Colloidal Dispersion Gels Improve Oil Recovery in a ... Dispersion... · Colloidal Dispersion Gels...

Colloidal Dispersion Gels Improve Oil Recovery in a Heterogeneous

Argentina Waterflood

Presented by:

TIORCO, Inc.The Improved Oil Recovery Company

Avenida Mosconi 3169 • Suite 5B • Buenos Aires, Argentina 1419 54 11 4572 0027 • 54 11 4572 0015 Fax • www.tiorco.com

FIGURE 1

Colloidal Dispersion Gels Improve Oil Recovery in a

Heterogeneous Argentina Waterflood

ABSTRACT The Loma Alta Sur Field is a mature waterflood in the Neuquén Basin of Argentina. The productive formation (Grupo Neuquen) consists of numerous fluvial, multi-layer sandstone packages. Extensive diagnostics, including tracers, injection profiles, review of historical production and reservoir fluid analysis corroborated the combined effect of reservoir heterogeneity and an adverse mobility ratio. High concentration polymer gels, sometimes called “bulk gels”, can be effective in reducing water channeling in naturally fractured formations or in reservoirs with multi-darcy permeability anomalies. However, the Loma Alta Sur Field produces from a multi-layer unfractured matrix rock reservoir and is not a candidate for traditional bulk gel treatments. Uncrosslinked polymer is an alternative for improving an adverse mobility ratio, but is most effective in relatively homogeneous reservoirs in order to minimize polymer breakthrough in offset producing wells. The primary objective of the the operator in this pilot was to improve volumetric sweep efficiency. CDG’s were selected for the Loma Alta Field for several reasons: (1) CDG’s offer significantly higher adsorption and residual resistance factors than uncrosslinked polymer (2) CDG’s can be injected in matrix rock and (3) fresh water was not required for gel formation at low polymer concentrations. Extensive diagnostics were applied before and after the CDG injection, including tracers, injection profiles and analysis of historical production data. Post treatment analysis of the CDG treatments indicate positive oil and water trends in the pilot area. INTRODUCTION The Loma Alta Sur field is located in the province of Mendoza in the Neuquén Basin of Argentina (Figure 1). The productive reservoir is the Grupo Neuquen Formation, which is characterized as heterogeneous multi-layer sandstone. In an effort to control the vertical distribution of injected water, injection wells are completed with downhole selective injection mandrels. However, the combined effects of heterogeneity within the individual layers and the extremely adverse mobility ratio motivated the operator to evaluate techniques for in-depth volumetric sweep improvement. Polymer is a traditional alternative for viscosifying water and lowering the mobility ratio. However, relatively homogeneous reservoirs are preferred in order to avoid polymer breakthrough in offset producing wells. The objective of the operator was to apply a staged chemical injection program that would reduce water channeling in the highest permeability layers and, as a secondary benefit, improve the oil-water mobility ratio.

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FIGURE 2

FIGURE 3

NEUQUEN BASIN GEOLOGY The Triassic-Cretaceous Neuquen Basin of west-central Argentina covers an area of nearly 200,000 sq. km (Figure 1). A seven kilometer thick sedimentary succession has been developed after three main geotectonic stages: 1) Basin onset and fault-induced subsidence after Triassic – Early Jurassic extensional collapse of a Late Paleozoic marginal orogenic belt; (2) Middle Jurassic – Paleogene regional subsidence behind a retreating subduction system; (3) Neogene contractional deformation and local load subsidence forced by advancing subduction conditions. The habitat of petroleum in the Neuquen Basin is regulated internally by a heterogeneous Jurassic - Cretaceous stratigraphy which features stacking of multiple clastic, carbonate and evaporite genetic intervals which developed under highly fluctuating base-level conditions. Stratigraphic complexity has provided a variety of migration conduits and internal separators that has induced a laterally and vertically variable distribution of oil and gas reservoirs throughout the basin. The key stratigraphic component of the Neuquen Basin is a 6,000-m thick Middle Jurassic to Paleocene wedge that contains most of the source rocks and the hydrocarbon bearing members (Uliana and Leggareta 1993). Dark ammonite-bearing shales are the most common source rocks and a prominent stratigraphic component in the folded belt ranging from Central Neuquen to southern Mendoza. The best source development is evident at the base of the Vaca Muerta Shale. It consists of 45-50 m of marly shales deposited in basinal-to-distal ramp settings (Veiga and Orchuela 1989). The bulk of the reserves known in the basin are geographically related to the area where the Tithonian Vaca Muerta interval behaved as an effective source rock in updip locations. The Vaca Muerta and the regional shales act as local top-seals in several fields. Oil-bearing facies range from braided-stream conglomerates to fluvial channels and from deltaic to shallow-marine sandstones. All these deposits carry a sizable mixture of volcanic debris (Rosenfeld. 1978). The western side of the Malargue Platform and the adjacent fold-and-thrust belt are areas that contain high-yield source rocks (Figure 2). A limited number of large oilfields, including the Loma Alta Sur field, are found in this region.

