup for the 3D radial probe. Left: gridding with indication of inlet drain faces (the picture displays half of the full domain, whereas only one-eighth of the domain is simulated, cf. Fig. 1. Right: numerical solution to miscible contamination cleanup after breakthrough of oil (red = pure filtrate, blue = pure reservoir oil). Initial Conditions. The model is initialized hydrostatically with a specified datum pressure at the center of the sampling probes. For immiscible fluids, the mud filtrate invasion is simulated prior to the cleanup operation. Due to mudcake buildup the invasion rate follows a trend (Chin 1995). The shape of the invasion profile depends mainly on the total invaded volume and the relative permeability curves. For simulation purposes, the actual invasion rate is therefore of minor importance and influences the invasion profile only through rock/fluid compressibility effects. To mimic the invasion process, we therefore chose a representative period of 24 hours and simulated the invasion as constant rate injection over this period, with the rate specified to reach a target depth. Hence, we do not attempt to predict invasion depth, but instead treat the depth as an input to the model. For miscible cleanup processes the model is initialized postinvasion. When dispersion and diffusion processes are negligible compared with convection, a miscible contamination source will invade the formation in a piston-like manner with full displacement of the reservoir fluid. From a quick analysis of likely Peclet numbers during a filtrate invasion process, similar to the one presented by Orr (2007) for more general processes, we conclude that the transition zone between high and low filtrate concentrations is small compared with the total invasion depth when the formation is relatively homogeneous. Hence, the invasion can be approximated as piston displacement, and we therefore simply initialize the model postinvasion with 100% filtrate to the specified invasion depth. We note that similar arguments and assumptions were made by Hammond (1991) when modeling miscible contamination invasion and cleanup. To assess the sensitivity of the results to piston-like invasion we performed a number of numerical experiments while accounting for varying degrees of dispersion. The results show that, even when the invasion profile was significantly smeared by dispersion, the resulting cleanup curve was affected only during the early part of cleanup. When contamination dropped below 5% the cleanup behavior was practically insensitive to the amount of dispersion (Fig. 3). Basic Behavior of Cleanup As an introductory example, we considered the miscible contamination cleanup of OBM filtrate during oil sampling. Using the model parameters listed in Table 1, we simulated the cleanup process using both the 3D radial probe and the XLD probe. The results are reported as the volume fraction of filtrate in the produced stream versus total pumped volume as well as versus time. To allow fair comparison, the two WFT probes are operated at a constant drawdown (600 psi), thus mimicking the common situation where the maximum allowable drawdown pressure during sampling is constrained by the bubblepoint pressure of the fluid. An upper limit of 25 cm 3 /s is imposed on the pump rate, which is a common rate observed during WFT surveys.

