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Solution gas drive reservoirs

Oil reservoirs that do not initially contain free gas but develop free gas on pressure depletion are classified as solution gas drives. The solution gas drive mechanism applies once the pressure falls below the bubblepoint. Both black- and volatile-oil reservoirs are amenable to solution gas drive. Other producing mechanisms may, and often do, augment the solution gas drive. Solution gas drive reservoir performance is used as a benchmark to compare other producing mechanisms.

Contents

Stages of production

Pure solution gas drive reservoirs are subject to four stages of idealized production. In chronological order, the four stages are:

  1. Production while undersaturated
  2. Production while saturated but the free gas is immobile
  3. Production while saturated and the free gas is mobile and the producing gas-oil ratio (GOR) is increasing
  4. Production while saturated and the free gas is mobile and the producing GOR is decreasing

Not all these stages are necessarily realized. For instance, Stage 4 may not be realized if primary recovery is terminated during Stage 3.

The key characteristics of each stage are outlined here.

Stage 1

  • No free gas
  • Producing GOR is equal to initial dissolved GOR
  • Fractional oil and gas recoveries are small and approximately equal
  • Reservoir pressure drops rapidly
  • Duration of stage depends on degree of initial undersaturation. The greater the initial undersaturation, the longer the duration of Stage 1. The stage duration is generally short

Stage 2

  • Reservoir pressure is less than bubblepoint
  • Free gas appears, but the saturation is small and immobile
  • Producing GOR is slightly less than initial dissolved GOR
  • Rate of pressure decline is mitigated

Stage 3

  • Free gas becomes mobile
  • Producing GOR increases steadily
  • Fractional gas recovery exceeds fractional oil recovery
  • Longest of all stages; typically consumes 85 to 95% of primary recovery
  • Primary recovery may be terminated during this stage

Stage 4

  • Reservoir pressure is very low, typically less than 100 to 400 psia
  • Producing GOR decreases
  • Primary recovery often terminated before this stage is realized

This chronology and these characteristics are an idealization and oversimplification of actual behavior; nevertheless, they are instructive and provide a preliminary basis for understanding scenarios that are more complicated.

Performance

To illustrate solution gas drive performance, tank model predictions of a west Texas black-oil reservoir are presented. Though idealized, these simulations, which are from a commercial simulator, [1][2] capture the main features and establish the theory of solution gas drives.

For the sake of simplicity, the simulations consider the depletion of only a single well in an 80-acre closed area. Table 1 summarizes some of the reservoir and fluid properties. The simulations assume that the PVT parameters in Table 2 apply.

Fig. 1 shows the performance in terms of pressure, producing GOR, and gas saturation as a function of cumulative produced oil. The four stages of production are depicted. During Stage 1, less than 1% of the OOIP is produced. The pressure decreases from the initial pressure of 2,000 psia to the bubblepoint pressure of 1,688 psia. The producing GOR remains constant and equal to the initial dissolved GOR of 838 scf/STB; no free gas evolves.

During Stage 2, the pressure falls below the bubblepoint; solution gas is liberated; and low, immobile gas saturations form. The cumulative oil recovery reaches approximately 4.5% of the OOIP. The pressure decreases from the bubblepoint to approximately 1,550 psia. The gas saturation increases to approximately 5% PV. The producing GOR actually decreases slightly, but this change is barely noticeable.

During Stage 3, the gas saturation increases to the point at which gas is mobile. Free-gas production begins, and the producing GOR rises steadily. By the end of Stage 3, the cumulative oil recovery is 28% of the OOIP, the pressure has decreased to 200 psia, the gas saturation reaches approximately 35% PV, and the producing GOR reaches approximately 6,700 scf/STB.

During Stage 4, the pressure has reached such a low level that the expansion of gas from reservoir to surface conditions is minimal. Consequently, the producing GOR decreases. By the time the pressure reaches 50 psia, the GOR is only 2,000 scf/STB and the total oil recovery is 32% of the OOIP.

