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Difference between revisions of "Reserves estimation of thin oil columns"

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Revision as of 12:00, 16 July 2015

Thin oil columns overlain by free gas and underlain by water pose difficult problems in well spacing and completion method, production policy, and reserves estimation. In this context, “thin” is a relative term. Whether an oil column is considered thin depends on costs to drill and produce the accumulation.

For example, in the Bream field (Australia Bass Strait, 230 ft water depth), 44 ft was considered thin,[1] whereas in the Troll field (offshore Norway, 980 ft water depth), 79 ft was considered thin.[2] Onshore U.S.A., 20 ft is considered thin. Irrgang[3] takes a pragmatic approach, defining thin oil columns as those that “will cone both water and gas when produced at commercial rates.”

Reserve estimation

The overall reserve estimate of oil from such accumulations can be influenced by well spacing and completion method and by gas-cap management policy. Economics, though, tend to be controlled by individual well recoveries and production capacities, rather than by average reserve estimate (RE) from the reservoir; thus, development planning focuses on the economics of individual wells—the cost to drill, complete, and operate vs. the oil rate/time profile. Ultimate oil recovery from individual wells tends to be controlled by a number of factors, including the gross thickness of the oil column and the horizontal/vertical permeability ratio in the well’s drainage area. This ratio might vary significantly over the areal extent of the reservoir, depending on the depositional environment of the reservoir rock. Experience with such reservoirs indicates that this parameter typically is underestimated, causing underestimates of oil recovery. Localized shale breaks might contribute to suppressed coning of gas and/or water if wells can be completed to take advantage of these heterogeneities.

From limited data from conventional well completions in several such fields in Australia, Irrgang[3] developed the relation

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

where the bracketed term is a correlating parameter.

Irrgang does not provide details on estimation of kH; the median permeability probably is appropriate. Irrgang has observed, “a higher power may be appropriate for permeability—possibly even 2.”* The vertical/horizontal permeability ratio, kV/kH, influences volumetric sweep efficiency in bottom waterdrive reservoirs. The absence of this term in Irrgang’s correlation is puzzling, but might be because of measurement difficulties.

Depending on the water/oil mobility ratio and the horizontal/vertical permeability ratio, oil wells completed in this type of accumulation might exhibit coning of the overlying gas and/or coning of the underlying water early in life. These phenomena might cause rapidly increasing gas-oil ratio (GOR) or water-oil ratio (WOR) and relatively short economic life; thus, how efficiently this type of accumulation can be exploited depends on the degree to which premature coning of gas and/or water can be avoided by appropriate completion methods and production practices. In one of the earliest published analyses of this problem, Van Lookeren[4] advocated perforating below the initial oil-water contact (OWC) to minimize gas coning; however, the simple isotropic model used in his analysis essentially negates the practical application of this approach. In the last few years, horizontal drainholes have been used to develop these accumulations.[5] Because this technology is still evolving, consider apparent successes in analogous reservoirs with caution.

Determination of optimum well spacing and estimation of oil reserves in such reservoirs is subject to substantial uncertainty, at least until a reasonably well-defined performance trend has been established for each well. Before performance trends are established, however, reserves typically are estimated using a combination of volumetric mapping and analogy or analytical methods. In this context, computer simulation can be extremely useful in establishing sensitivity of RE to various assumed scenarios, thereby helping to determine optimum well spacing and commerciality. Potential analogs are provided in Table 1.[3]

Critical parameters

A critical review of the more than 50 years of literature[6][7][8][9][10][11] makes apparent that the industry has yet to develop a general treatment of coning that includes the influences of gas cap, aquifer influx, and other relevant parameters. For example, some authors investigate the problem of coning in the presence of an inactive aquifer, which is analogous to the classic coning problem first discussed by Muskat and Wyckoff,[6] whereas others investigate it in the presence of an active aquifer. Clearly, the critical rate to avoid water coning would be less in the presence of an active aquifer than in the presence of an inactive aquifer, other factors being the same.

In addition to aquifer strength, another critical parameter to apply the correlations in the selected literature[6][7][8][9][10][11] is the horizontal/vertical permeability ratio over each well’s drainage area. Laboratory measurements of vertical and horizontal permeability of small core samples are inadequate for estimating this parameter. In theory, vertical interference testing or vertical pulse testing can determine this parameter, as discussed by Earlougher,[12] but the test procedure involves two sets of perforations separated by a packer, an expense operators might be reluctant to incur. Another possible approach for wells exhibiting coning is computer simulation to establish the horizontal/vertical permeability ratio that yields an acceptable match to observed behavior. Whether results from a few such wells would apply to all wells in the reservoir depends on the depositional environment of the reservoir formation and the degree of lateral heterogeneity; however, it is unlikely. It might be more practical to test wells at gradually increasing rates to determine a maximum rate at which each well can be produced without coning.