5 IPTC No dispersion D c = cm 2 /hr 0.8 D c = cm 2 /hr 0.6 D c = cm 2 /hr 0.4 No dispersion D c = cm 2 /hr 0.2 D c = cm 2 /hr Distance from wellbore [cm] D c = cm 2 /hr Fig. 3 Invasion profiles and cleanup curves for miscible contamination cleanup by the 3D radial probe at different levels of dispersion of the invasion front. For each case dispersion is modeled using a constant dispersion coefficient (D c) as indicated in the figure legends. Left: invasion profiles viewed radially away from the wellbore. Right: produced contamination during cleanup vs. total volume pumped. is plotted as a volume fraction (0 = pure oil, 1 = pure filtrate). TABLE 1 FORMATION, FLUID, AND OPERATIONAL PARAMETERS USED IN THE BASE CASE MODEL SETUP FOR MISCIBLE AND IMMISCIBLE CONTAMINATION CLEANUP Common Parameters Value Immiscible Case Parameters Value Porosity 20% WBM filtrate viscosity 0.6 cp Horizontal permeability 10 md Oil/water capillary pressure Ignored Vertical permeability 2 md Relative permeability Water-wet Oil-wet Wellbore diameter cm (8.5 in.) Residual oil saturation, S or Formation thickness 50 m Irreducible water saturation, S wi Tool distance from boundary 25 m Water relative permeability at S or Formation pressure 3,000 psi Oil relative permeability at S wi Max. drawdown during cleanup 600 psi Water and oil Corey exponents 3.0, , 3.0 Max. pump-out rate 25 cm 3 /s Connate water saturation Depth of filtrate invasion cm (4 in.) Oil viscosity 1 cp OBM filtrate viscosity 1 cp Fig. 4 shows the comparison between the cleanup curves for the two probes. For each probe, the cleanup follows three distinct regimes: a short period of pure filtrate production, an intermediate period just after oil breakthrough, and a late-time period where the cleanup rate is proportional to. The late-time cleanup rate was derived analytically for a conventional probe by Hammond (1991) and is thus confirmed by our numerical simulation. Further numerical experiments on different kinds of nonfocused sampling devices (probes as well as dual packers) show that they all follow a late-time trend proportional to. Physically this late-time regime corresponds to the situation where all filtrate around the circumference of the wellbore at the level of the sampling device has been removed, and where filtrate instead flows vertically from above and below the device. The behavior during the intermediate regime, between pure filtrate production and late-time cleanup, differs for the conventional probe and the 3D radial probe. This regime corresponds to circumferential cleanup where filtrate is drawn from around the wellbore circumference at the level of the sampling device. For a conventional probe the cleanup rate in this regime is proportional to (Fig. 4), a result that has been confirmed empirically from analysis of field tests by Mullins and Schroer (2000). For the 3D radial probe, on the other hand, the cleanup is much faster owing to the better circumferential connection provided by the four drains. In addition, with its much larger drain area the 3D radial probe can achieve a higher pump rate compared with the conventional probe, which is reflected in the overall cleanup time. To reach a level requires a pumping time of 0.7 hours for the 3D radial probe compared with 9.1 hours for the conventional probe. A contamination value of 5% is chosen for comparison, because this is a commonly observed cleanup limit for unfocussed single-probe tools. Depending on the formation interface used, available time on station, and the formation and fluid properties, higher or lower limits might be encountered. The comparison in cleanup time and volume will change depending on the contamination cut-off used. Oil sampling with WBM happens under immiscible flow conditions. Invasion profiles are not piston-like but follow the characteristic shape governed by the relative permeability curves. Fig. 5 shows two examples of cleanup under immiscible

6 6 IPTC conditions, one for a typical water-wet formation and one for a typical oil-wet formation. The quantity of invaded filtrate is the same for the two cases. As expected, cleanup is slower in the oil-wet formation. The relative performance of the 3D radial probe versus the conventional probe is similar to that for miscible cleanup. An overview of the cleanup times to reach a 5% contamination level is presented in Table 2. C ~ t -2/3 C ~ t -5/ Fig. 4 cleanup curves for OBM filtrate cleanup during oil sampling using the 3D radial probe and the XLD probe. is plotted as a volume fraction (0 = pure oil, 1 = pure filtrate). The model parameters used are listed in Table 1. Left: contamination vs. volume pumped. Right: contamination vs. time Fig. 5 cleanup curves for WBM filtrate cleanup during oil sampling using the 3D radial probe and the XLD probe. is plotted as a volume fraction (0 = pure oil, 1 = pure filtrate). The model parameters used are listed in Table 1. Left: contamination vs. volume pumped. Right: contamination vs. time. Solid lines: water-wet rock-fluid properties. Dashed lines: oil-wet rock-fluid properties. TABLE 2 PREDICTED CLEANUP TIME (HOURS) AT A 5% CONTAMINATION LEVEL FOR THE 3D RADIAL PROBE AND XLD PROBE USING MODEL PARAMETERS LISTED IN TABLE 1 Miscible Cleanup Immiscible Cleanup: Immiscible Cleanup Water Wet Oil Wet 3D radial probe XLD probe

7 3D Radial Probe XLD Probe Time 1 Time 2 Time 3 Time 4 IPTC Fig. 6 Comparison of cleanup performance between the 3D radial probe and the conventional XLD probe. The 3D contamination distribution is shown at 4 different times during the cleanup. One-fourth of the domain is displayed. The same drawdown is applied to both the 3D radial probe and the XLD probe. Because of its larger flow area and multiple, circumferentially spaced drains, the 3D radial probe can operate at higher pump rates and consequently achieves a faster cleanup compared with the XLD probe.

