Production Strategy for Thin-Oil Columns in Saturated Reservoirs

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Reservoirs With Small Gas Caps

Stage 1 Depletion. The H-01/MR-56 is a saturated virgin reser-voir. The OOIP for this reservoir is estimated to be 19.60 MMSTB.Three wells penetrated the reservoir. A crestal well encounteredapproximately 24 ft net oil pay, with an average reservoir porosityof approximately 26%.

Fig. 2 shows the initial oil saturation profile in the H-01/MR-56reservoir. A conventional horizontal well drilled in the best part of the reservoir recovered 1.96 MMSTB or 10% of the OOIP. Fig. 3shows the oil saturation after 27 years of production. Again, sub-stantial reserves will be left undrained, if this reservoir is to bedepleted by conventional method only.

Stage 2 Depletion. At the end of Stage 1, only 10% of the OOIPhad been recovered by the conventional method. After initiating

Option 1 (crestal vertical completion in the gas cap) of the gas-blowdown scheme, recovery increased to 12.7% of the OOIP. Fig.4 captures the saturation profile for this scenario at the end of project life. However, Option 3, which is horizontal completions atthe GOC, yielded approximately 20% of the OOIP.

Reservoirs With Large Gas Caps

Fig. 5 presents the oil saturation distribution of Ekiti-7 reservoir atthe end of history match. The gas column in Ekiti-7 reservoir in theOkubie field is approximately 200 ft thick, overlain by a 45-ft oilcolumn. The OOIP estimate ranges between 45 and 63 MMSTB.In reservoirs with thick-gas columns, such as Ekiti-7, two deple-tion strategies were adopted. They were two-stage depletion withgas well completions just above the GOC for reverse coning.

Two-Stage Depletion. Stage 1 involved the drilling of two hori-zontal wells with a 13-ft standoff from the GOC. Cumulativerecovery after 27 years of production is approximately 11.4MMSTB, or 18% of the OOIP.

In Stage 2, after the initial depletion with horizontal wells, oneof the wells is recompleted as a vertical-gas producer, just above

Fig. 2—Oil saturation profile of the H-01/MR-56 in 2003.


Fig. 1—(a) Schematic representation of conventional comple-tion. (b) Remaining oil column after the floodout.


74 February 2008 SPE Reservoir Evaluation & Engineering



value associated with a variable suggests that its increase has anadverse effect on the optimized variable, oil recovery in this case.The opposite is true for a positive value. In other words, the chartsindicate that increasing the oil-column thickness is good for re-covery, while increasing the residual oil saturation decreases re-covery. These observations are consistent with those one mightexpect intuitively.

On the basis of these results, we combined ho , k h , S orw , and Lw

with the process variables for another set of D-optimal designexperiments. Following exactly the same procedure discussed be-fore, 30 flow-simulation runs were made with six variables.

Fig. 9 presents the Pareto chart. The chart shows that all thevariables fall to the left of the “95% confidence level” line. Oneshould not misconstrue that these variables do not influence theprocess; rather, we cannot make “statistical significance” claimsabout these variables at the specified 95% significance limit.

A full-factorial design with all possible combinations of the sixvariables will result in 729 (36) flow-simulation runs. With D-optimal design, only 30 flow-simulation runs out of a possible 729were actually made. To fill in the information void, we generateda polynomial using the multivariate nonlinear regression to repre-sent the response surface, which serves as a proxy to the flow

simulator. The polynomial in terms of recovery factor, , is given by

= −24.626 + 1.722ho + 9.687 × 10−4k h

+ 3.171S orw + 2.062 × 10−3 Lw + 0.276hGOC

+ 4.983 × 10−4q − 0.026ho

2+ 1.482 × 10

−4qho

− 0.019qS orw.

. . . . . . . . . . . (1)

Eq. 1 is the correlation for evaluating Stage 1 recovery factor.

Stage 2 Depletion. Following exactly the same ED procedure usedearlier, we determined that time of switching to Stage 2 or thegas-cap-blowdown phase and gas rate at which to produce the wellat are the key variables of interest. Table 2 presents the two

variables and their statistical distributions.With two variables, we constructed a 9-run experimental matrixfor the full-factorial design. Table 3 presents the variable matrixand the results of flow simulations. Variables are represented by–1, 0, and 1, which reflect p-10, p-50, and p-90, respectively, asidentified in Table 2.

Following the flow-simulation runs, we developed a Paretochart, which is shown in Fig. 10. As expected, gas rate dominates,

not just as a linear term, but also as a quadratic term, as shown inthe following expression:

= −24.915 + 1.961qt − 0.07t

− 0.082q2

− 0.036t 2

+ 0.016q.. . . . . . . . . . . . . . . . . . . . . . . . (2)

Eq. 2 allows one to evaluate the recovery factor for the combineddepletion schemes, whereas Eq. 1 does so for Stage 1 only.

