SPE 23678 Reservoir Engineering Study of C02 Enhanced Oil Recovery for the Nipa 100 Field, Venezuela

In this application, water-alterning-gas (WAG) enhances oil recovery, not by controling effective C02 mobility, but by promoting simultaneous

waterflooding at the base while C02 miscible flooding the top of the formation.

Jaime Almeida, Carlos Espinoza, INTEVEP, S.A. Jose Mosquera, CORPOVEN, S.A.

Michael R. Todd, TCA INC. 1994 Society of Petroleum Engineers

SUMMARY The J2L interval in the NIP-I03 reservoir is comprised of a

thin, uniform, high permeability sandstone. Well spacing is about 120 acres/well in the miscible-flood target region. The well configuration is non uniform. Oil saturation in the miscible flood target area is expected to be near initial at the start of COz injection. These characteristic distinguish this application from the majority of existing miscible floods.

In order to study the interaction of the COz miscible flood process with the J2L reservoir characterization, a numerical simulation study was conducted. First, a set of one dimensional simulations was made in order to examine linear displacement features. Then, multi-dimensional pattern flood simulations were conducted. Finally, a numerical simu-lation of the J2L COz pilot project was undertaken. This part of the simulation work included the construction of a field model, calibration of the field model through history-matching previous field performance, and examination of the COz miscible flood process as it might be im-plemented in the J2L.

INTRODUCTION Natural gas being piped to the cryogenic plant at San Joaqufn

contains 5-6 % of COz. If separated from the natural gas stream, 40-50 MMscf/d of COz could be made available as a solvent for oil recovery. Consequently, a feasibility study was initiated in order to evaluate the potential for enhanced oil recovery (EOR) by means of COz injection. The initial aim of the feasibility study was to determine reservoirs, in the vicinity of the pipeline, amenable to COz enhanced oil recovery. Rivas et al 1 developed a methodology to rank more than 600 reservoirs in terms of their suitability for COz flooding. A priority list was created and one reservoir was selected for further investigation. This reservoir exhibited good technical properties based on the preliminary screening, and is small enough to be used for short-lived EOR pilot.

The J2L sand in the NIP-103 reservoir has qualities substantially different from those of the giant West Texas COz miscible floods. The reservoir is a sandstone with both high horizontal and vertical perme ability. Thus, where the West Texas dolomite COz floods are viscous dominated and vertical conformance is determined by stratification, here the displacement is gravity dominated and vertical conformance is de-termined by gravity tonging. As consequence, WAG processes act in an unexpected manner. Further, as the reservoir exhibits water-wet character, waterblocking of oil from the COz solvent appears to be an important factor.

The COz flood, planned for the NIP-I03, will be the first non-thermal enhanced oil recovery project conducted in Venezuela. Sim-ulations suggest that viability of process can be estimated based on observed project performance over the first 2 or 3 years. If successful, 86

the availability of COz solvent would make this project the forerunner of significant COz EOR recovery in Venezuela.

RESERVOIR DESCRIPTION NIP-I03 reservoir is located in the Greater Oficina area near San

Joaquin in Eastern Venezuela. It was discovered in late 1957, with the majority of the development occurring in 1958. Wells produce at depth ranging from 8280 to 8480 ft. The reservoir is limited by an oiVwater contact at 7725 ft subsea in the north and by permeability pinchout in the southern part of the field. The formation has an average thickness of 4.4 ft. Fig. 1 shows the map which refers to the top of the sandstone in question. A characteristic log is presented on Fig. 2, where the vertical stratification can clearly be seen.

The original reservoir pressure was 3420 psia, measured in well NV-I03, and the bubble point pressure of the oil was 2465 psia at 230 OF reservoir temperature. The reservoir oil volume formation factor, the dissolved gas/oil ratio and the viscosity of the oil was 1.42 RB/STB, 636 SCF/STB, 0.51 cP respectively, measured at initial reservoir conditions.

PRODUCTION HISTORY The production from this reservoir started in October 1957. Up

to the end of December 1990 2.7 MMSTB oil, 0.564 MMSTB water and 4.6 MMscf gas was produced, mainly from those wells which were drilled along the longitudinal axis of the reservoir, near the aquifer. To date the reservoir has been developed by drilling six wells as shown in Fig. 1. Wells NV -105 and NV -108 were shut down in the early life of the production history of the reservoir due to mechanical problems. In late 1964 the NV -103 well produced high water cut and was closed, with an accumulative 544 MSTB of oil. In 1971, the best producer well(NV-109), with accumulative 1.02 MMSTB of oil, was shut down due also to increase in water production. The reservoir was closed from 1972 to 1974, the production of this reservoir was reinitiated by recompleting the well NV-120. In 1981, the well NV-107 was also recompleted in this reservoir. Since 1981 the reservoir has been drained from those two wells at an average rate of 100 Bls/d of oil by well.

