Combining Bulk Gels and Colloidal Dispersion Gels for Improved Volumetric Sweep Efficiency in a Mature Waterflood

Transcription

1 Combining Bulk Gels and Colloidal Dispersion Gels for Improved Volumetric Sweep Efficiency in a Mature Waterflood Presented by: TIORCO, Inc. The Improved Oil Recovery Company

2 Combining Bulk Gels and Colloidal Dispersion Gels for Improved Volumetric Sweep Efficiency in a Mature Waterflood ABSTRACT The Golfo San Jorge (GSJ) is located in the southern Argentina provinces of Santa Cruz and Chubut. This hydrocarbon basin occupies a surface area of approximately 170,000 km 2, approximately 1/3 of which is offshore. Waterflood oil recovery in many GSJ reservoirs does not exceed 10% OOIP due to the combined effects of reservoir heterogeneity and, in many fields, an adverse mobility ratio. The most significant hydrocarbon accumulations of the basin occur in a series of fluvial and shallow lacustrine reservoirs with significant tuffaceous content. A typical GSJ hydrocarbon reservoir includes a series of relatively thin sandstone packages that are not believed to be naturally fractured. In an effort to distribute water injection more uniformly, most injection wells are equipped with injection mandrels. However, heterogeneity within the productive layers limits the effectiveness of near wellbore selective injection. A recent field pilot combining two types of gel technologies in the Comodoro Rivadavia Formation, one of the most prolific GSJ reservoirs, is encouraging. Based on tracer studies, historical production data and reservoir characterization, approximately 15,000 barrels of Marcit SM gels were injected in each of two adjacent injection wells. Seven months after the Marcit gel treatments, the operator began a colloidal dispersion gel (CDG) pilot in the same two patterns, injecting a total CDG pore volume of approximately 18% in certain layers of the Comodoro Rivadavia Formation. A chemical injection plant was connected at a point upstream of the two injectors so that both wells could be treated simultaneously, with the flexibility to vary the rate and polymer gel concentration in each well. A discussion of the reservoir characterization will be presented as well as the chemical treatment designs, subsequent modifications in the course of the pilot, and recommendations. INTRODUCTION Reservoir heterogeneity is the biggest challenge to oil recovery in waterfloods. Heterogenity is essentially any nonuniformity in the productive reservoir, including, but not limited to variablilty in permeability and porosity, anisotrophy, fractures, faults and compartmentalization. Anyone who has studied the classic theories of Buckley and Leverett (1942), Stiles (1949), and Dyktra-Parsons (1950) among others appreciates the dramatic effect of heterogeneity on ultimate oil recovery. In the GSJ of Argentina, injection wells are typically completed with downhole selective injection installations (mandrels) designed to improve vertical distribution of water injection. However, near wellbore mechanical configurations do not address in-depth reservoir heterogeneities. Polymer gels are designed to reduce the effects of reservoir heterogeneity beyond the near wellbore area. The basic premise of any gel technology is that the pre-gel solution, or gelant, will preferentially enter high permeability anomalies responsible for low volumetric sweep efficiency. The theory is that once the gels reduce the flow capacity in the thief zones, areal and vertical sweep efficiency will be improved. This project describes the pilot area evaluation, gel design and field implementation of two polymer gel technologies: Marcit gels (Sydansk 1938) and colloidal dispersion gels (CDG) (Mack 1994). Marcit gels are high polymer concentration gels designed for application in reservoirs with extreme heterogeneities such as natural or induced fractures, fissures and other multi-darcy permeability anomalies. CDG s are typically large volume, low polymer concentration gels designed to improve sweep efficiency in unfractured matrix reservoirs that exhibit poor waterflood performance. Many waterfloods exhibit both types of heterogeneities.