Verification of Correlation

Synthetic Data. Eq. 1 was tested with independent sets of datafrom numerical experiments. Fig. 11 tests independent flow simu-lation data obtained for the G-01/MR-02 reservoir. One potentialdifficulty with the application of a correlation of this type is thatthe contributing length of a horizontal well is never known a priori. The lack of a superior agreement in Fig. 11 is attributed tothe difficulty of discerning effective L

w in a heterogeneous field.

Fig. 12 makes this point.Recovery factors obtained from this study were compared with

analytical methods using both in-house and external correlations,

as shown in Table 4. The results of this study are consistentlylower for the G-01 and higher for the H-01 reservoir than others.Our observation is that the other correlations, unlike those devel-oped here, do not incorporate the phenomenological variables gov-erning recovery. Consequently, large discrepancies can occur. Thiscomparative study underscores the inherent danger of extrapolat-ing the use of any correlation beyond the bounds of the original study.

Field Data. We also tested and validated the correlations withpublished field data from the Attaka (Irrgang 1994) and Serang(Vo et al. 1997) fields in Indonesia.

Fig. 13 suggests that the general trend holds, but is skewed tothe right. This skewness is attributed to higher recoveries in thefield owing to high-well density. For instance, the average-

Fig. 8 —Relative contributions of variables to recovery factor.

Fig. 9 —Relative contributions of variables.




drainage area per well is 66 and 34 acres in the Attaka and Serangfields, respectively. By contrast, the G-01/MR-02 has 602 acres fora single-well situation. Note that we did not incorporate drainagearea as an independent variable in our ED work. That is becausethe minimal economic oil recovery of 2 MMSTB at the currentbusiness setting precludes the use of denser well spacing, which is

an order-of-magnitude smaller than those used here.Nonetheless, we made experimental runs to replicate small

drainage area in the G-01/MR-02 reservoir. Eight wells approxi-mated a drainage area of 75 acres per well. Recovery factor fromthese wells ranged between 22 and 56%. This spread in recoveryfactor is a direct reflection of areal heterogeneity. That denser wellspacing leads to higher recovery in coning/cresting situation isdemonstrated by this numerical experiment.

Field Examples

Example 1. The D-2 Sand in the South Timbalier 37 field is atypical Gulf of Mexico strong water-drive reservoir. This deltaicsandstone is upper Miocene in age, having high permeability of over two darcy with porosity of approximately 30%. Strong bot-

tom-water-drive provides most of the energy support at a depth of 11,800 ft subsea in this reservoir. Fig. 14 displays the two wellswith different orientation in the flow-simulation grid, with localrefinement around the wells.

Since the project’s inception in July 1998, we recognized thatthe oil column is located between a small gas cap and a highlyactive aquifer. The oil-column thickness is approximately 40 ft,and the gas column is approximately 83 ft. In this study, the OOIPis estimated at 12 MMSTB within a 9,288 acre-ft oil band with asolution GOR of 889 scf/STB. The in-place free gas volume isestimated at 7.33 Bscf in a 2,946 acre-ft gas cap. Cumulative oilproduction as of October 2003 was 7.44 MMSTB, representing62% of the current OOIP estimate. Cumulative gas production asof October 2003 was 9.8 Bscf, representing 54% of the OGIP.

Fig. 10 —Stage 2; relative contributions of variables.

Fig. 11 —Correlation vs. simulation recovery factor.

Fig. 12 —Performance sensitive to horizontal well length.

Fig. 13 —Verification of correlation with field data.

77February 2008 SPE Reservoir Evaluation & Engineering



Pressure data indicated less than a 400-psi pressure drop from theinitial datum pressure of 4,780 psia.

Stage 1 Depletion. The I-1 well was the first well drilled tar-geting multiple stacked sands. This vertical well penetrated a lowerportion (33 ft net TVD) of the gas cap as well as an upper portion(11 ft net TVD) of the oil band. The initial perforations were withinthe uppermost 10 ft of the oil column. The cumulative productionthrough February 2002 was 2 MMSTB of oil and 3 Bscf of gas.Fig. 15 shows the production profile and Fig. 16 presents thematch obtained. The rapid decline of GOR is tied to balancedwithdrawal rate commensurate with the strong aquifer support.

The I-2 well was a horizontal well drilled along strike to the I-1well with a 320-ft lateral section. This well was completed in Julyof 2000. The cumulative production through February 2002 was2.5 MMSTB of oil and 4.9 Bscf of gas. Fig. 17 captures theproduction history, and Fig. 18 displays the GOR match.