FLUIDS AND ROCK PROPERTIES A reservoir fluid sample was taken from the J2L sand and a PVT

analysis, including differential liberation experiment, was conducted. The results of this analysis were put in a compositional form as re-quired by the reservoir simulator. The reservoir hydrocarbon system is represented by two pseudo components; stock-tank oil (OIL) and sepa-rator gas (SGAS). Gas solubility is expressed in the simulator as the mol fraction of SGAS in the liquid hydrocarbon phase. The gas solubility (Rs) versus pressure curve which is determined by laboratory differential liberation experiment is expressed in the simulator as the correspond-ing kvalue versus pressure curve. The laboratory determined volume

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factor versus pressure curve is represented in the simulator by blend-ing of pseudo components OIL and SGAS, each having an effective molar volume and compressibility. Hydrocarbon phase density is de-termined in the simulator from the density of the stock-tank oil and the effective (mixture) molecular weight of the dissolved gas. Finally, the viscosity of the hydrocarbon phase is determined by blending the pseudo components, each having a component viscosity and viscosity pressure coefficient. Fig 3 shows the SGAS solubility curve determined in the differential liberation experiment, together with the corresponding k-value curve used by the simulator. Fig. 4 compares the experimental data with the model used in the simulator for the liquid hydrocarbon phase formation volume factor. Here it is noted that the J2L hydrocar-bon system is well represented by the two pseudo components.

Fig. 5 and 6 show the experimental and simulator model of the liquid hydrocarbon phase density and viscosity respectively. The properties of CCh and the solubility of CCh in water were taken from the data available in the literature 2. The miscibility pressure with CCh is approximately 3000 psia, as determined by laboratory experiments. Every attempt will be made during the CCh flood to keep the reservoir above the miscibility pressure. If we take 3500 psi as the average displacement pressure during the CCh flood, it will take 1.5 Mcf of CCh to create one barrel of solvent under reservoir conditions. Fig. 7 shows the water-oil relative permeability functions, krw(Sw) and krow(Sw). Fig. 8 shows the gas-liquid relative permeability' functions, krg(Sg) and krog(Sg). The residual oil saturation for miscible CCh displacement is taken as 0.05, representative of a number of CCh core floods.

Fig. 9 shows the model used in the simulator for the three phase oil relative permeability. This function was derived by connecting with straight lines equal values of oil relative permeability as observed on the krow and krog curves. It is believed that this formulation for the three phase curve is the least biased, given that actual measured three-phase data are not available 3. Fig. 10 shows the water-oil capillary pressure functions for two levels of permeability. Although these curves were determined for rock samples for the 13 sand, they are thought to be representative of the J2L sand as well.

Given the fluid properties and the saturation functions end-points, we can estimate the transport ratios that control the displacement..

TRANSPORT PROPERTIES

FLUIDS MOBILITY DENSITY RATIO CONTRAST

BRINE-OIL 0.67 12.7

CO2-OIL 12.65 16.5

CO2-BRINE 21.36 29.2

Further, the end-points from the saturation functions allow us to compute the maximum possible oil recovery as a function of original-oil-in-place (OOIP).

Er(max) = 0.675 OOIP for Waterflooding. Er(max) = 0.938 OOIP for CCh flooding. From the transport properties shown above we see that for a

waterflood (or continuation of the aquifer supported depletion in the J2L sand), the mobility ratio is favorable. However, the density contrast between the oil and the brine should cause the brine to attempt to underrun the oil column. However, as will be demonstrated later, the capillary pressure function largely prevents this underruning.

For CCh displacing oil, the mobility ratio is highly unfavorable as is characteristic of miscible flooding processes. However, the mobility ratio for our case is not as unfavorable as most of the West Texas floods,

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where the mobility ratio ranges from 20 to 40. Regardless, we must expect that unstable frontal advance (viscous fingering) will result from the unfavorable mobility ratio. The density contrast between the CCh and the oil will cause the CCh to attempt to override the oil column. Unfortunately, since there is no interfacial tension between the CCh and the oil under miscible conditions, there is no capillary pressure to prevent this overriding.

The mobility contrast between the CCh and the brine is only really important for Water Alternating Gas (WAG) processes. For a given specified WAG ratio, the mobility contrast between the CCh solvent and the injected brine determine the eqUilibrium brine and solvent saturations. This consideration has a strong influence on the predicted oil recovery performance and, consequently, on the selection of the optimal miscible flooding process.

Laboratory experiments have shown that the presence of water can affect the ability of a miscible solvent to contact and mobilize oil 4. Fig. 11 depicts this water-blocked oil as a function of the water saturation. It has been noted that the water-blocking phenomenon is a function of rock wetting conditions 5. Waterblocking appears significant in water wet cores, but appears to have much less significance in oil wet cores. The parameter alpha (Fig. 11) is introduced in the correlation to include the effect of different rock wetting conditions 6. A value for alpha of 1.0 reflects conditions of a highly water-wet sandstone. A value for alpha of 100 reflects a mixed to oil-wet system. The influence of the waterblocking function on oil recovery performance will be discussed in. later sections.