Fig. 2 shows reservoir performance as a function of time. This figure plots the pressure, instantaneous producing GOR, cumulative producing GOR, gas saturation, oil rate, gas rate, and fraction of OOIP and OGIP recovered as a function of time. Stage 1 is very short and lasts less than one month. The oil and gas producing rates and pressure decline sharply. The producing rates decline if the bottomhole pressure (BHP) is restricted. The producing rates can remain constant, but only if the minimum BHP is not yet reached.


Stage 2 also is relatively brief, lasting only several months. The reservoir pressure and producing rates also decline sharply but not as quickly as during Stage 1. The decline rate dampens because solution gas is liberated. The producing rates decline if the BHP is restricted. Constant producing rates can be realized only if the minimum BHP is not yet reached.

Stage 3 starts before one year of depletion and continues until the economic limit is reached. In this example, the limit is reached after 13.5 years when the oil-producing rate reaches 20 stock tank barrels/day (STB/D). The length of pressure depletion depends strongly on the reservoir permeability and on the prevailing economic conditions. For instance, lower permeabilities will decelerate recovery and protract depletion. The final pressure is 613 psia. This pressure is not low enough to realize Stage 4; therefore, this stage of depletion is not portrayed in Fig. 2. The absence of Stage 4 in field cases is not uncommon. The marked increase in the GOR from 838 to 4,506 scf/STB during Stage 3 coincides with marked increase in the gas saturation from 5 to 28.7% PV. At the economic limit, these simulations predict final oil and gas recoveries of 24.2% of the OOIP and 53.1% of the OGIP. Stage 3 clearly dominates the depletion life of a solution gas drive reservoir.

The results of this simulation are an oversimplification and idealization of actual performance. Oversimplification stems from the fact that the tank model ignores many important secondary phenomena. For example, the simulations ignore reservoir heterogeneity, which can be expected to reduce the recoveries by approximately 20 to 50% depending on the degree of heterogeneity. For instance, if a volumetric recovery efficiency of 80% is applied, then the idealized oil recovery of 24.2% corresponds to an adjusted oil recovery of 19.4%. Also, the simulations ignore spatial effects.

Qualitatively, solution gas drive, volatile-oil reservoirs act very similarly to their black-oil counterparts. One pronounced quantitative difference, however, is that volatile-oil reservoirs exhibit much greater peak producing GORs. The field example below illustrates this difference. This example considers a volatile-oil reservoir that exhibits a peak GOR of approximately 29,000 to 32,000 scf/STB. This GOR is considerably greater than the peak GOR for the example black oil of 6,700 scf/STB. Another difference between volatile- and black-oil reservoirs is that the former often exhibit slightly greater oil recoveries; however, there are numerous exceptions to this trend.

Field example

Cordell and Ebert[3] report the performance of a volatile-oil reservoir located in north-central Louisiana. Table 3 summarizes some of the pertinent reservoir data. This reservoir produced from the Smackover lime located at an approximate depth of 10,000 ft. The field was discovered in 1953 and was developed with 11 wells on 160-acre spacing. Jacoby and Berry[4] report on the fluid properties of this volatile oil. The standard PVT parameters in Table 4, which were developed from laboratory data with the EOS method, are applicable.

Table 5 summarizes the reservoir performance in terms of the cumulative oil production, cumulative gas production, and instantaneous producing GOR as a function of pressure. Table 5 includes the oil and gas recoveries as a percent of the OOIP and OGIP. These recoveries were based on the volumetric OOIP and OGIP estimates of 10.7 million STB and 31.1 Bscf, respectively.

Fig. 3 shows the reservoir performance in terms of pressure and producing GOR as a function of cumulative oil recovery. This figure qualitatively agrees with the theoretical results for the black oil in Fig. 1. A comparison confirms that volatile-oil reservoirs experience much higher producing GORs. For example, this volatile-oil reservoir reaches a peak GOR of 29,000 scf/STB (compared with 6,700 scf/STB for the black oil). This reservoir was produced to a low enough pressure to exhibit Stage 4, which is the period of declining GOR. The GOR began to decline at a reservoir pressure of approximately 800 psia.