Stage 2 Depletion. At the beginning of 2003, a pulse-neutroncapture log was run across the I-1 well, indicating a 44-ft columnof oil. This encroachment of the oil band into the gas cap occurredafter cumulative production of 4.54 MMSTB, representing 37.8%of the OOIP and 8 Bscf, representing 44% of the total OGIP. Thus,in February of 2002, the additional (33 ft net TVD) perforationswere shot to take advantage of the entire oil column. As of October2003, the oil recovery factor has increased to 62% and the gasrecovery factor has increased to 54%, as previously indicated.

To interpret and optimize the reservoir performance and recov-

ery, various tools were implemented to model the D-2 Sand. Flowsimulations confirmed movement of the fluid contacts. The modelfurther showed that the active aquifer accounted for over 90% of the reservoir energy as well as excellent sweep within this cleanpackage of sand.

To summarize, use of the two-stage completion strategy al-lowed for optimum hydrocarbon production and recovery. Of course, monitoring the fluid movements aided the process. In sodoing, we realized excellent sweep, while minimizing the loss of energy from the production of excessive free gas.

Example 2. The DS-41H well was inadvertently landed at theGOC in the Delta South G-02/DS-03 reservoir in Nigeria. Thisexample is an embodiment of typical high-permeability sandstonereservoirs in the Niger delta. Fig. 19 shows the schematic of thewell path in the structure. Despite the seemingly precarious loca-tion, the well has exhibited stellar performance, as Fig. 20 testifies.

In fact, this well happened to be the best producer in this reservoir.The precipitous decline in GOR owes largely to the downdip waterinjection. In other words, pressure support has kept the gas cap at bay,resulting in good sweep and sustained solution-GOR production.

One may surmise that the high-initial GOR may cause signifi-cant energy loss in the gas cap. Our contention is that although theinitial high-GOR response may be alarming, that does not neces-sarily lead to excessive gas production. We illustrate this pointwith Fig. 21, which shows that the normalized GOR (ratio of cumulative to solution GOR) for the DS-41H well is less thanaverage unit volume of gas that we produce from various reser-voirs, including the one where this well is located in. In other words,the proposed depletion strategy does not produce excessive gas.

Discussion

To avoid displacing oil into large gas caps and consequent “smear-ing,” we advocated the notion of reverse coning of oil by placinga horizontal well just above the GOC. As expected, very high-initial GOR production will be experienced before significant oilrate takes effect. Where gas monetization is not an issue, thisapproach will maximize oil recovery. However, to mitigate exces-sive early gas production, the well can be placed just below theGOC. As Fig. 22 shows, the high-GOR production is relativelyshort lived (∼1 year) in the H-01/MR-56 reservoir, and ensuressignificant gain or approximately twice as much reserves.

Fig. 14 —

Location of two wells in the simulation model.

Fig. 15 —Production history of I-1 well.

Fig. 16 —

History matching GOR and watercut responses,I-1 well. Fig. 17 —Production history of I-2 well.




Irwin and Batycky (1997) demonstrated that the so-calledsmearing of oil in a thick-gas column was unfounded. In carbonatereef reservoirs, they found that even an 18-ft oil column could besuccessfully displaced by bottom water into a 500-ft gas column,without experiencing the anticipated loss of oil. In fact, they re-ported a combined oil production of approximately 2,000 STB/Dfrom five crestal wells, when production of oil was least expectedduring the blowdown phase of a vertical-miscible flood. Thiscounterintuitive phenomenon became a reality because of low-S orw

saturation (∼ 10%) owing to high-trapped-gas saturation (S gt ).Their laboratory measurements showed that S gt could be in excessof 50% in carbonates when the water invasion occurs.

Similar measurements for water-wet sandstones show that S gt

can significantly reduce the residual-oil saturation, S orw. As a ruleof thumb, the total saturation (S gt +S orw) owing to waterflood isapproximately the same (Kortekaas and van Poelgeest 1991) asS orw , in absence of gas. In other words, if S gt ranges from 25 to45% (Irwin and Batycky 1997; Kortekaas and van Poelgeest 1991;Firoozabadi et al. 1987), S orw values are expected to be reduced byapproximately one-third. These observations imply that approxi-

mately 6% (1

⁄ 3 of 20% S orw) incremental of the remaining oil canbe recovered in a blowdown operation in a typical sandstone res-ervoir. Indeed, flow simulations with the hysterisis effect suggestapproximately 6% improvement in RF, which translates to over 1MMSTB incremental oil for G-01/MR-02 reservoir, as shown inFig. 23. Consequently, all results from the blowdown simulationsreported earlier are pessimistic. Details of the simulations for theG-01/MR-02 reservoir and results of other field examples are re-ported elsewhere (Kabir and Agamini 2004).

Note that most horizontal-well placements in this study con-sidered coarse (100 m × 100 m) areal grids, although verticaldefinition was retained at approximately 2 to 3 ft. Inevitably, ques-tions arise whether the areal grids are too coarse to yield “good”

solutions. To alleviate this concern, we made simulations with (33m × 33 m) local grid refinement. The recovery factors did notchange by more than 0.1%. These results are not surprising in thegravity-stable, favorable-mobility-ratio situation models.