SENSITIVITY STUDIES One dimension simulations A series of one dimensional simulations was run in order to

examine in a simple geometry, the interaction of the ftuid and rock property descriptions with the CCh process description employed in the simulator. These runs demonstrate the character of the linear displacement and the sensitivity of predicted performance to variations in the parameters and functional relationships used to describe the system.

The mixing parameter model 7 employed in the simulator allows the prediction of the effects of viscous fingering without actually repro-ducing in the simulations the details of the unstable frontal advance.

The reservoir description used in the 1-0 simulations included a porosity of 0.20 and a permeability of 150 mO. These are values representative of the pay in the area of the 12L where the miscible flood is likely to be implemented. The displacement pressure is held to about 3500 psi, well above the miscibility pressure of 3000 psi, by means of specifying the injection pressure. The throughput rate was specified by means of the production rate.

Simulation of the historical12L performance indicates that the oil saturation in the area likely to be the target for miscible flood will still be near discovery conditions if the miscible flood is implemented in early 1992. Therefore, for our process simulation work, we used an initial oil saturation of 0.8, i.e. connate water conditions. Thus, it was assumed that the CCh miscible flood will be essentially under secondary conditions.

For the initial set of runs, the mixing parameter, which control the degree of viscous fingering represented in the simulations, was assigned a value of 0.6. This represents a modest degree of viscous fingering. Values of this order have been used in simulations that were successful in matching a number of actual field-implemented CChmiscible flooding projects8,9.1O. Waterblocking has no influence on secondary CCh floods unless a WAG process is employed. Consequently, we first look at cases where the waterblocking function is left out. Later, we examined the influence on predicted performance of variations in the mixing parameters and different waterblocking functions. All 1-0 simulations are run to a total throughput of 2.0 hydrocarbon-pore-volume (HPV).

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Fig. 12 shows predicted cumulative CCh injection and CCh and oil production for a case of continuous CCh injection. By 2.0 HPV the oil recovery has nearly reached the maximum of 0.938, consistent with the miscible-residual saturation of 0.05. More than half of the CCh injected has been recovered. After CCh breakthrough at about 0.5 HPV, produced CCh would be available for reinjection. Thus, after CCh breakthrough, the net CCh requirements increase very slowly, and in fact, only equals the volume of oil being recovered.

Water alternating gas processes are often used to help control the mobility of the solvent and, hence, promote more efficient oil recovery. For a linear system, we might expect mobility control to reduce the length of the fingered zone. We also expect mobility control to improve areal sweep in pattern floods, and to improve vertical conformance in stratified systems. Fig. 13 shows cumulative oil recovery and cumulative CCh injection and recovery for the 1:1 WAG case. Note the same high recovery as for the continuous CCh injection case. However, only half the CCh has been injected as was required for the continuous CCh injection case.

Many CCh process are comprised of a fixed volume of CCh fol-lowed by waterdrive. These are often referred to as CCh-slug processes. The CCh is meant to mobilize the oil, particularly under tertiary condi-tions, while the final waterdrive is meant to drive the mobilized oil to the production well. Since the waterdrive has a much more favorable mobility ratio than does the CCh flood, this process has the potential of being more efficient than straight CCh flooding. The use of a CCh-slug process is an attempt to reduce the CO2 required per barrel of oil recovered.

Fig. 14 compares the predicted results of the straight CCh process with those of the WAG process for the cases of a 0.5 HPV CCh injection volume and a 1.0 HPV CCh injection volume, each followed by a final waterdrive. Straight waterflooding is shown in this figure for comparison. Here we see that cumulative recovery for 0.5 HPV WAG process is nearly as good as that predicted for the 1.0 HPV straight process. Furthermore, the rate of oil recovery is much higher for the WAG processes. This is reflecting the improved effective CCh mobility of the WAG process.

Fig. 15 shows the effect of the value of the mixing parameter on the prediction of oil recovery performance for the case of a 0.5 HPV 1:1 WAG + WD. Over the range 0.4 to 0.8 (more to less fingering) of values for the mixing parameter the sensitivity is about 0.05 to 0.06 OOIP increase or decrease in the predicted cumulative oil recovery, relative to the base case of omega= 0.6. This sensitivity is less than it is normally seen, and reflects the better than usual mobility ratio for the CCh-oil displacement. Sensitivity to the waterblocking function will be described bellow.