3 2 THE SAN JORGE GULF OF ARGENTINA The Golfo San Jorge (GSJ) basin (Figure 1) is located in the southern Argentina provinces of Santa Cruz and Chubut. This is the most prolific basin in Argentina, having produced over 3 billion barrels of oil and approximately 3 TCF of gas since the initial discoveries in More than 26,000 wells have been drilled in the GSJ basin. However, secondary oil recovery is challenging due to the combined effects of reservoir heterogeneity and, in many fields, an adverse mobility ratio. The most significant hydrocarbon accumulations of the basin occur in a series of fluvial and shallow lacustrine reservoirs. During the Tertiary, the basin developed a series of alternating marine and continental deposits. The Quaternary deposits represent drastic climatic changes, such as glaciations and accompanying fall in sea level. Volcanic activity FIGURE 1 throughout the history of the basin is expressed in the high tuffaceous content of the entire column, affecting the quality of the reservoirs. Hydrocarbon generation and expulsion is thought to have begun million years ago. After migrating through a network of faults and pathways, the oil accumulated in both extensional and compressional stratigraphic traps (Sylwan 2001). The majority of the oil and gas reserves in the GSJ are located in three Cretaceous formations: El Trebol, Comodoro Rivadavia and Mina El Carmen. The top of Figure 1 indicates the relative location of several important oil fields along the north-south axis of the basin, showing the central location of the El Tordillo Field. THE EL TORDILLO FIELD The El Tordillo Field, discovered in 1932, was operated by YPF (the Argentina national oil company) from 1932 until In 1991, the Consortium El Tordillo, in which Tecpetrol is the operator, assumed operations. The field is situated on the north flank of the San Jorge Basin in the Province of Chubut (Figure 2). The field is approximately 50 kilometers southwest of the city of Comodoro Rivadavia. More than 1200 wells have been drilled in the 117 km2 field. The Comodoro Rivadavia formation, a normally faulted fluvially dominated sandstone, is the most important hydrocarbon reservoir in the El Tordillo Field, and was the objective of the polymer gel conformance pilot. FIGURE 2

4 3 GEL PILOT AREA The pilot area consists of two adjacent patterns, I-1 and I-2 (Figure 3). Selected data relevant to the evaluation of these patterns as gel candidates is shown in Table 1. The gel pilot was restricted to the Comodoro Rivadavia Formation. TABLE 1 PATTERN I-1 I-2 Area, acres Average Depth*, meters Reservoir Temp, ºC Oil Viscosity, cp Sor, % Layers, Cmd Riv. Fm. 4 5 Oil Recovery**, % OOIP FIGURE 3 * Comodoro Rivadavia Formation ** Primary + Secondary, Cumulative to Jan PRE-MARCIT GEL DIAGNOSTICS Core Studies The operator has performed numerous core evaluations of the Comodoro Rivadavia Formation. Figure 4 shows the results of a Dykstra-Parsons (Dykstra and Parsons 1950) permeability ordering for a typical rock sample. In this case, the calculated Dykstra-Parsons coefficient of 0.80 indicates a high degree of vertical heterogeneity. The inset graph of depth (m) vs. permeability, visually illustrates the nonuniform water injection distribution which has been confirmed by logs (Figure 5). FIGURE 4 FIGURE 5

5 4 Conceptualization of Heterogenity Effect To illustrate the effect of the degree of reservoir heterogeneity in the pilot area, the operator prepared a conceptual simulation of an inverted five spot 30-acre pattern with ten equal thickness layers using real permeability values from the Comodoro Rivadavia Formation cores. Figure 6 incorporates these assumptions in a graph of flow capacity vs. thickness. The model demonstates that 25% of the injected water is entering in only 7% of the total thickness. Intuitively, we understand the consequences of reservoir heterogeneity, but simple calculations help us visualize how dramatic the effects can be for even a moderately heterogeneous reservoir. FIGURE 6 Production Data Analysis Historical production data indicated water channeling in both patterns. Water/oil ratio vs. Np graphs for two of the offset producing wells, P-3 and P-6, illustrate typical water/oil ratio vs. Np behavior (Figures 7a and 7b). All data is prior to the Marcit gel treatments. Note that within a few months after the water breakthrough, the water/oil ratio continues to increase in a step function manner. The erratic behavior of the water/oil ratio curves reflect water breakthrough in different layers of the Comodoro Rivadavia Formation and well workovers. However, the trend over time is clear. FIGURE 7a FIGURE 7b Chemical Tracers In May of 2005 chemical tracers were injected in each injector in two layers of the Comodoro Rivadavia Formation: CR and CR As expected, the tracers appeared rapidly in several of the offset producers. Figures 8a and 8b show the tracer results for the same producing wells described above, P-3 and P6. In January 2006, two months after the Marcit gel treatments, a second tracer survey was performed in order to determine if the Marcit gels had in fact been placed in the thief zones identified by the previous tracer study. The results of the post-marcit gel tracers are shown by the red trend lines in Figure 8a and Figure 8b, confirming that permeability reduction in the high velocity zones. This point will be discussed in more detail in the following paragraphs.