LOMA ALTA SUR FIELD GEOLOGY The exploitation of the Loma Alta Sur Field began in 1990 with the LAS-x1 well. The field includes 72 producing wells with an average depth of 450 m. Forty six producing wells and nine injecting wells are currently active. The producing interval in the Loma Alta Sur Field is the Grupo Neuquen (Figure 3), which is divided into four stratigraphic sequences: V, VI, VII and VIII. Each one of the sequences contains multiple sand packages, delineated in “gamma ray” and “SP” logs, which consist of lenticular channel-fill deposits of medium to fine grained sandstones that are typical of a meandering river depositional environment

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FIGURE 4

TABLE 1

Reservoir Characteristics Reservoir Type Sandstone Area, acres 57.3 Reservoir Temp, °C 45 Average Depth, m 450 Total Pay Thickness, m 35 Permeability Range, md 20 – 1000 Dykstra-Parsons Coefficient, v 0.89 Porosity, % 18.8 OOIP, m3 2,169,000

Oil Characteristics API Gravity 21 Viscosity, cp 30

The Loma Alta Sur structure is a north-northeast to south-southwest anticline approximately 3.5 km in length by 1 km in width with dipping flanks of 20° to 25° where the presence of inverse faults has been detected (Figure 4).

Width varies from 150 m to 900 m in the most developed and continuous channel deposits. Generally, the connectivity and areal development of the upper sand sequences is better defined than the lower layers. The fluid distributions and drainage systems within the facies are influenced by structural as well as stratigraphic control. Primary porosity is due primarily to calcareous cement dissolution, which is responsible for the abundant amount of fines found in the pore throats. LOMA ALTA SUR FIELD CDG PILOT AREA The CDG pilot was implemented in the LAS-58 injector, an irregular pattern shown in Figure 4. Water injection began in 2002 followed by rapid water breakthrough due to the combined effects of reservoir heterogeneity and 30 cp oil at reservoir conditions. The LAS-58 pattern includes ten producing wells, six “first line” producers and four “second line” producers. The reservoir rock and fluid characteristics are summarized in Table 1.

CDG’s were implemented in two phases in the LAS-58 pattern. In Phase I, 186,000 barrels of CDG were injected during the period July 14, 2005--February 2, 2006. Phase II included 192,200 barrels of CDG from April 11--October 31, 2007. These CDG volumes represent 1.45% pore volume and 1.50% pore volume during Phase I and Phase II, repectively. The total CDG volume injected in Phases I and II, therefore, was 2.96% of the LAS-58 pattern pore volume. This is a very modest volume by industry standards (Braun and DeBons 1995; Chang et. al. 2004a).

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FIGURE 5

FIGURE 6a

FIGURE 6b

FIGURE 7

DIAGNOSTICS Injection Profiles Repeated injection surveys demonstrate the inefficient distribution of injected water in the LAS-58 injector. A typical vertical profile is shown in Figure 5. In this example, the three most permeable layers are receiving approximately 90% of the injected water and several layers are not being contacted by water. Correlation of hydrocarbon intervals The operator conducted a series of geological, reservoir engineering and tracer surveys to correlate the Grupo Neuquén Formation layers within the LAS-58 pattern. Those studies confirmed that there was excellent connectivity between the LAS-58 injection well and the associated first line producing wells (Figure 6a and 6b).