5-spot pattern flood simulations From the I-D simulations it was observed how the parameters and

functions that describe CCh miscible flooding for the J2L sand interact in determining the performances of linear displacements. In this section we examine the CCh miscible flood process as it might perform in a pattern flood. A 5-spot pattern is selected for study as it captures all the displacement features might anticipate observing in the J2L application, but in a simple, easily understood geometry. In additions to areal effects, it is expected to see strong gravity effects. This should result from a combination of 1) the large density contrast among the fluids, 2) the high permeability with allows for rapid gravity segregation, and 3) the large well spacing which, together with the high permeability, probably will result in a gravity-dominated displacement.

Fig. 16 shows the numerical grid used to represent the quarter 5-spot symmetry element. This grid has been demonstrated to be fine enough to resolve the areal character of the displacement 7. As indicated in the figure by the dashed lines, the simulator actually solves the equa-tions for 1/8 minimum element of symmetry. This formulation results in reduced requirements for computer resources. Also, an alternative grid

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system was used for representing a quarter 5-spot symmetry element. This is referred to as a 2-D variable-width cross-section model. The plan view area of this model is the same at that of the quarter 5-spot element. This model does not resolve the areal sweep in any given layer. However, with the expanding and contracting cross-section, the model does reproduce the effects of the diverging flow as the fluids leave the region of the injection well and the converging flow as the fluids enter the region of the production well. Thus, the ratio of viscous to gravity forces is maintained in the correct proportion as the flood proceeds across the pattern.

The 2-D variable width cross section model has benefits over the 3-D model in that 1) simulations can be made much quicker as the computer requirements are reduced for the reduced grid, and 2) it is easy to examine cross-section maps showing the features of the displacements. The cross-section model gives good approximations to the performance predicted by the 3-D model when vertical sweep effects are much important than areal sweep effects. After several tests it was determined that the predicted performances for the two models were very similar. That allowed us to use the 2-D variable width model to study the character of the CCh displacements for the various processes described in this section.

Fig. 17 shows the final recoveries predicted for a variety of WAG ratios, from continuous straight CCh injection (WAG=O) to continuous straight waterflooding (WAG=infinity). Here we see a well defined optimum at a WAG ratio of 1:2. The final oil recovery for this case is 0,779 OOIP, and the incremental oil recovery over straight waterflooding is 0.121 OOIP.

From the table of transport properties, above, we see that there is considerable driving force (density contrast) for both underrun of injected water and overrun of injected CCh. However, examination of saturation profiles generated during the simulations show that there is lit-tle actual underrunning by water during the waterflood, but considerable overrunning by CCh during CCh injection. This is because, for the wa-ter injection case, the capillary pressure distributes the water vertically. However, for the CCh injection case, since under miscible conditions there is no interfacial tension and, hence, no capillary pressure, there are no forces to counteract that of gravity. Consequently. rapid segregation of the oil and CCh occurs.

The saturation distribution at the end of the straight CCh injection case showed that there was considerable oil in the lower portion of the pay that was still at initial saturation. As we increase the WAG ratio, we start waterflooding some of this oil in the portion of the pattern while, simultaneously, CCh flooding the upper portion of the pattern.

Unlike viscous dominated floods where CCh and water flow to-gether for WAG processes, for gravity dominated processes the WAG components may segregate. After segregation, the height of the CCh-water interface adjusts itself such that the ratio of the mobility-thickness products for the CCh and water is about the same as the WAG ratio. Thus, if the WAG ratio were I: 1 and the endpoint CCh mobility were 10 times the end-point water mobility, the thickness of the water zone would have to adjust to be 10 times that of the CCh. Consequently, for this system, the higher the WAG ratio, the thinner is the zone at the top of the model contacted by the CCh.

This combination of displacement phenomena results in the recov-ery performance depicted in Fig. 17. At very low WAG ratios, we leave too much oil at initial saturation in the bottom of the model. As the WAG ratio increases, we start recovering waterftood oil, but the CCh invaded zone gets thinner, resulting in less miscible recovery. Past the maximum oil recovery predicted for a WAG of 1:2, the increase in wa-terflood oil does not compensate for the decrease in miscible flood oil.

All the pattern-flood simulations described so far have not included a waterblocking function in the process description. Fig. 18 shows how the final recoveries for the different processes change when the strongest waterblocking function (ALPHA = 1.0) is used. Here we see a

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monotonic decrease in both total and incremental recovery as the WAG ratio increases. One way to view these results would be to say that the most prudent process would be a straight C(h injection process. Alternatively, we could say that the potential for gain using a 1:2 WAG process is far greater than the potential loss. Here, we must keep in mind that the most severe waterblocking function has been employed, and that there is at this time no direct laboratory evidence that there even is any waterblocking for our particular application.