Conclusions

1. Novel two-stage/single-stage depletion strategies for significant

recovery gain are shown in reservoirs with thin oil columns.Field data and computational results lend support to the notionpresented in this study.

2. Simulation results show that the invading water traps gas, re-sulting in additional recovery of approximately 6% of the OOIP.

3. Simple correlations are presented to screen candidate reservoirsfor both Stage 1 and the combined Stage 1 and Stage 2 depletionschemes for 600-acre spacing.

Nomenclature

Bg gas formation volume factor, RB/Mscf

Bo oil formation volume factor, RB/STB

C o oil compressibility, 1/psi

hg gas-cap thickness, ft

ho oil-column thickness, fthGOC well standoff from GOC, ft

k h horizontal permeability, md

k rgro gas relative permeability at gas saturation (1–S wi r

–S org), fraction

k rocw oil relative permeability at oil saturation (1–S wir ),

fraction

Fig. 18 —History matching GOR response, I-2 well.

Fig. 19 —Schematic well path of DS-41H well.

Fig. 20 —Production performance of DS-41H well. Fig. 21 —

Completing at the GOC does not necessarily produceexcess gas.




k rwro oil relative permeability at oil saturation (1–S orw),

fraction

k v vertical permeability, md

k v / k h reservoir anisotropy, dimensionless

Lw horizontal well length, ft

qg gas rate, Mscf/D

qo oil rate, STB/D

qw

water rate, STB/D Rs solution gas/oil ratio, scf/STB

S gc critical-gas saturation, fraction

S gt trapped gas saturation, fraction

S org residual oil saturation owing to gasflood, fraction

S orw residual oil saturation owing to waterflood, fraction

S wir irreducible water saturation, fraction

recovery factor, %OOIP

o oil viscosity, cp

Acknowledgments

We are grateful to colleagues Ed deZabala and Jairam Kamath forinsightful discussions and John Pederson for his interest and sug-gestions. Contributions made by the earth modelers are much ap-

preciated. We appreciate our partners and Chevron managementfor permission to publish this work.

References

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parent in various completions, G-01/MR-02 reservoir.




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Appendix A—Recovery Factors for ED Runs

See Tables A-1 and A-2.

Appendix B—PVT and Relative PermeabilityData

See Tables B-1 and B-2.

Rock Properties

Pore-volume Compressibility. The pore-volume compressibilityused in the simulated models is 4×10−6 psi−1 and reference pres-sure is 2,368 psia.

Relative Permeability. Water-oil and oil-gas relative permeabilitywere modeled using power-law relations, as given by Eqs. B-1through B-4. The model parameters for both water-oil and oil-gas

relative permeabilities are summarized in Table B-3.

k rw = k rwoS w − S wir 1 − S wir − S orw1.8 . . . . . . . . . . . . . . . . (B-1)

k row = k rwocw1 − S w − S orw 1 − S wir − S orw1.8 . . . . . . . . . . (B-2)

k rg = k rgroS g − S gc 1 − S wir − S gc − S org2. . . . . . . . . . . . . (B-3)

k rog = k rocw1 − S g − S wir − S org 1 − S wir − S org2. . . . . . . (B-4)

SI Metric Conversion Factors

ft × 3.048* E–01 m

*Conversion factor is exact.




Shah Kabir is a Consulting Reservoir Engineer at Chevron En-ergy Technology Company in Houston. e-mail: [email protected]. He has more than 30 years of experience in theoil industry, with the last 18 of these at Chevron. His experienceincludes pressure-transient testing, wellbore fluid- and heat-

flow modeling, and reservoir engineering. He has publishedmore than 100 papers and two books, including the 2002 SPEtext Fluid Flow and Heat Transfer in Wellbores . He holds an MSdegree in chemical engineering from the University of Calgary,Canada. He has served on the SPE editorial review committeeof several journals and has received multiple commendationsas an outstanding technical editor. He was 2006–2007 SPE Dis-tinguished Lecturer and became a Distinguished Member in2007. Rueben (Tony) Holguin is currently a production opera-tions supervisor at the Kern River heavy-oil field in Bakersfield,California. e-mail: [email protected]. Previously, he heldvarious positions in production engineering, reservoir engineer-ing, and asset development in the Gulf of Mexico Business Unit

in New Orleans. In his career, he has modeled a number ofreservoir development alternative evaluations, reserve estima-tion, and risk and economic analyses. He holds BS degrees inpetroleum engineering and mathematics from Marietta Col-lege in Marietta, Ohio. An active SPE member since 1996, heserved on the ATCE host committee in 2001.


Production Strategy for Thin-Oil Columns in Saturated Reservoirs

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