6 5 FIGURE 8a FIGURE 8b Estimated Volumetric Sweep Efficiency Using historical production data and petrophysical data, the operator calculated the estimated volumetric sweep efficiency (Ev) in the pilot area. This exercise (Figure 9) resulted in a calculated Ev of slightly above 30%, which is consistent with the diagnostics above and corroborated the potential to accelerate and increase the oil reserves if the gel treatments were successful. As a point of reference, the median Ev for an average performing waterflood has been estimated to be in the range of 60% (World Oil). In summary, the gel treatment diagnostics included several complementary data sources, each of which corroborated the effect of reservoir heterogeneity and the improved oil recovery FIGURE 9 potential: Core data Simulation/conceptualization Historical production data Chemical tracers Petrophysical data MARCIT GEL TREATMENTS Laboratory evaluation In August 2005, laboratory evaluations were performed using El Tordillo injection water. Gels were evaluated at 85 C with polymer concentrations from 1500 to 9000 ppm. Several crosslinker concentrations were evaluated to optimize the Marcit gel designs prior to field implementation. Field Implementation In November 2005, 15,000 barrels and 12,000 barrels of Marcit gels were injected in injectors I-1 and I-2, respectively. The gel volumes were based on a percentage of the estimated volume of the thief zones as calculated from production history data, reservoir characterization and chemical tracer data. Both treatments were bullheaded into 4-5 layers of the Comodoro Rivadavia formation. In each of the injection wells, the Marcit gels treatments were started on a vacuum (no surface pressure) which was yet another indication of the reservoir heterogeneities. The gel treatments were injected below the formation fracture pressure at polymer concentrations ranging from 1500 ppm to 4000 ppm. During the Marcit gel treatments, polymer breakthrough was detected at one of the producing wells. That well was then shut in for the duration of the Marcit treatments.