One process alternative would be to allow a lower bottom-hole flowing pressure after C(h breaks through. This would be an attempt to take advantage of the natural gas lift in maintaining for a longer period, a high oil production rate. Fig. 19 shows the effect of using a producing bottom-hole pressure constraint of 1000 psi instead of 2500 psi. Recall that, until C(h breakthrough, the throughput rate is controlled by the maximum oil rate of lOO/STBO/d (quarter well). Fig. 19 shows that the continuous C(h injection process suffers the greatest degradation in performance. Here, the pressure is drawn down below the miscibility pressure, and miscibility is lost. The final oil recovery at the GOR limit is nearly 0.07 OOIP less than that for a straight waterflooding.

Up until this point, results have been reported for continuous injection cases, i.e. C(h and water are injected until an economic limit is reached.

Fig. 20 shows the final recovery predicted for a series of C(h slug simulations, for C(h slug sizes for the 1:2 WAG process. For these runs, a specified volume of COz is injected and then water is injected until the producing watercut reaches 0.95. Here, we see a 0.4 HPV of COz can be injected in under 5 years. However, if this is followed by water injection, the incremental oil recovery over straight waterflooding is under 0.03 OOlP.

In summary, we note that the features for a potential COz miscible flood in the J2L are dominated by gravity forces. Because of the favorable mobility ratio and a capillary pressure function that results in reduced gravity slumping, straight waterflooding might recover 0.658 OOIP, for a perfectly confined, repeated pattern. A straight C(h injection scheme results in a reasonable oil recovery (0.713 OOIP), but requires a large volume of COz (8.6 Mscf of total COz injection per stock-tank barrel of oil produced). A high WAG ratio flood is more efficient but the relative mobility considerations result in the COz only flooding a very thin region at the top of the formation. Therefore, the recovery is mostly the result of waterflooding. An optimal WAG ratio (1:2) results in both miscible oil recovery and waterflood oil recovery. This process might recovery 0.78 OOIP, or an increment of 0.12 OOIP over straight waterflooding. The COz utilization for this process is less than 4 Mscf of total COz injection for each stock-tank barrel of oil produced.

If waterblocking of oil from contact with the injected COz sol-vent is, indeed, severe, the oil recovery performances for all WAG process will be degraded. However, the potential gain from a WAG process would appear to be much grater than the potential loss due to waterblocking. Again, it should be noted that we have no independent laboratory data to confirm that waterblocking is a problem in the J2L reservoir rock. However, standard correlations indicate that it could well be a problem.

For a slug process, as adverse to continuous injection process, water injected subsequent to the C(h slug will cause mobile oil to float back into the region previously swept by the miscible solvent. This re-saturation loss can be significant. Predictions indicate that incremental recovery for the 1:2 WAG process could drop from 0.12 OOIP to less than 0.03 OOIP if a slug size of 0.4 HPV or less is used instead of continuous COz injection to an economic limit.

HISTORY MATCHING The objective of the history matching was to calibrate the nu-

merical model of the NIP-l03 reservoir to match the observed data. Historical production rates were input and pressure, water production

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and water-cut in the wells constituted the history matching parameters. Since the reservoir pressure was always well above the bubble point pressure, the gas-oil ratios were not considered a historical matching parameter. A plot of predicted field pressure against historical obser-vations can be seen in Fig. 21, similarly the water-cut production of well NV-109 can be seen in Fig. 22, showing good agreement with the simulator prediction.

PREDICTIONS Future production performance of the NIP-l03 J2L reservoir was

investigated using five cases: CASE O. Natural depletion (continued waterflooding from the

aquifer) The reservoir is produced by wells NV-l07 and NV-120, as it is produced at this moment in time.

CASE 1. Straight COz injection in well NV-I07, at a injection pressure of 6720 psia, Wells NV-103, NV-105, NV-l08, NV-109, NV-120 and NV-126 open to productions.

CASE lAo Identical as CASE 1, except that the injection pressure is dropped to 4720 pSia.

CASE 2. Identical to CASE I, except that wells NV -107 and NV -109 are closed.

CASE 2A. Identical to CASE 2, except that pressure was reduced to 4720 psia.

CASE 3. WAG (1:2) injection in well NV-107, wells NV-105 and NV-I09 closed. The simulation results for each case are summarized

. in Tables 1 and 2. The results for the five first years are summarized in Table I, while in Table 2 is presented the results for ten yeas.

DIscussion. The most likely scenario is CASE 2, after five years, the incremen-

tal oil recovery over continued depletion is predicted to be 800 MSTBO, after having injected a total of 3560 Mscf/d, and produced 3.16 MMMscf of COz, which presumably, will be flared if no other project is available. At this point in time it has cost 8.13 Mscf of COz for each incremental barrel of oil recovered. If produced C(h is re-USed the net C(h required is 4.2 Mscf COz per incremental barrel of oil recovered. Dropping the injection pressure to 4720 psi a (BHFP), we will lose 210 MSTBO; this is because the pressure in the project area cannot be maintained above the miscibility pressure, and the average injection rate drops to 1424 Mscfld. If wells NV -105 and NV -109 are open to production or if a new well is drilled in this area, the production may increase by 600 MSTBO. This would seem a very worthwhile consideration.