8 8 IPTC Fig. 6 illustrates the 3D contamination distribution during miscible cleanup at four different times. The advantage of multiple drains with large inlet areas is clearly observed in the comparison against a conventional probe. Field Data Comparison for Focused Probe Sampling The use of simulations to better understand WFT cleanup behavior is well established in the industry. Several studies have been published that use history matching as a simulation validation tool (e.g., Malik et al. 2007; Angeles et al. 2009). It is not the objective of this paper to duplicate this work. Results of a history matching exercise are included in this section to demonstrate the validity of the specific contamination cleanup model used in this study. The reservoir parameters used in the cleanup simulation are provided in Table 3. A tilted formation layer was created in the simulation due to the significant dip angle (55 ). Due to uncertainties in the estimated rock permeability (k h ) and mud invasion depth, these two parameters were adjusted within the interpretation error bounds to obtain a good match between simulation and the field data. All other parameters used were obtained directly from log interpretation reports without any adjustments. Focused sampling probes can be used in split mode, where one pump draws fluid from the sample probe and another pump draws from the guard probe, or in commingled mode, where both sample and guard probes are routed to a single pump. Commingled flow can be further broken down to commingle-up and commingle-down, denoting the location of the pump used. Fig. 7 (left) shows the measured and simulated pump rates during commingle-down, commingle-up and split flow operation. Fig. 7 (right) shows contamination during commingle-down as obtained from Optical Monitoring (OCM) (Mullins and Schroer 2000). during the subsequent commingle-up and split flow was derived from the guard side and sample side gas-oil-ratio (GOR), as measured with guard and sample side optical fluid analyzers. For this history matching application the OCM and GOR derived contaminations were adjusted to match the laboratory measured sample bottle contamination. TABLE 3 FORMATION AND FLUID PARAMETERS FOR THE FIELD COMPARISON STUDY OF FOCUSED PROBE SAMPLING Parameter Estimated Value Wellbore diameter 27 cm (10.63 in.) Formation layer thickness 7 m TVD Formation layer dip 55 Porosity 22% Formation pressure psi Formation fluid (oil) density 850 kg/m 3 Formation fluid (oil) viscosity 5 cp Filtrate density 810 kg/m 3 Filtrate viscosity 3 cp Fluid compressibility psi 1 Rock compressibility psi 1 Horizontal permeability 400 md Formation anisotropic ratio (k v/k h) 0.9 Mud invasion depth cm (2 4 in.) Comparison of Miscible Cleanup Performance To understand the cleanup performance of the 3D radial probe over a broad range in formation and fluid properties we performed a parameter sensitivity study and compared performance against the conventional and elliptical probes. Using the domain and wellbore dimensions as listed in Table 1, we studied the effects of absolute permeability, permeability anisotropy, viscosity contrast between filtrate and formation fluid, and depth of filtrate invasion. The parameter ranges considered are shown in Table 4. The viscosity contrast is varied by fixing the filtrate viscosity (1 cp) and varying the oil viscosity. The parameters are varied one at a time and results are reported as produced contamination versus total pumped volume and versus pumping time. TABLE 4 PARAMETERS AND RANGES USED IN SENSITIVITY STUDY OF WFT PROBE CLEANUP PERFORMANCE Parameter Minimum Value Maximum Value Absolute permeability: k h 0.1 md 1000 md Permeability anisotropy: k v/k h Viscosity ratio: o/ mf Depth of invasion 5.08 cm (2 in.) cm (16 in.)