Material balance analysis

A material balance analysis is performed routinely to confirm the suspected producing mechanism and to estimate the OOIP independently. The applicable material-balance equation for a solution gas drive reservoir is[5][6][7][8]

Vol5 page 0907 eq 003.png....................(1)

Vol5 page 0915 eq 001.png....................(2)

Eq. 2 is a simplification of Eq. 1 and assumes no initial free gas (Gfgi = 0). Because there is no initial free gas, Nfoi = N. If free gas is present initially, the material-balance methods for gas cap reservoirs should be applied (see material balance analysis of gas cap reservoirs). Eq. 2 also applies to waterdrives; however, if the following methods are applied to waterdrives, the water influx history must be reliably known. If the water-influx history is not known, then the methods on the material-balance analysis for waterdriving oil reservoirs page regarding waterdrives must be applied. If there is no water influx, then We = 0.

  • If a reservoir produces exclusively by solution gas drive with only supplemental connate-water expansion and pore-volume contraction, then Eq. 2 dictates that a plot of F vs. Eowf is a straight line, emanates from the origin, and has a slope equal to N. This observation is used to confirm the producing mechanism.
  • If water influx exists and if We is known, then an F-vs.-Eowf plot is replaced by a (FWe)-vs.-Eowf plot. Fig. 4 shows a (FWe)-vs.-Eowf plot for a volatile-oil reservoir. Once the OOIP is determined, the OGIP is given by G = RsiN.
  • If an F-vs.-Eowf plot is not a straight line, then another producing mechanism, such as a waterdrive or an initial gas cap, exists. The shape of the nonlinearity is important in diagnosing the true producing mechanisms. For instance, if the F-vs.-Eowf plot curves upward, this suggests that a waterdrive or an initial gas cap exists. 'Fig. 5 shows the effect of water influx or an initial gas cap on an F-vs.-Eowf plot.

The number of data points in an F-vs.-Eowf plot is usually limited by the number of average-reservoir-pressure measurements. Recall that F and Eowf are functions of pressure by means of the standard PVT parameters. If two or more data points (other than the origin) exist, then a mathematical criterion must be adopted to determine the "best" line though the data or the "best" estimate of N. If a least-squares criterion is adopted, then the OOIP estimate is[9]

Vol5 page 0916 eq 001.png....................(3)

where:

  • subscript j denotes the value at pressure pj
  • n is the total number of data points

Eq. 3 offers a strictly mathematical means to estimate the OOIP without constructing an F-vs.-Eowf plot. In general, however, a plot is recommended because it provides a visual means to assess the scatter of the data. The straightness of the data points is a measure of material balance and confirmation of the solution gas drive mechanism.

The composite expansivity Eowf implicitly includes and accounts for rock and connate-water expansion. Thus, the methods offered here are applicable equally to reservoirs in which rock and connate-water expansion are important. In practice, rock and connate-water expansion cannot be neglected unless the reservoir is saturated and the pressure is less than approximately 1,500 psia. These phenomena cannot be neglected while the reservoir is undersaturated because their combined effects are not negligible compared to oil expansion. For instance, the relative expansion of oil, rock, and water in an undersaturated west Texas black-oil reservoir was 72, 25, and 3%, respectively. This example also demonstrates that the connate-water expansion is normally insignificant and can be ignored. Not until the pressure falls below the bubblepoint and approximately 1,500 psia will the rock expansion be negligible compared to the net hydrocarbon expansion. If doubt persists as to whether it is safe to ignore rock and connate-water expansion, the safest approach is to include them. To include these phenomena, the rock and connate-water expansivities, Ef and Ew, must be calculated. Compaction drive reservoirs discusses experimental and empirical methods to estimate Ef. The connate-water expansivity is calculated from Eq. 4. This equation ignores dissolved hydrocarbon gases in the water. To include dissolved gases, the water expansivity is calculated from

Vol5 page 0906 eq 004.png....................(4)

Vol5 page 0917 eq 001.png....................(5)

where Btw is the two-phase water FVF and is given by

Vol5 page 0918 eq 001.png....................(6)

where Rsw is the dissolved gas/water ratio. [8]

Two common errors occur when applying a material-balance analysis to volatile-oil reservoirs.