7 6 COLLOIDAL DISPERSION GELS Laboratory evaluation Prior to starting the CDG project in July 2006, a series of laboratory evaluations were performed to optimize the chemical design in the field. The field injection water has approximately 7000 ppm total dissolved solids (TDS), consisting primarily of Na, Ca and Cl ions. This water chemistry is ideal for gel formulation. CDG s with polymer concentrations ranging from 300 to 1800 ppm were evaluated with polymer to crosslinker ratios from 20:1 to 40:1. CDG strength and stability was quantified using a Transition Gel Unit (TGU) (Smith 1989) apparatus. Transition Pressure is proportional to the strength of the gel and is used to compare gels quantitatively. A transition pressure was observed after 24 hours at a polymer concentration of 900 ppm, but the gels degraded after one week at the reservoir temperature of 87 C. It is believed that small concentrations of oxygen that remained in the gel samples and generated free-radicals. Oxygen concentrations as low as 1 ppm are sufficient to adversely affect gels. If the hypothesis is correct, the free radicals destroyed the polymer chains when reacting with impurities in the water. Oxygen is not a concern in the field since the reservoir is a reducing environment. Any oxygen in the gelant is quickly neutralized after entering the reservoir (Martin 1974). However, this condition is very difficult to replicate in a laboratory. The next step was to evaluate the water treating chemicals in the injection water. Gels were formulated in synthetic water using the field concentrations of each individual treating chemical as well as a combination of all treating chemicals. The gel samples were stable even after one month at reservoir temperature. Therefore, treating chemicals were ruled out as the cause of gel degradation. It was hypothesized that dissolved oil and/or phosphonates could be causing gel degradation in the injection water. Further lab analysis indicated that the oil and phosphonate concentrations were 0.4 and 0.09 ppm respectively, which are believed to be too low to affect the gels. Finally, attention was directed to the hypothesis that the CDG s dehydrate as they pass through porous media, resulting in a significantly higher gel concentration in the reservoir compared to the injected concentrations. This hypothesis was confirmed in a series of tests injecting 600 ppm CDG s through 3.0 μ and 8.0 μ millipore paper filters. More research is needed, but it appears that dehydration (leakoff) of water from the gelant may result in the formation of CDG s in reservoir conditions that cannot be detected by conventional laboratory analysis. Injection Water Quality Injection water quality was monitored continuously during the CDG pilot. Routine chemical analyses were performed on a periodic basis to monitor the consistency of the water chemistry. An equally important objective was to quantify the concentration of solids and oil carryover in the injection water. The chemical injection plant was equipped with 40 micron filters. Howerver, during the course of the ten month CDG pilot, operational problems in the water injection plant resulting in higher than normal levels of solid and oil that could be effectively filtered in the field. As a result, face plugging occurred on a few isolated occasions when the oil and solids were encapsulated by the gelant. This was remedied by circulating a small volume solvent treatment to remove the skin. CDG injection was then resumed. Field Implementation A portable chemical injection unit was placed at the distributor in order to perform both CDG treatments simultaneously. A mother gel solution of 1000 barrels/day was prepared in the chemical injection unit which was diluted at the distributor with injection water in order to arrive at the desired CDG concentration and injection rate (Figure 10). Note that in this case the distributor served four injection wells, of which only two wells were treated with CDG s. However, all four wells could have been treated simultaneously. CDG injection began on July 1, 2006 and was completed in April 30, Periodic logs were run in order to determine the distribution of the CDG s in each of the injectors I-1 and I-2. Figures 11a and 11b also indicate the location of the injection mandrels in relation to the various layers of the Comodoro Rivadavia Formation. As expected, there was some variation over time in the relative injectivity of the CDG s. The profiles for injection well I-1 are consistent with the operator s evaluation of each injection well. For example, well tests in injector I-1 have confirmed that layer Cr29-50 has the highest average permeability. Layers Cr29-30, Cr28-20, Cr28-30 and Cr28-40 also include high permeability zones, as evidenced by Figure 11A. The profiles for injector I-2 also corroborate the operator s experience that the primary thief zones are located in layers Cr28-40 and Cr29-20 in that injection well (Figure 11b).

8 7 During the course of the project, the crosslinker was briefly suspended in order to maintain the injection pressure below formation parting pressure. On each occasion, the injection pressure immediately stabilized and began to slowly decline, confirming that a chemical reaction was in fact occurring between the polymer and crosslinking agent (i.e., gel formation). The cumulative CDG injected volume (% pore volume) for injectors I-1 and I-2 are summarized in Figures 12a and 12b, respectively. The interpretation of this data is that although the primary water channeling is focused in one or two layers, permeability variation occurs in all layers. Some researchers have used simplistic multi-layer models and homogeneous cores to simulate gel placement in FIGURE 10 unfractured reservoirs, with the implicit assumption that permeability and fluid saturations in each layer are uniform (Seright 1988; Sorbie 1992). Core samples are typically one inch in diameter, three inches long, and homogeneous. As noted by Christiansen (Christiansen 2001), extrapolating results from core samples to a reservoir scale is an unresolved topic of current investigation by engineers around the world. FIGURE 11a FIGURE 11b FIGURE 12a FIGURE 12b