Because of the low productivity index of well NV-107, the WAG process falls very short of the continuous COz processes. The average COz injection rate is only 490 Mscf/d. It is important to note, however, that for a project containing many patterns, the relative performance of the WAG process could be much better. For example, for our case, over four injectors could be in operation for the same COz availability as for case 2. In other applications, it has been found that total oil recovery under WAG is much higher than for continuous C(h injection, even though a single pattern performance may appear better for continuous COz injection.

At five years notice that the oil recovery efficiency is only 25.6% OOIP. This reflects both, that large areas are not being swept, as well as limited vertical sweep resulting from the gravity override. At ten years, it can be see that the relative performances of the different process are about the same as seen at five years. Note, particularly, that over one million STBO might be gained just by working over NV-I05 and NV-109 wells (or perhaps, drilling a new well in this area). At ten years, note that the COz utilization is probably not economic for the most likely case (CASE 2); having required 14.7 Mscf of C(h injection for each incremental barrel of oil recovered. In practice, the producing GOR would be monitored, and the process terminated when the instantaneous GOR becomes uneconomic. The most cost efficient process is the

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WAG process, although, again, because of the low throughput rate, the recovery is low.

CONCLUSIONS

For continuous C{)z injection in the reservoir crest (Well NV-I07), the incremental oil expected is 800 MSTBO (5\% OOIP) after injecting 6.5 MMscf of C{)z in a 5 years period, at a injection rate of 3560 Mscf/d and a injection pressure of 6720 psia (BHP). To the end of the 5 years period the cost for incremental oil would be of 8.13 Mscf, which could be reduced to 4.2 Mscf if the C{)z is recycled.

Gravity effect are likely to be significant for any displacement in the J2L. Thus, injected water will attempt to underrun the oil column, and injected C{)z will attempt to overrun the oil column.

If the injector and producer bottom-hole pressure are not controlled so as to maintain the average pressure higher than the miscibility pressure, significant potential oil is lost.

Without waterblocking, a WAG ratio of 1:2 was determined to be optimum for a pattern flood. However, when a strong water-blocking function was employed in the simulation model, much of the potential advantage for the WAG process is lost.

A process that employs a specified volume of C{)z followed by final waterdrive is predicted to recovery significantly less oil than a continuous C{)z injection process. This is because of resaturation of the C{)z miscible swept region with oil during the final waterdrive portion of the process.

REFERENCES

1. Rivas, 0., Embid, S., Bolivar, F. Ranking Reservoir for Carbon Dioxide Flooding Process. II LAPEC, March, 1992.

2. Goodrich, J., Review and Analysis of Past and Ongoin Carbon Dioxide Injection Field Test. SPE 8832 SPE/DOE EOR Sympo-sium Tulsa, 1980.

3. Baker, L. E. Three-Phase Relative Permeability Correlations, SPE 17369, Dec. 1988.

4. Stalkup, F. Y. Displacement of oil by Solvent at High Water Saturation. SPEJ, Dec. 1970.

5. Tiffin, D. L., Yelling, W.F. Effects of Mobile Water on Multiple Contact Miscible Gas Displacements. SPE 10687 SPE/DOE EOR Symposium Tulsa, 1982.

6. Claridge, E. L. C{)z Flooding Strategy in a Communicating Lay-ered Reservoir. SPE 10289, 1981.

7. Todd, M. R., Longtaff, W. J. The Development, Testing and Application of a Numerical Simulator for Predicting Miscible Flood Performance. JPT, July, 1972.

8. Bilhartz, H. L. A Method for Projecting Full-Scale Performance of C02 Flooding in the Willard Unit. SPE 7051, April, 1978.

9. Youngren, G. K., Charlton, G. S. A History Match Analysis of the Little Creed C{)z Pilot Test. JPT, Nov. 1980.

10. Pontious, S. B., Tham, M. J. North Cross (Devonian) Unit CCh Flood Review of Flood Performance and Numerical Simulation Model. JPT, Dec. 1978.

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SI Metric Conversion Factors bbl x 1.589 873 E-Ol = m3

psi x 6.894 757 E 00 = kPa

("F-32)/1.8 = C 141.5/(131.5 + API) = g/cm3

Authors

Jaime Almeida is a research engineer at INTEVEP, S.A were he works in compositional reservoir simulation studies, he received a Chemical Engineering degree from the "Institut National des Sciences Appliquees (INSA), " Toulouse, France" and a MSc de-gree from The University of Manchester Institute of Science and Technology (UMIST), Manchester, England. Carlos Espinoza is manager of the Production Department at INTEVEP, SA He hold a as and PhD degree in mathematics.Jose Mosquera was a senior reservoir engineer at CORPOVEN, S.A until he died in 1992.Mlchael R. Todd is the president of TCA Reservoir Engineer-ing Services, a reservoir engineering consulting firm specializing in the design of EOR projects. Previously he worked for Shell Development Co. and for Intercomp Resource Development & Egineering Inc. He received a BS degree in aeronautics from the Massachusetts Inst. Technology, an MS degree in mechanical en-gineering from Imperial C., London, and a PhD degree in chemical engineering from the State U. of New York in Buffalo. Todd was the winner of 1973 SPE Ferguson award.