Quantification of Heterogeneity Core analysis of producing well LAS-72 (Figure 7) indicated a Dykstra-Parsons coefficient (Dykstra and Parsons 1950) of 0.89. A single core study is not necessarily representative of reservoir heterogeneity; however, the results of the LAS-72 core evaluation were consistent with the injection profiles and oil/water production behavior in the LAS-58 pattern. The operator estimates that after three years of water injection the LAS-58 pattern, cumulative secondary oil recovery is only 5.48% of original oil in place (OOIP).

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FIGURE 8. Pre-Phase I CDG. Fractional daily tracer recovery (Fdtr), by well.

FIGURE 9. Pre-Phase I CDG. Fractional accumulated tracer recoved (Fatr), by well.

Tracers Tracer velocity is proportional to the permeability and thickness of the reservoir flow paths. The permeability controls the “time of flight” of the tracer particles between the injector-producer and the “permeability-thickness” product controls the “mass flow rate” of the tracer (assuming a constant pressure drop). Interwell tracer tests can be utilized in quantifying water channeling through the analysis of two tracer variables:

1. Times of flight distribution (or the first moment of the distribution) 2. Tracer mass produced (rate and cumulative production)

In addition to quantifying pre-CDG water channeling in the LAS-58 pattern, tracers were utilized to analyze the post CDG “times of flight” and the “tracer mass recovered”. Due to the possible differences in the flow conditions between the pre-CDG and post CDG tests, the tracer results are expressed in terms of the fractional daily tracer recovery (Fdtr) and the fractional accumulated tracer recovered (Fatr). These variables are defined as: where: mtracer-inj = tracer mass injected T = time Ctracer-sample = measured concentration in a producer Δmtracer-rec = tracer mass recovered in the time Δ qwater-producer = water flow rate of the producer Interwell Tracers, Injection Well LAS-58 The first tracer test was begun in March 2003, three months after initial water injection in the LAS-58 injector. The tracers were “bullheaded” simultaneously in the three injection mandrels. The most rapid tracer responses were observed in offset producers LAS-18 and LAS-49 (Figures 8 and 9).

injtracer

producerwatersampletracerrectracer

injtracer mqC

tm

mFdtr

−

−−−

−

=Δ

Δ=

.1

∫ −−−

=t

producerwatersampletracerinjtracer

dtqCm

Fatr0

.1

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FIGURE 10. LAS-49: Post-Phase I CDG. Fractional daily tracer recovery (Fdtr), by mandril.

FIGURE 11. LAS-49: Post-Phase I CDG. Fractional accumulated tracer recovered (Fatr), by mandril.

A second tracer campaign was begun on June 14, 2006, approximately 4 ½ months after the Phase I CDG (July 14, 2005—February 2, 2006). However, in this test, different tracers were injected in each of the three mandrels of injector LAS-58: Ammonium thiocyanate in mandrel 1 (lower layers), tritiated water in mandrel 2 (middle layers) and Yellow Acid 73 in mandrel 3 (upper layers). Relatively rapid tracer breakthrough was observed in only two offset producers: LAS-18 and LAS-49. The tracer response in each of these wells was similar, so only the results for producing well LAS-49 are presented in Figure 10 and Figure 11, which indicate the fractional recovery of each of the three tracers by mandrel. A review of the post-CDG oil response for the LAS-49 (see “CDG Results”) does not corroborate the apparent post-CDG water channeling implied by Figures 10 and 11. Several possible explanations exist. First, CDG injection was restarted after this tracer study (CDG Phase II, April 11—October 31, 2007). Tracers subsequent to October 2007 may show that very different results from Figures 10 and 11. Secondly, the thief zones indicated by the post Phase I CDG are believed to be direct, small volume channels. The fluid production from a small volume channel in a single layer would be insignificant as a percentage of the total well production. Finally, the well production data is based on periodic well production, which tends to mask production fluctuations. It should be noted that the total tracer recovery in Figures 10 and 11 was 4.6% of the total tracer volume injected in all three mandrels, compared to 4% total recovery of the pre-CDG tracer. The operator speculates that in the absence of the Phase I CDG pilot, the 2006 tracers would have indicated much more pronounced water channeling.