  • First, an incorrect set of PVT parameters is used. This occurs if the volatile oil is subjected to a conventional DV test instead of a CVD or a specialized DV experiment that measures volatilized oil. The resulting set of PVT parameters will not reflect the true phase behavior. If this mistake occurs, the volatilized oil/gas ratio, Rv, will be omitted altogether and the resulting values of Bo and Rs will be erroneous and overestimated. Significant errors in these fluid properties will occur if appreciable volatilized oil exists. For example, the volatile oil in Table 4 yielded an erroneous initial oil FVF of 3.379 RB/STB and a dissolved GOR of 3,636 scf/STB (errors of approximately 25%) when it was subjected to a standard DV instead of a CVD.
  • The second error commonly occurs if the conventional or black-oil material-balance equation[10][11] is applied instead of the generalized equation in Eq. 7. The conventional material balance inherently ignores Rv. Both of these errors will cause the OOIP to be underestimated, which can be quite serious if the volatilized-oil content is appreciable.

Vol5 page 0906 eq 001.png....................(7)

Example: Volatile oil reservoir

Perform a material-balance analysis on the Louisiana volatile oil reservoir in the field example. Use the production data in Table 5 and the PVT data in Table 4 as necessary. Estimate the OOIP (million STB) and confirm the suspected solution gas drive producing mechanism if possible. Compare your OOIP estimate to the volumetric estimate of 10.7 million STB reported by Cordell and Ebert. [5]

Solution

To confirm the producing mechanism and estimate the OOIP, construct an F-vs.-Eowf plot. Because the lower pressure in Table 5 is less than 1,500 psia and below the bubblepoint, connate-water expansion and pore-volume contraction can be ignored. Thus, Eowf can be replaced by Eo where:

  • Eo = BtoBoi
  • Bto is given by Eq. 8

Vol5 page 0907 eq 001.png....................(8)

Vol5 page 0906 eq 002.png....................(9)

Table 6 tabulates the results of Bto and Eo as a function of pressure. For example, at p = 4,398 psia, evaluating Eqs. 8 and 9 yields

Vol5 page 0919 eq 001.png

and Eo = 2.864 – 2.704 = 0.160 RB/STB.

Vol5 page 0908 eq 001.png....................(10)

Vol5 page 0910 eq 003.png....................(11)

Vol5 page 0908 eq 003.png....................(12)

F is given by Eq. 10 when the reservoir is saturated and by Eq. 11 when the reservoir is undersaturated. For example, at p = 4,398 psia, evaluating Eq. 10 yields

Vol5 page 0919 eq 002.png

Table 6 tabulates the results at other pressures and the cumulative GOR, Rps = Gps/Np.

Fig. 4 shows a plot of F vs. Eo. The slope of this plot is 10.2 million STB, which is an estimate of the OOIP. This estimate agrees closely with the volumetric estimate of 10.7 million STB. The agreement of the volumetric and material-balance OOIP estimates, together with the straightness of the F-vs.-Eo plot, is strong evidence that this reservoir is producing exclusively by a solution gas drive mechanism.

If the volatilized oil was ignored and standard PVT parameters based on a conventional DV test were used, the material balance would yield an OOIP estimate of 8.2 million STB, or an error of 23%. Alternatively, if the volatilized oil was ignored and the conventional (black oil) material-balance equation were used instead of the generalized equation defined by Eqs. 1 through 12, the material balance would yield an OOIP of 9.09 million STB, or an error of 15%.