9 8 Other Operational Issues All offset producing wells were tested for polymer breakthrough several times a week. There was no polymer detected at any of the producing wells during the course of the CDG treatments. TABLE 2 Water Distribution, Injector I-1 LAYER PRE-GEL POST-GEL CR CR CR CR CR Total m 3 /day The operator did not experience any difficulties injecting water in any of the layers following the CDG treatments, confirming that the CDG s did not plug the lower permeability reservoir rock (Table 2). The objective in this pilot is to improve the sweep efficiency within each layer through in depth placement of gels. On the other hand, if the goal is to change the vertical distribution of water among the layers, a reconfiguration of the injection mandrels would be the preferred option. RESULTS Based on well tests every one to two weeks, the operator monitored oil and water production in each of the ten offset producing wells. Two additional producers in the vicinity of the first line of producing wells also showed a positive response. As expected, the oil response in each of the producing wells was not uniform in timing or magnitude. No new producing wells were drilled in the vicinity of the I-1 and I-2 patterns and no workovers were performed on neighboring injection wells. As mentioned above, the Marcit gel treatments were performed in November of The CDG treatments were begun on July 1, 2006 and continued through April 30, Four representative producing wells are discussed in more detail below. Figures are the same graphs used by the operator to monitor the project. Note that all production data is in cubic meters. Producing Well P-3 (Figures 13a, 13b): Oil production after the Marcit gels increased from 2.8 m 3 /d to 10.5 m 3 /d in less than 30 days. The interpretation is that the filling of the fracture or high permeability anamoly produced a pistonlike displacement immediately after the Marcit gel treatments, resulting in a rapid and and very pronounced oil response. A steady decline in oil production is noted for the next 12 months, as water channeling returns due to the combined effects of heterogeneity in rock not contacted by the Marcit gels and the adverse mobility ratio. Approximately five months after starting the CDG s, oil production begins to stabilize. Over the twelve month period from December 2006 to December 2007, oil production has more than doubled, from 3.1 m 3 /d to 7.5 m 3 /d. Figure 13b shows the water/oil ratio response during the same period, indicating the oil production increases were not accompanied by an equal increase in water production. FIGURE 13a FIGURE 13b

10 9 Producing Well P-4 (Figures 14a, 14b): Drilled in August 2005, the well shows an exponential decline typical for this part of the field. Oil production stablizes and increases after the Marcit gel, accompanied by a gradual increase in water/oil ratio. A positive change in the oil production trend is seen beginning in December 2006, five months after beginning the CDG s. A pump change is performed in May Therefore, no incremental oil from the gel treatments is attributed to this well after May FIGURE 14a FIGURE 14b Producing Well P-5 (Figures 15a, 15b): A positive oil response is noted within six weeks after the Marcit treatment. During the eight month period beginning in January 2006, oil production increases over 20%, peaking at 17.5 m 3 /d in August Typical production decline is noted from August 2006 through May 2007 (except for a brief spike in oil production in February-March). Over the next seven months, oil production increases over 50%, from 9.9 m3/d in May 2007 to 15.6 m 3 /d in December The water/oil ratio graph corroborates the argument that the oil increases are due to the gel treatments. Except for timing differences, the P-3 and P-5 responses are similar. FIGURE 15a FIGURE 15b Producing Well P-10 (Figures 16a, 16b): Oil production increases dramatically in January 2007, two months after the Marcit gel treatment; however, this could be a measurement error. A consistent positive trend is noted beginning in July 2007, with oil production more than doubling from 3.9 m 3 /day in late May 2006 to a peak of 8.4 m 3 /d in mid February The water/oil ratio graph confirms effects of the gel treatments. From July 2007 to December 2007, the water/oil ratio declines from 5.2 m 3 /d to 1.2 m 3 /d in December 2007.

11 10 FIGURE 16a FIGURE 16b Tracers As described above, chemical tracers before and after the Marcit gel treatments confirmed that the Marcit gels had effectively blocked the highest permeability thief zones. The reader is referred again to Figures 8a and 8b. Distinguishing the effect of the Marcit gels and the CDG s is an imprecise exercise. However, considering the production responses in all wells in the pilot patterns I-1/I-2 and comparisons with similar producing wells outside the pilot area, the operator estimates that the oil response due to the Marcit gels is minimal after mid A composite analysis of all producing wells in the pilot area is shown in Figures Figure 17 is a representation of actual oil production (m 3 /d) versus the projected oil production based on the exponential decline for similar production wells. From Figure 18, a composite graph of water/oil ratio versus cumulative oil production (Np), the operator estimates incremental oil reserves of approximately 50,000 m 3 in incremental oil reserves as of December Figures 17 and 18 include all ten first line producing wells and two second line producing wells that responded to the gels. The final incremental oil recovery will be determined as the project evaluation continues. The operator estimates that current incremental oil production is about 30 m 3 /day. Figure 19 shows the increase in water injection efficiency due to the gel treatments. The reader is advised that the composite graphs (Figures 17-19) include extended periods of production interruption due to normal mechanical problems with one or two producers. Removing these events would result in additional incremental reserves and an even more significant improvement in water injection efficiency. FIGURE 17 FIGURE 18