BRIEF HISTORY OF COLLOIDAL DISPERSION GEL DEVELOPMENT In the 1970’s and 1980’s, Phillips Petroleum investigated several processes that combined polyacrylamide polymer with multivalent cations (Needham et. al. 1974). The strategy was to increase the polymer adsorption in the reservoir, resulting in higher residual resistance factors (RRF) compared to traditional polymer flooding. RRF is defined as the ratio of brine mobility before contact with the chemical solution to brine mobility after the chemical injection. Increasing the post flood RRF, therefore, should improve volumetric sweep efficiency. Phillips reported successful field applications in Oklahoma (Zornes 1986), injecting the polymer and metal ion solutions in sequential slugs. However, interest in IOR waned after 1985 due to an unfavorable oil price environment. During the period 1985-1994, the Phillips process was modified. Instead of injecting the polymer and multivalent ion solution in slugs, the polymer and crosslinking agent were mixed on the surface and injected as a gelant (pre-gel) with encouraging results (Mack 1994; Fielding et. al. 1994; Nicol 1996). The majority of these initial “colloidal dispersion gel” or “CDG” applications were applied shortly after waterflooding was initiated, leading some to question if the CDG technology would be effective in mature, high WOR reservoirs. Recently, economically successful CDG applications have been reported in China’s giant Daqing field, in a pilot area with an average watercut of 96% prior to CDG injection (Chang 2004b). Laboratory experiments in the Daqing field demonstrated that the behavior of the CDG’s in

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FIGURE 12.

core floods was consistent with the reported field results (Smith 2000). CDG’s have compared favorably to uncrosslinked polymer in the Daqing field (Chang 2006). However, the CDG technology continues to be critically evaluated in isolated instances (Seright 2006). Colloidal dispersion gels (CDG’s) are so named from the nature of the gel solutions, which are suspensions of individual bundles of crosslinked polymer molecules, or colloids. A solution of separate gel “bundles” are formed in which a mixture of predominantly intramolecular and minimal intermolecular crosslinking reactions. By contrast, in “bulk gels” the crosslinking mechanisms form a continuous intermolecular network of polymer molecules. Figure 12 illustrates the difference in types of crosslinking reactions. The traditional CDG crosslinking agent is aliminum. However, in the Loma Alta Sur field, trivalent chromium was the multivalent ion that was applied in the field. Chromium (III) gels have a long and successful history in gel applications (Sydansk 1998), but at minimum polyacrylamide polymer concentrations of 0.3% (3000 ppm), forming a three dimensional molecular network termed “bulk gel”. The unique feature of the Loma Alta Sur CDG pilot is the use of chromium triacetate at polymer concentrations of 0.03% to 0.06% (300-600 ppm). Because of the relatively low polymer and crosslinker concentrations, the gel formation rate is slow, on the order of days and weeks for gel solutions stored in the laboratory. During injection in field projects, CDG formation appears to take longer than laboratory tests indicate. Large volumes of gelant are injected over time frames of weeks and months, with slow pressure development at the injection well, suggesting slow, gradual development of gelant. Research has shown that gels tend to show significantly delayed formation when in a high shear regime, and it is theorized that this phenomena accounts in part for more delayed gel formation in the lab than the field. Once the CDG forms in the formation, it is more resistant to flow than uncrosslinked polymer. It also adsorbs more strongly in the formation, and provides several times the residual resistance factors of uncrosslinked polymer. The enhanced properties of CDG’s over uncrosslinked polymer are particularly useful in heterogeneous formations, where non-uniform rock results in an uneven flood front and incomplete volumetric sweep. In this type of rock, uncrosslinked polymer is not strong enough to overcome these adverse effects. DESIGN AND IMPLEMENTATION OF THE CDG TREATMENT Shear A common concern when contemplating the use of gels is the potential effect of shear. Shear is the mechanical degradation which occurs as the flow of the polymer or the gelant is severely restricted as the solution passes through points of restricted flow. The term gelant refers to the “pre-gel” mixture of polymer and crosslinking agent which is injected at the wellhead. The chemical reaction to covert a gelant to a gel is a function of time and temperature. Valves, abrupt curvatures in the surface piping and particularly the perforations are examples of stress points where shear can occur. However a number of variables must be known or estimated with reasonable accuracy in order to accurately predict shear effects. Smith (1994) presented data showing significant discrepancies between the projected shear effects, based on generally accepted methodologies for estimating shear rates in the laboratory, versus 57 actual field projects. That is, the field results were much more positive than would be expected based on the calculated shear effect. The field projects in the study included both low polymer and low concentration gel applications (<500 ppm polymer). The shear effect on gel formulations is also minimal at higher polymer concentrations. Studies indicate that the effect of shear on medium molecular weight partially hydrolyzed polyacrylamide polymer crosslinked with chromium triacetate is a delay in the gelation time. Following a rest period of less than 24 hours, the sheared gels exhibit approximately the same yield stress as unsheared gelants. The research concluded that shortly after entering a low shear environment in the reservoir, the chemical bond between the polyacrylamide polymer carboxyl groups and the chromium ion re-form with no significant loss in gel strength after shear (Broseta 2000).