Fig. 1. Isopach map NIP-I03 I2L reservoir.

1-6

Fig. 2. Well NV-126 induction log.

(SPE 23678)

SPE Advanced Technology Series, Vol. 2, No. 1

500

400

Q .... i 300 .. a:

200

100

5.0

Rs

2.5

0.0 2500 0L-~~~~L-~------~~~~~~~~~~ 500 1000 1500 2000

PRESSURE (psla,

Fig. 3. Solubility of associated gas

100 0

75

M Ii: iii d. 50 ~ Q..-'l iii as c

25

OBSERVED CAlCtl.ATED

0 e e

2000

0 0

3000 PRESSURE (psla,

0

I

4000

Fig. 5. Hydrocarbon phase density

0.90

0.80

> 0.70 !::

mO.60

~0.50 W Il. wO.40 > ~ 0.30 a: 0.20

0.10

Krow

Swc-O.20 Sorw-o.26 Iao(Swc)oO.5654 krw(Sorw)-o.17I6

, ,

, ,

,

, , ,

0.00 L..r ................. s;;., ...... _ ....... "-...... _~"-.................. ..;J 0.00 0.25 0.50 0.75 1.00

WATER SATURATION

Fig. 7. Water oil relative permeability

SPE Advanced Technology Series, Vol. 2, No. I

100

75

50

25

o 5000

iii ~ III

~ ~ III

~ ! 11 :> ..,

1.500 1.500 0 OBSERVED

g,.45O CAlCll..ATEO

1.450 III iii !; a: 1.400 1.400

~ if W

'

35O 1.350

::Ii :::l ...J 0 >'.300 1.300 Z Q ....

e: ~1250 1.250 12

1.200 1.200 0 1000 2000 3000 4000 5000

PRESSURE (psla)

Fig. 4. Hydrocarbon phase formation volume factor

1.00 1.00 0 OBSERVED

CAlCu.ATED

0.75 0.75 0

Ii:' g, ~0.50 0.50 III 8 III >

0.25 0.25

0.00 I--.................... -...J .................. ....L .................. ...L ................... J... ................ .....J 0.00 o 1000 2000 3000 4000 5000

PRESSURE (psla,

Fig. 6. Hydrocarbon phase viscosity

1.00 .......... "T""...., ............ "T""",...,. ....... "T"" ....... ...,. ...... ......,,....,., 0.90

0.80

~0.70 ::;

~ 0.60 ~0.50 w Il. wO.40 > ~0.30

. a: 0.20

0.10

Krg

Swc-O.20 SorPl26 SpO.OS Iao(S,..o)oO.5654 IaJ(SorJ)..Q.179

Krog

0.00 r.. ___ ............................. """;;...,.. ........... -L:;:;:::=.-....:I 0.00 0.25 0.50 0.75 1.00

LIQUID SATURATION

Fig. 8. Gas oil relative permeability

91

92

1.5

Sg

Fig. 9. 'Three phase-oil relative penneability

0.30 ,......_ ...... .,....,,......-...,.....,....,,..-.-...... .,....,,.. ....... -r-...,

~ I-< I-~0.20 -' a c w x:

~ 0: 0.10 w

i ~

..... 11

0.00 L.. ............... ...:::I_;;;;:;:J:::;; ..... .-.::r::::::; ...... ....L.. ............. ........, 0.00 0.25 0.50 0.75 1.00

WATER SATURATION

Fig. 11. Water-blocked oil saturation

1.00

C a I I

050 I II

0.5

L.::::.. ....... ..a.-._...J.....c:::::O:"' ....... _...l-....... ___ :7 .......................... -: 0.00 0.00 .0 0.5 1.0 1.5 2.0

TotA&. .... erlCH (trI)

Fig. 13. I-D. 1:1 WAG: cumulatives

1.5

0.5

! ~ 15 ;:) en 13 a: D.. >-a: 10 :5 -' iL is -' ~ 5 i

0.25 0.50 0.75 WATER SATURATION

Fig.l0. Water oil capillary pressure

1.00

0.75

s I

0.50 I II

0.25

0.0 L-...... -'" ....... -'-:r:::::::&.. ...... -'"-:-':-' ..... "'--~-=,:5 ...... --' ...... "'-..... 2-:.':00 ~ " I~ .

1.00

0.'0

~ 1 0 . 0 I ,. ! 0.70 IE

II 0.'0

TOTAL .... CTI)N(WV)