12 11 Post CDG Injection Rate A graph of the injection history in Injector I-1 reveals that the injection rate increased after the CDG pilot (Figure 19). However, the water/oil ratio graphs for the four representative producing wells demonstrate that the increased injection rate has not been accompanied by increased fluid production. In fact, the post CDG water/oil ratio s have, in general, decreased. The post-gel fluid production data, along with Figure 20, indicate that volumetric sweep efficiency has improved. In conclusion, post-gel water injection is more efficient. FIGURE 19 Economics Operators in the San Jorge Gulf of Argentina receive a net price that is about 45% of the average world oil price due to special taxes and adjustments for oil quality. This gel project is economically viable at the current net oil price in the San Jorge Gulf of Argentina, which is roughly equivalent to the January 2005 world spot oil prices (Energy Information Administration). Based on the incremental oil recovery quantified in Figure 18, the development cost as of December 2007 is about $4.00 per incremental barrel. FIGURE 20 CONCLUSIONS 1. The oil response from the Marcit gels has been more rapid, pronounced and and short-lived than the CDG s. This is expected due to the objectives and designs of each gel technology. 2. Although operational changes were kept to a minimum, certain well maintenance workovers were necessary. In those limited circumstances, none of the post-workover oil production was taken into account in the estimate of incremental oil due to the gel treatments. 3. Injection water quality is extremely important in order to maintain injectivity of gels. This is particularly true for longer term projects (CDG s). 4. Oil production responses in IOR projects are not always immediate and are frequently subtle. Detailed, continuous and rigorous post-treatment oil and water production monitoring is essential. The evaluation should include each well in the pilot area as well as second line producers. Workovers and other events must be carefully documented. Graphs of all production wells, injection volumes versus oil production and other composite analyses are useful to identify long term trends. 5. Based on this pilot project, twelve additional Marcit treatments were performed from May 2007 to January Another multiple well CDG project is planned for start-up in early 2008.

13 12 REFERENCES Buckley, S.E., and Leverett, M.C., Mechanism of Fluid Displacement in Sands, Trans., AIME (1942) Christiansen, R.L., Two Phase Flow Through Porous Media, Colorado School of Mines (2001) Dykstra, H., and Parsons, R.L., The Prediction of Oil Recovery by Waterflooding, Secondary Recovery of Oil in the United States, 2 nd ed., API (1950) Dykstra, H., and Parsons, R.L., The Prediction of Waterflood Performance with Variation in Permeability Profile, Prod. Monthly (1950) Editorial, Practical Waterflooding Shortcuts, World Oil (December 1966) Energy Information Administration, U.S Department of Energy, Mack, J.C., et. al., In-Depth Colloidal Dispersion Gels Improve Oil Recovery Efficiency, SPE (1994) Martin, F.D., Laboratory Investigations in the Use of Polymers in Low Permeability Reservoirs, SPE 5100 (1974) Seright, R.S., Placement of Gels to Modify Injection Profiles, SPE (1988) Smith, J.E., The Transition Gel Pressure: A Quick Method for Quantifying Polyacrylamide Gel Strength, SPE (1989) Stiles, W.E., Use of Permeability Distribution in Water Flood Calculations, Trans., AIME (1949) Sydansk, R.D., A Newly Developed Chromium (III) Gel Technology, SPE (1990) Sorbie, K.S., et. al., Gel Placement in Heterogeneous Systems with Crossflow, SPE (1992) Sylwan, C.A., Geology of the Golfo San Jorge Basin, Argentina, Journal of Iberian Geology, (2001) NOMENCLATURE CDG = colloidal dispersion gel Np = cumulative oil production Cp = centipoises OOIP = original oil in place Ev = volumetric sweep efficiency ppm = parts per million H = thickness RRF = residual resistance factor k = permeability Sor = residual oil saturation M = mobility ratio V = Dykstra-Parsons coefficient m = meters VP = pore volume m 3 = cubic meters WOR = water oil ratio Md = millidarcies CONVERSIONS km 2 km 1.00 E + 06 = m 1.00 E + 03 = m