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FIGURE 13

Zone isolation Most hydrocarbon reservoirs are composed of a series of layers, with each layer representing a distinct period of geologic time with a unique depositional environment and type of minerals. In fact, stratification exists even when there is no direct evidence of vertical separation. That is, even individual layers almost always include flowpaths of varying porosity and permeability due to microscopic permeability distribution. Consequently, low volumetric sweep efficiency occurs due to the petrophysical characteristics between different layers as well as permeability anomalies within each layer. In Argentina, selective injection mandrels are frequently used in order to distribute injected water more uniformly between layers. If the layers were homogeneous, this technique would result in high vertical sweep efficiency, particularly in reservoirs with favorable mobility ratios. However, most reservoirs exhibit large permeability variations even within individual layers. Seright (1988) asserts that zone isolation is necessary for gel treatments in unfractured reservoirs that exhibit radial flow. In practice almost all gel treatments have been bullheaded, indicating that (1) virtually all reservoirs are fractured, or contain high permeability anomalies with fracture-like behavior, or; (2) significant permeability heterogeneity exists within individual layers. The authors believe that both conditions frequently exist in waterfloods. Recent field experience (Romero 2003; Norman 2006) where gels bullheaded in reservoirs with no known natural fractures indicates that gelant solutions behave like water during injection, with preferential injectivity in the highest permeability layers. Sydansk (2006, 2007) postulates that most, if not all reservoirs characterized as matrix rock are in fact fractured due to injection above fracture pressure, undetected micro-fractures and/or extremely high permeability anomalies that exhibit fracture like behavior. Such reservoir heterogeneities, difficult to quantify at a macroscopic level, offer a credible hypothesis for the mechanism of colloidal dispersion gel propagation in the reservoir. Reservoir engineering principles introduced in the mid 20th century demonstrate that, in the absence of free gas and natural fractures, the fraction of total water injection entering each zone will be proportional to the flow capacity of that zone (kh, the permeability thickness product). These mathematical models have been proven empirically in hundreds of waterfloods. Finally, studies have shown that polymer molecules cannot physically enter low permeability rock (Zaitoun, A. and Kohler N. 1987). Due to the addition of a crosslinking agent a gel molecule is significantly larger than a polymer molecule. Gel injectivity includes several variables, including polymer molecular weight, crosslinker effects and shear rate, to name a few. Therefore, the lower permeability limit below which gel cannot be injected is reservoir specific and difficult to quantify. CDG RESULTS Production Logs Phase II of the CDG pilot was completed in October 2007. Therefore, the results presented in the following paragraphs are attributable only to Phase I, which included 1.45% pore volume of CDG. The operator ran a production logs before and after the Phase I CDG treatment. Figure 13 indicates a positive variation in the vertical profile. Injectivity was reduced in the primarly thief zone (mandrel 3) and increased in mandrels 1 and 2. Several layers (A170a, B120-B120a and B150-B150a) had no injectivity prior to the CDG pilot.