9 flow rate (cc/s) contamination IPTC Pump down Pump up Model (commingle/sample Model (guard) Commingle OCM Sample GOR Based Guard GOR Based Modeled (1) (2) (3) time (s) etime (sec) Fig. 7 Field data and simulation results for focused probe sampling. Left: measured and simulated pump rates (1: commingled pumping with pump 1. 2: commingled pumping with pump 2. 3: split pumping with pumps 1 and 2). Right: simulated contamination of commingled flow vs. measured contamination using methane and color channels in the downhole fluid analyzer. Fig. 8 shows the results of the parameter study. Before interpreting the results it is worth noting that the study was performed by changing one parameter at the time, whereas formation properties generally do not adhere to this principle. A change in permeability, for example, might coincide with a change in porosity and invasion depth. In this context, we observe that cleanup volume is insensitive to formation permeability, as long as the permeability anisotropy is fixed. Formation permeability affects only the rate with which filtrate can be pumped without violating the maximum drawdown constraint. As permeability is increased, the pump rate reaches the upper limit (50 cm 3 /s was used for this part of the study), resulting in no further improvements to cleanup time. Increasing permeability anisotropy (i.e., reducing the permeability anisotropy ratio k v /k h ) leads to a reduction in both cleanup volume and time. As k v /k h is reduced, flow of filtrate from above and below the sampling point is naturally impeded, thereby enabling horizontal flow of clean formation fluid. Increasing the contrast in viscosity between the formation oil and the filtrate results in a larger cleanup volume and longer cleanup time. Again, this is expected behavior because flow is preferential to the lower-viscosity filtrate. Finally, increasing the depth of filtrate invasion naturally causes an increase in cleanup time. Overall the observations on parameter sensitivities from Fig. 8 are in line with our expectations. A similar parameter study was performed for the conventional and elliptical probes. In Fig. 9 the three types of probes are compared by measuring their performances as the volume pumped and time taken to reach a level in the produced stream. The results were studied as a function of formation mobility, permeability anisotropy ratio, fluid viscosity ratio, and depth of filtrate invasion. At low mobilities as well as at high viscosity ratios, the conventional and elliptical probes cannot produce at the minimum pumping rate (0.2 cm 3 /s), which is indicated by dashed lines in Fig. 9. As mobility is increased, the cleanup times reduce until the tools reach the upper pump rate limit, after which a further increase in mobility has no impact on cleanup time. The three probes show similar dependencies on the parameters studied. For example, doubling the invasion depth from cm (4 in.) to cm (8 in.) leads to an increase in cleanup time by a factor of approximately 4 for all three probes. Across the majority of the parameter space studied (except at high mobility, for which the cleanup time is limited by maximum pump rate constraints), the cleanup time for the 3D radial probe is between 10 and 20 times faster than the conventional probe and between 4 and 8 times faster than the elliptical probe, which can be attributed mainly to its larger drain area and better circumferential connection to the formation. The simulation results are in line with field observations, noting that 3D radial probe cleanup was 15 to 20 times faster than a circular probe (Al Otaibi et al. 2012).

10 Depth of Filtrate Invasion Viscosity Ratio Permeability Anisotropy Absolute Permeability 10 IPTC Kh = 0.1mD Kh = 1mD Kh = 10mD Kh = 100mD Kh = 1000mD Kv/Kh = 0.01 Kv/Kh = 0.1 Kv/Kh = 1 Kv/Kh = o / mf = 0.1 o / mf = 1 o / mf = 10 o / mf = Invasion = 2 in Invasion = 4 in Invasion = 8 in Invasion = 16 in Fig. 8 Predicted cleanup performance for the 3D radial probe during oil sampling in OBM. The cleanup performance was studied as a function of absolute permeability, permeability anisotropy, viscosity contrast between filtrate for formation oil, and depth of filtrate invasion.