In the presence of a strong aquifer and a gas cap, the combination of water encroachment and gas-cap coning might cause displacement of part of the oil column into the gas cap. Depending on the size of the initial gas cap and the degree of gas-cap voidage, significant volumes of oil might be lost. In some cases, this loss might be minimized or avoided by injecting the produced free gas into the gas cap to maintain constant gas-cap volume.


* Personal communication with H.H. Irrgang, Command Petroleum Holdings (December 1994).

Nomenclature

Bo = formation volume factor, oil, RB/STB
ht = gross oil column thickness
kH = horizontal permeability
n = variable
Npaw = cumulative oil production, well, at abandonment, STB
Rng = net-to-gross pay ratio, dimensionless
Sor = residual oil saturation, fraction
Sw = water saturation, fraction
μo = oil viscosity, general, cp
Ф = porosity, general, fraction

References

  1. Sulaiman, S. and Bretherton, T.A. 1989. Thin Oil Development in the Bream Field. Presented at the SPE Asia-Pacific Conference, Sydney, Australia, 13-15 September 1989. SPE-19493-MS. http://dx.doi.org/10.2118/19493-MS.
  2. Seines, K., Lien, S.C., and Haug, B.T. 1994. Troll Horizontal Well Tests Demonstrate Large Production Potential From Thin Oil Zones. SPE Res Eng 9 (2): 133-139. SPE-22373-PA. http://dx.doi.org/10.2118/22373-PA.
  3. 3.0 3.1 3.2 Irrgang, H.H. 1994. Evaluation and Management of Thin Oil Column Reservoirs in Australia. APEA J. 1: 64.
  4. Lookeren, J.V. 1965. Oil Production From Reservoirs With an Oil Layer Between Gas and Bottom Water in the Same Sand. J Pet Technol 17 (3): 354-357. http://dx.doi.org/10.2118/1063-PA.
  5. Sognesand, S. 1997. Reservoir Management of the Oseberg Field During Eight Years' Production. Presented at the Offshore Europe, Aberdeen, United Kingdom, 9-12 September 1997. SPE-38555-MS. http://dx.doi.org/10.2118/38555-MS.
  6. 6.0 6.1 6.2 Muskat, M. and Wycokoff, R.D. 1935. An Approximate Theory of Water-coning in Oil Production. Trans. of AIME 114 (1): 144-163. http://dx.doi.org/10.2118/935144-G.
  7. 7.0 7.1 Chierici, G.L., Ciucci, G.M., and Pizzi, G. 1964. A Systematic Study of Gas and Water Coning By Potentiometric Models. J Pet Technol 16 (8): 923–929. SPE-871-PA. http://dx.doi.org/10.2118/871-PA.
  8. 8.0 8.1 Bournazel, C. and Jeanson, B. 1971. Fast Water-Coning Evaluation Method. Presented at the Fall Meeting of the Society of Petroleum Engineers of AIME, New Orleans, 3-6 October. SPE-3628-MS. http://dx.doi.org/10.2118/3628-MS.
  9. 9.0 9.1 Kuo, M.C.T. 1983. A Simplified Method for Water Coning Predictions. Presented at the SPE Annual Technical Conference and Exhibition, San Francisco, California, 5–8 October. SPE-12067-MS. http://dx.doi.org/10.2118/12067-MS.
  10. 10.0 10.1 Kuo, M.C.T. 1989. Correlations Rapidly Analyze Water Coning. Oil & Gas J. (October): 77.
  11. 11.0 11.1 Høyland, L.A., Papatzacos, P., and Skaeveland, S.M. 1989. Critical Rate for Water Coning: Correlation and Analytical Solution. SPE Res Eng 4 (4): 495–502. SPE-15855-PA. http://dx.doi.org/10.2118/15855-PA.
  12. Earlougher, R.C. Jr. 1977. Advances in Well Test Analysis, Vol. 5. Richardson, Texas: Monograph Series, SPE.

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See also

PEH:Estimation_of_Primary_Reserves_of_Crude_Oil,_Natural_Gas,_and_Condensate

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