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FIGURE 14

FIGURE 15

FIGURE 16

OIL PRODUCTION RESPONSE Total LAS-58 Pattern Figure 14 is a time-rate production history for the 10 offset producing wells in the LAS-58 pattern through October 2007. The trend before the injection of CDG begins to stabilize in November 2005, approximately 3 months after the Phase I CDG pilot began. The succeeding months show a clear oil response that continues as of the writing of this paper. The operator has quantified incremental oil production of 21,194 m3 (133,292 Bbls) and a reduction in water reduction of 64,710 m3 (406,949 Bbls) as October of 2007. Figure 15 demonstrates the change in the post Phase I CDG campaign. Figure 16 shows the increase in the efficiency of injected water after Phase I. No significant workovers were performed on the LAS-58 injector or any of the offset producing wells during the CDG injection (Phases I and II). Also, no new wells were drilled in the LAS-58 drainage area. No polymer breakthrough was noted at any time during the Phase I or Phase II CDG injection.

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Individual producing well response in the LAS-58 Pattern A well by well analysis revealed that the oil response is not uniform among the producing wells, which is typical in almost all chemical floods. Certain wells did not show any significant oil response; however, none of the offset producers saw a decline rate that was more pronounced that the pre CDG trend. Figures 17, 18, 19 and 20 are the time-rate graphs that are representative of the range of oil response seen among all ten offset producing wells.

Figure 18

Figure 17

Figure 20

Figure 19

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FIGURE 21

TABLE 2

LAS-58 Pattern (Volumetric Parameters) OOIP (m3) 2,169,000 Actual Incremental Oil Recovery as of October 2007 (m3) 21,194

Projected Ultimate Incremental Oil Recovery (m3) as of October 2007 62,000

Projected Incremental Recovery Factor (%OOIP) 2.9

Water-Oil Ratio Trend Figure 21 shows the WOR vs Np graphs for the 10 offset wells to injector LAS-58. The WOR trend before the Phase I CDG was projected to an economic limit (WOR of 50). Based on a parallel trend line projected from the latest data point to the same economic limit, the operator estimates total incremental oil of 62,000 m3 (389,968 Bbls). This represents the actual incremental oil production as of October 2007 and the projected oil production until the economic limit. The current evaluation represents 2.9% of the OOIP in the LAS-58 drainage area. This ultimate incremental oil realized is almost certain to increase with time, particularly due to the expected effect of the Phase II CDG pilot. Table 2 shows the actual and projected incremental oil recovery only for the CDG treatment. CONCLUSIONS

1. Colloidal Dispersion Gels (CDG’s) were applied in two Phases in a mature waterflood with an adverse mobility ratio. Results to date indicate a clear oil response from the Phase I pilot. The Phase II pilot, concluded in October 2007, is under evaluation.

2. No significant operational problems were encountered during the fourteen months of CDG injection (Phases I and II).

3. Based on incremental oil quantified as of October 2007 from the Phase I pilot, the cost per incremental barrel of oil is approximately $3.35. The ultimate cost per incremental barrel from the combined Phase I and Phase II CDG pilots is expected to be in the range of $2.00 to $3.00.

4. The operator is currently performing an updated reservoir characterization in order to implement a field-wide expansion of the CDG technology.

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REFERENCES Braun, R.W. and DeBons, F.E., “Polymer Flooding: Still A Viable IOR Tecnique”, 8th European IOR Symposium,

Vienna, Austria, May 15-17, 1995. Broseta, et. al., “Shear Effects on Polyacrylamide/Chromium (III) Acetate Gelation”, SPE Reservoir Evaluation &

Engineering, June 2000. Chang, H.L, et. al, “Successful Field Pilot of In-Depth Colloidal Dispersion Gel (CDG) Technology in Daqing Oil

Field”, SPE 89460, 2004. Chang, H.L., et. al., “Advances in Polymer Flooding and Alkaline/Surfactant/Polymer Processes as Developed and

Applied in the People’s Republic of China” Journal of Petroleum Technology, Jan. 2006, pp. 84-89. Chang, H.L., et. al., “Successful Field Pilot of In-Depth Colloidal Disperion Gel (CDG) Technology in Daqing Oil