11 Time to [hrs] Time to [hrs] Time to [hrs] Time to [hrs] IPTC E-Probe Mobility: [md/cp] 10 1 Permeability anisotropy: Kv/Kh E-Probe 10 3 E-Probe 10 2 E-Probe Viscosity ratio: o / mf Depth of invasion [in] Fig. 9 Comparison of cleanup performance for the 3D radial probe against conventional and elliptical probes. The performance is measured as the pump-out time required to reach a level and results are studied as a function of formation mobility (top left), permeability anisotropy ratio (top right), fluid viscosity ratio (bottom left), and depth of filtrate invasion (bottom right). vs. Dual-Packer and Focused Probe Sampling Following the preceding observations, it is natural to extend the analysis to investigate the relative merits of the new tool when compared against sampling with dual packers and a focused probe. As mentioned, the simulation models predict the contamination at the sandface. When sampling with dual packers, the fluid drawn from the formation first enters into the space between the packers, which is initially filled with drilling mud. From an intake on the tool mandrel the fluid then flows through fluid analyzers and is eventually directed to sampling bottles when sufficiently clean. Hence, the storage volume between the packers acts to delay the arrival of clean formation fluid. To account for this effect in a miscible contamination cleanup model we treat the storage volume as a mixing tank and assume complete and instantaneous mixing when formation fluids enter the space between the packers: ( ) ( )... (7) where is the flow rate, is the storage volume, is the contaminant concentration at the sandface, and is the contaminant concentration flowing into the sampling bottles. We assume a packer spacing of cm (40 in.) and a storage volume of 17 L (4.5 gal) which is representative for common dual-packer tools when sampling in wellbores with a diameter of cm (8.5 in.). Fig. 10 shows the comparison of sampling performance between dual packers and the 3D radial probe using the test case parameters listed in Table 1. The two tools are comparable in performance at low contamination levels (< 5%), whereas the 3D radial probe is faster during early cleanup. Dual-packer cleanup is characterized by a late breakthrough of formation fluid followed by a sharp drop in contamination. The transient effect from wellbore storage is most prominent when cleanup is

12 12 IPTC otherwise fast, i.e., at shallow invasion depths. At deeper invasion depths, when cleanup volumes are large this early-time effect has passed once contamination at the sandface reaches low-enough levels for sample collection. Further performance comparisons over broader parameter ranges reveal that dual-packer sampling is slightly faster than the 3D radial probe when invasion is deep (> 6 8 in.) and permeability anisotropy is low (k v /k h > 0.2), whereas the opposite is true at shallower invasion and greater anisotropy. When vertical flow is naturally restricted at low values of k v /k h the large vertical interval opening between the dual packers becomes a disadvantage compared with shorter and more compact tools. Dual Packer (bottle inlet) Dual Packer (sand face) Fig. 10 Comparison of cleanup performance between the 3D radial probe and dual-packer sampling. The model parameters used are listed in Table 1. For dual-packer sampling a packer spacing of cm (40 in) was assumed with a wellbore storage volume of 17 L (4.5 gal) between the packers. Left: contamination vs. volume pumped. Right: contamination vs. time. As a final investigation we compare the 3D radial probe against a focused probe. The focused probe has two concentric circular drains separated by a sealing packer (Fig. 1). Separate flowlines are connected to each drain so that the outer drain acts to guard the flow of filtrate to the inner drain. Fig. 11 shows the cleanup performance of the focused probe and the 3D radial probe using the test case parameters from Table 1. Flow focusing provides for very efficient cleanup, making the focused probe about an order of magnitude faster than the 3D radial probe. While all nonfocused tools enter a late-time cleanup regime with a cleanup rate proportional to, the sample drain on a focused probe produces essentially clean fluid shortly after breakthrough. The superior performance of the focused probe extends to broader parameter ranges than the case considered here. However, the 3D radial probe has a drain area that is 18 times larger than the total drain area of the focused probe, making sampling possible in lower-mobility formations. This has been the observed behavior since the tool was introduced, with better performance in low-mobility formations for sampling and pressure transient testing. Focused Probe (sample drain) Focused Probe (guard drain) Fig. 11 Comparison of cleanup performance of the 3D radial probe and a focused probe. The model parameters used are listed in Table 1. The focused probe was simulated assuming the same drawdown on both the sample and guard drains corresponding to single-pump operation. Left: contamination vs. volume pumped. Right: contamination vs. time.