Fig. 12. I-D. continuos CO2 injection: cumulatives

, , ,

/ , ,

' .. ""WAQ ...... -

.--

- 0.'0 ".~:~~~~.o_--____ ~ ", .... HPVILUO c

1ft a 0.'0 I 0.70 i

WatrftoOd ~ --------~~--~ II 0.80

0.50 L.. ........................ _L-................ -"' ....... __ '-................ ....L ........ --' .................... 0.50 0.0 0.5 1.0 1.5 2.0

TOTA&. IfIUECTM)N PPVJ

Fig. 14. I-D. comparison of slug and WAG processes

SPE Advanced Technology Series, Vol. 2, No. I

Z 3 4 , 6 7 9

1.00 1.00

:-6) V:J V

-'-'-- 1/ 1 O.tO 0.90

......... (bIMc.e) 6 / 1

1/ _ . , .... - e ~ S 0.10 I 1 0.80 I I ~ i Ii

0.70 i ~ 0.70 g g

/ /

/ ~

0.80 0.80

0.50 0.50 0.0 0.5 1.0 1.5 2.0

~llllllllllil TOTAL HJECTtON (WV)

Fig. 15. 1-0. Effect of fingering level on predicted recovery Fig.16. 3-D grid used for 5-spot pattern flood simulations

0.80 0.200 iL 0.80 0.200 iL iL -. ---.... - ;,' 0.100 a: ~ . ~ 5 o il. i'.... ...J ~ 0.80 ~ i:; '\ ,. del Er i

~ !' 0.050 ~ 5 ; a: ~ A ~ o Er(wf) 658' ,J:i ..-, del Er(1:2 WAG).,121 .n

0.50 L-.-'-............ ~::..i... ...... '-' ...... _ ...... ....L. .................. -'-................. .1...I ........... .o...JO.OOO ~

Er _ ......... , ~:- ..w:PIPAOI_2500 PI' . ...::._-__ ~""',:g:-Pj ... OI.'......! 1 . ~ !, 0.150 > ffi 0.70 Il : ~! ! 8w> S .. -':; \.. a:

I ,"'-'-:-_....l!!!Er' 0.100 ...J a: ~ 0 0 6 8 ; ~ ...J ~ 0.80 = 15 i ~ i U50 ~ ! Er(wl)-.,658 ~ ~ ,J:i ui

0.50 L...-... ...... .o...JL...o. ...................................... ....I. .......................................... 4>-................... 0.000 ~

Fig. 19.2-0, 5-spot, effect of pressure on process performance Fig. 20. 2-D 5-spot, effect of CO2 slug size on process performance

SPE Advanced Technology Series, Vol. 2, No. I 93

NY-loa

2 ... .2

__ --------------------___ N.,- --..----

....,

.-.

eo

a-v-.... ...

'38.' sa

year year

Fig. 21. History matching: pressure Fig.22. History matching: water cut well NV-109

TABU: 1. PREDICnON ANALYSIS Ta 5 YEARS OOIP 15.5 MMSTB

procesl Qo Incr . DH. E. C02 I. qC02 C02P. Ef brut Ef.NeI Qw

--"'"

..... 'lAC. -=- ..:0/0 -.:f ilia"" ilia""

--CASE 0 3.17 0 .aGO .205

CASE 1 . 56 1.390 590 .29. 6.60 361. 3.88 . 75 1.96

CASE 10 . 21 1.1,.0 UO .272 2.90 1588 1.76 2.79 1.10

CASE 2 3.97 aoo 0 .256 6.50 3559 3.16 8.13 . 18

CASE 20 3.76 590 210 .U3 2.60 l.u U7 . 1 1.92 CASE 3 3 . .s 280 520 .223 .195 .90 .2BB 3.20 2.17 257

TABU: 2. PREDICnON ANALYSIS Ta 10 YEARS OOIP 15.5 MMSTB

p.oc ... Qo Incr . DR. E. C02 I. qC02 C02P. Ef bruta Ef.NeI Qw

--

..... ... FIAt:. -.:f ,,,,"ID -. ..:0"" IIICffl1l -. CASE 0 3.S. 0 -870 .228

CASE 1 U5 1.910 l.u.o .352 13.8 3778 7.~ 7.23 3.38 CASE 10 5.10 1.560 690 .329 7.10

"" 3.S. 55 2.28

CASE 2 . 1 870 0 0.285 12.82 3510 7M 1 .. 7. 6.16

CASE 20 .. ~ aoo 70 .280 6.7. lW 2." U3 5.38

CASE 3 3.98 ..a .4JO .257 1.79 .90 .878 . 07 2.07 515

CASE. . U 700 170 .27. 6.38 0 1.02 9.11 7.66 B9B

(SPE 23678)

94 SPE Advanced Technology Series, Vol. 2, No.