Field” SPE 89460, 2004. Dykstra, H., and Parsons, R.L., The Prediction of Waterflood Performance with Variation in Permeability Profile,

Prod. Monthly (1950) Fielding, R.C., et. al., “In-Depth Fluid Diversion Using an Evolution of Colloidal Disperion Gels and New Bulk Gels:

An Operational Case History of North Rainbow Ranch Unit”, SPE 27773, 1994. Mack, J.C., et. al., “In-Depth Colloidal Dispersion Gels Improve Oil Recovery Efficiency” SPE 27780, 1994. Needham, R.B., et. al., “Control of Water Mobility Using Polymers and Multivalent Ions”, SPE 4747, 1974. Nicol, A.B., et. al., “The Adon Road-An In-Depth Gel Case History” SPE 35352, 1996. Norman, C. et. al., “A Review of Over 100 Polymer Gel Injection Well Confomance Treatments in Argentina and

Venezuela: Design, Field Implementation and Evaluation”, SPE 101781 (2006) Romero, C. et. al., “Non-Selective Placement of a Polymer Gel Treatment to Improve Water Injection Profile and

Sweep Efficiency in the Lagomar Field, Venezuela”, SPE 80201 (2003) Seright, R.S., “Placement of Gels to Modify Injection Profiles”, SPE 17332, 1988. Seright, R.S., “Are Colloidal Dispersion Gels Really a Viable Technology?”, http://baervan.nmt.edu/randy/ March

2006. Smith, J.E., et. al., “Laboratory Studies of In-Depth Colloidal Disperion Gel (CDG) Technology for Daqing Oil Field”

SPE 62610, 2000. Smith, J.E., “Closing the Lab-Field Gap: A Look at Near Wellbore Flow Regimes and Performance of 57 Field

Projects”, SPE 27774, 1994. Sydansk, R.D., et. al., “More Than 12 Years of Experience with a Successful Conformance-Control Polymer Gel

Technology”, SPE 59315, 1998 Sydansk, R.D., “Key & Controversial Issues Relating to Conformance Improvement”, Society of Petroleum Engineers

Advanced Technology Workshop, Comodoro Rivadavia, Argentina, November 2006. Sydansk, R.D., “New Conceptual Mechanisms for CDG’s”, unpublished presentation, Denver, Colorado, July, 2007. Uliana, M.A., and Legaretta, L., 1993. “Hydrocarbons Habitat In A Triassic-To-Cretaceous Sub-Andean Setting:

Neuquén Basin, Argentina”, Journal of Petroleum Geology, October 1993 Veiga, R. and Orchuela, I.A., 1989. “Identificación de niveles generadores de hidrocarburos a partir de técnicas de

perfilaje en la Formación Vaca Muerta”, Primer Congreso Nacional Exploración Hidrocarburos. 2, 1061-1093. Buenos Aires.

Zaitoun, A., Kohler, N., “The Role of Adsorption in Polymer Propagation Through Reservoir Rocks”, SPE 16274, 1987.

Zornes, D.L., et. al., “An Overview and Evaluation of the North Burbank Unit Block A Polymer Flood Project, Osage County, Oklahoma” SPE 14113, 1986

ACKNOWLEDGEMENTS: The authors thank the management of Repsol-YPF for the opportunity to present this paper. Also, we would like to acknowledge the assistance of the Malargue Area Operations and Development Groups as well as the consulting firm NCT of Maracaibo, Venezuela.

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NOMENCLATURE CDG = colloidal dispersion gel OOIP = original oil in place Cp = centipoises ppm = parts per million Ev = volumetric sweep efficiency RRF = residual resistance factor H = thickness Sor = residual oil saturation k = permeability Qinj = water injection rate, m3/day M = mobility ratio Qo = oil rate, m3/day m = meters Qw = water rate, m3/day m3 = cubic meters V = Dykstra-Parsons coefficient

Md = millidarcies VP = pore volume Np = cumulative oil production WOR = water oil ratio

CONVERSIONS

km2 × 1.00 E + 06 = m km × 1.00 E + 03 = m

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