13 IPTC Conclusions Numerical modeling is a viable tool for studying the cleanup behavior of various WFT tools, which can help in designing a tailored string. We were able to duplicate the observed cleanup behavior for existing tools, including the cleanup exponents observed for circular probes in the field as well as focused probe performance. This comparative study shows that the new 3D radial probe has superior cleanup performance compared with existing probe-type tools, both for miscible and immiscible flow conditions. Oil-wet rock for immiscible cleanup, increasing depth of invasion, increasing viscosity ratio of filtrate to formation fluid, and increasing vertical permeability all increase cleanup times. The focused probe performs better than all other tools, but loses its effectiveness in tighter formations for which the 3D radial probe performs best because of its large flow area. Cleanup times for dual-packer tools are comparable with the 3D radial probe at low contamination levels (< 5%), but generally longer at higher contamination levels, which are often more realistic for the low-mobility formations where dual-packer tools are typically deployed, considering constraints on station time, etc. Dual-packer tools suffer from the large storage volume, which acts like a mixing tank. This prolongs the cleanup unnecessarily in case of shallow depths of invasion. With an increasing diameter of invasion the cleanup time for the dual-packer increases and the sump in the interval between the packers gets progressively cleaner to achieve an acceptable level of contamination. Nomenclature C = miscible mud filtrate concentration (mass fraction) D c = dispersion coefficient k = absolute permeability p = pressure q = flow rate Q = sink/source term S = fluid saturation t = time T = well connection transmissibility u = Darcy velocity V = storage volume between dual packers = porosity = viscosity = density Super- and subscripts c = connection bhp = bottomhole pressure (tool pressure) h = horizontal inj/prod = injection/production j = fluid phase index mf = mud filtrate o = oil p = production sf = sand face v = vertical w = water References Al Otaibi, S.H., Bradford, C.M., Zeybek, M., Corre, P-Y., Slapal, M., Ayan, C., and Kristensen, M Oil/Water Delineation with a New Formation Tester Module in an Exploration Well. Paper SPE presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 8 10 October. Angeles, R., Torres-Verdin, C., Sepehrnoori, K., and Elshahawi, H History Matching of Multiphase Flow Formation Tester Measurements Acquired with Focused Sampling Probes in Deviated Wells. Paper presented at the SPWLA 50 th Annual Logging Symposium, The Woodlands, Texas, USA, June. Cherukupalli, P., Horstman, D., Arora, S., et al Analysis and Flow Modeling of Single Well MicroPilots to Evaluate the Performance of Chemical EOR Agents. Paper SPE presented at the Abu Dhabi International Petroleum Conference and Exhibition, Abu Dhabi, UAE, 1 4 November. Chin, W.C Formation Invasion. Houston: Gulf Publishing Company. ECLIPSE Technical Description Schlumberger Information Solutions. Flores de Dios, T., Aguilar, M.G., Herrera, R.P., Garcia, G., Peyret E., Ramirez, E., Arias, A., Corre, P-Y., Slapal, M., and Ayan, C New Wireline Formation Tester Development Makes Sampling and Pressure Testing Possible in Extra-Heavy Oils in Mexico. Paper SPE presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 8 10 October. Hammond, P.S One- and Two-Phase Flow During Fluid Sampling by a Wireline Tool. Transport in Porous Media 6:

14 14 IPTC Malik, M., Torres-Verdin, C., Sepehrnoori, K., Dindoruk, B., Elshahawi, H., and Hashem, H History Matching and Sensitivity Analysis of Probe-Type Formation-Tester Measurements Acquired in the Presence of Oil-Base Mud-Filtrate Invasion. Petrophysics. 48(6) Mullins, O.C., and Schroer, J Real-Time Determination of Filtrate During Openhole Wireline Sampling by Optical Spectroscopy. Paper SPE presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, USA, 1 4 October. Orr Jr., F.M Theory of Gas Injection Processes. Denmark: Tie-line Publications. Weinheber, P., Gisolf, A., Jackson, R.R., and De Santo, I Optimizing Hardware Options for Maximum Flexibility and Improved Success in Wireline Formation Testing, Sampling and Downhole Fluid Analysis Operations. Paper SPE presented at the Nigeria Annual International Conference and Exhibition, Abuja, Nigeria, 4 6 August.

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