Nomenclature

Bg = gas FVF, RB/scf
Bo = oil FVF, RB/STB
Btg = two-phase gas FVF, RB/scf
Bto = two-phase oil FVF, RB/STB
Btw = two-phase water/gas FVF, RB/STB
Bw = water FVF, RB/STB
Ef = rock (formation) expansivity
Eg = gas expansivity, RB/scf
Egw = expansivity for McEwen method, RB/scf
Egwf = composite gas/water/rock FVF, RB/scf
Eo = oil expansivity, RB/STB
Eowf = composite oil/water/rock FVF, RB/STB
Ew = water expansivity, RB/STB
F = total fluid withdrawal, L3, RB
G = total original gas in place, L3, scf
Gfgi = initial free gas in place, L3, scf
Gi = cumulative gas injected, L3, scf
Gp = cumulative produced gas, L3, scf
N = total original oil in place, L3, STB
Nfoi = initial free oil in place, L3, STB
Np = cumulative produced oil, L3, STB
Rs = dissolved GOR, scf/STB
Rsw = dissolved-gas/water ratio, scf/STB
Rv = volatilized-oil/gas ratio, STB/MMscf
Swi = initial water saturation, fraction
Vp = reservoir PV, L3, RB
Vpi = initial reservoir PV, L3, RB
We = cumulative water influx, L3, RB
WI = cumulative injected water, L3, STB
Wp = cumulative produced water, L3, STB

References

  1. Society of Petroleum Engineers. 2001. QUICKSIM—A Modified Black-Oil Tank Model, User’s Guide. Richardson, Texas: SPE Software Catalog.
  2. Walsh, M.P. 2000. QUICKSIM—A Modified Black-Oil Tank Model, Version 1.6. Austin, Texas: Petroleum Recovery Research Inst.
  3. Cordell, J.C. and Ebert, C.K. 1965. A Case History Comparison of Predicted and Actual Performance of a Reservoir Producing Volatile Crude Oil. J Pet Technol 17 (11): 1291-1293. SPE-1209-PA. http://dx.doi.org/10.2118/1209-PA
  4. Jacoby, R.H. and Berry, V.J. Jr. 1957. A Method for Predicting Depletion Performance of a Reservoir Producing Volatile Crude Oil. Trans., AIME 210: 27.
  5. 5.0 5.1 Walsh, M.P. 1995. A Generalized Approach to Reservoir Material Balance Calculations. J Can Pet Technol 34 (1). PETSOC-95-01-07. http://dx.doi.org/10.2118/95-01-07
  6. Walsh, M.P. and Lake, L.W. 2003. A Generalized Approach to Primary Hydrocarbon Recovery. Amsterdam: Elsevier.
  7. Walsh, M.P., Ansah, J., and Raghavan, R. 1994. The New, Generalized Material Balance as an Equation of a Straight Line: Part 1 - Applications to Undersaturated, Volumetric Reservoirs. Presented at the Permian Basin Oil and Gas Recovery Conference, Midland, Texas, 16-18 March 1994. SPE-27684-MS. http://dx.doi.org/10.2118/27684-MS
  8. 8.0 8.1 Walsh, M.P. 1998. Discussion of Application of Material Balance for High-Pressure Gas Reservoirs, SPE J 402.
  9. Walsh, M.P. 1999. Effect of Pressure Uncertainty on Material-Balance Plots. Presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, 3-6 October 1999. SPE-56691-MS. http://dx.doi.org/10.2118/56691-MS
  10. Schilthuis, R.J. 1936. Active Oil and Reservoir Energy. Trans., AIME 118: 33.
  11. Dake, L.P. 1978. Fundamentals of Reservoir Engineering. Amsterdam: Elsevier Scientific Publishing Co.

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See also

Oil fluid characteristics

Oil fluid properties

Waterdrive reservoirs

PEH:Oil Reservoir Primary Drive Mechanisms