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Reserves estimation of tight gas reservoirs

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As defined by the U.S. Federal Energy Regulatory Commission (U.S. FERC), low-permeability (“tight”) gas reservoirs have an average in-situ permeability of 0.1 md or less. Others have placed the upper limit at 1 md. Estimates of ultimate recovery from these resources vary widely and depend chiefly on assumptions of wellhead gas price.

Consideration of reserves estimation

Methods for estimating gas reserves in moderate- to high-permeability reservoirs are unreliable in very-low-permeability reservoirs. The unreliability can be attributed to the geologic setting in which these reservoirs occur and the completion methods required to make them commercial. In general, their geologic setting is characterized by:

  • A high degree of permeability heterogeneity
  • Lateral discontinuities in apparently blanket sands
  • Stratigraphic, rather than structural, traps
  • Complex mineralogy, frequently with high-grain-density minerals randomly dispersed throughout the section as well as water-sensitive clays.

These attributes make it very difficult to determine porosity and interstitial water saturation by conventional log and core analysis.[1][2][3][4][5] Petrophysical properties measured at ambient conditions (e.g., k and Sw) differ substantially from those at reservoir conditions, and corrections for formation compressibility are subject to considerable uncertainty. For example, permeabilities can be as much as two orders of magnitude greater at ambient conditions than at reservoir conditions. These problems and poor lateral continuity lead to substantial uncertainties in volumetric estimates of gas-in-place (GIP). In many cases, it is impossible to distinguish between commercial and noncommercial intervals from log analysis alone. Drillstem tests rarely provide useful information because formations often are damaged during drilling.

Massive hydraulic fracturing usually is required to obtain commercial flow rates. Despite more than 35 years of experience with fracturing technology, however, the industry remains unable to design a treatment and predict the results with high confidence when relying solely on analytical methods.[6][7] Typically, operators rely on analytical models coupled with analogy.

Along the US Gulf Coast, tight-gas accumulations frequently occur in geopressured sections.[8][9] In this environment, understanding the influence of reservoir stress on rock properties is important for differentiating between productive and nonproductive formations.

Over the life of a well completed in low-permeability gas reservoirs, the gas production rate typically exhibits a hyperbolic decline,[10][11] with apparent b values generally >1. In addition to decline curve analysis, empirical log-log rate/time models might provide useful short-term information for such wells—before the onset of significant pressure depletion. The following equations, developed in the 1980s for more than 2,500 then-new wells in the U.S. Rocky Mountains, have been used to estimate flow rates (Eqs. 1 and 2) and near-term reserves (Eqs. 3 and 4) for damaged fracture flow[12]:

RTENOTITLE(Eq. 1)

RTENOTITLE(Eq. 2)

RTENOTITLE(Eq. 3)

and

RTENOTITLE(Eq. 4)

where KA and KB are coefficients calculated during fitting these equations.

For an undamaged, fractured well, initial values of n should equal approximately –0.5. Because of damage, however, initial n values as small as –0.15 had been observed in the wells studied; the average was –0.34. With the onset of depletion, n decreases to –1.0 or more.[13][14]

Eqs. 1 and 3 can be used to account for the effects of a damaged fracture by using the field-observed value of n for each such well. Depending on circumstances, however, Eqs. 2 and 4 might provide a better fit to the observed data.

Reserves estimates (RE) of gas from some of these reservoirs vs. kgh is shown in Fig. 1[15]. Well spacing ranges from approximately 160 to 320 acres. For kh of less than approximately 50 md-ft, there is a decrease in RE, albeit erratically so.

Because of the high degree of permeability heterogeneity, drainage areas of individual wells vary widely. In the Green River basin (US), for example, effective drainage areas reportedly have ranged from approximately 100 to 640 acres.[16] Depending on economics, such situations can offer opportunities for significant increase in reserves by infill drilling.

Nomenclature

Gp = cumulative gas production, scf
KA = coefficient
KB = coefficient
n = variable
qg = gas production rate, scf/month
t = time, months or years

References

  1. Brown, C.A., Erbe, C.B., and Crafton, J.W. 1981. A Comprehensive Reservoir Model of the Low Permeability Lewis Sands in the Hay Reservoir Area, Sweetwater County, Wyoming. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 4–7 October. SPE-10193-MS. http://dx.doi.org/10.2118/10193-PA.
  2. Kukal, G.C., Biddison, C.L., Hill, R.E. et al. 1983. Critical Problems Hindering Accurate Log Interpretation of Tight Gas Sand Reservoirs. Presented at the SPE/DOE Low Permeability Gas Reservoirs Symposium, Denver, Colorado, 14-16 March 1983. SPE-11620-MS. http://dx.doi.org/10.2118/11620-MS.
  3. Spencer, C.W. 1985. Geologic Aspects of Tight Gas Reservoirs in the Rocky Mountain Region. J Pet Technol 37 (7): 1308–1314. SPE-11647-PA. http://dx.doi.org/10.2118/11647-PA.
  4. Witherbee, L.J., Godfrey, R.D., and Dimelow, T.E. 1983. Predicting Turbidite-Contourite Reservoir Intervals in Tight Gas Sands: A Case Study From the Mancos B Sandstone. Presented at the SPE/DOE Low Permeability Gas Reservoirs Symposium, Denver, Colorado, 14-16 March 1983. SPE-11609-MS. http://dx.doi.org/10.2118/11609-MS.
  5. Lewis, D.J. and Perrin, J.D. 1992. Wilcox Formation Evaluation: Improved Procedures for Tights Gas-Sand Evaluation. J Pet Technol 44 (6): 724-730. SPE-20570-PA. http://dx.doi.org/10.2118/20570-PA.
  6. Kazemi, H. 1982. Low-Permeability Gas Sands. J Pet Technol 34 (10): 2229-2232. SPE-11330-PA. http://dx.doi.org/10.2118/11330-PA.
  7. Veatch, R.W.J. 1983. Overview of Current Hydraulic Fracturing Design and Treatment Technology—Part 1. J Pet Technol 35 (4): 677-687. SPE-10039-PA. http://dx.doi.org/10.2118/10039-PA.
  8. Robinson, B.M., Holditch, S.A., and Lee, W.J. 1986. A Case Study of the Wilcox (Lobo) Trend in Webb and Zapata Counties, TX. J Pet Technol 38 (12): 1355-1364. SPE-11600-PA. http://dx.doi.org/10.2118/11600-PA.
  9. Lewis, D.J. and Perrin, J.D. 1992. Wilcox Formation Evaluation: Improved Procedures for Tights Gas-Sand Evaluation. J Pet Technol 44 (6): 724-730. SPE-20570-PA. http://dx.doi.org/10.2118/20570-PA.
  10. Stewart, P.R. 1970. Low-Permeability Gas Well Performance At Constant Pressure. J Pet Technol 22 (9): 1149-1156. http://dx.doi.org/10.2118/2604-PA.
  11. Brown, C.A., Erbe, C.B., and Crafton, J.W. 1981. A Comprehensive Reservoir Model of the Low Permeability Lewis Sands in the Hay Reservoir Area, Sweetwater County, Wyoming. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 4–7 October. SPE-10193-MS. http://dx.doi.org/10.2118/10193-PA.
  12. Hale, B.W. 1986. Analysis of Tight Gas Well Production Histories in the Rocky Mountains. SPE Prod Eng 1 (4): 310-322. SPE-11639-PA. http://dx.doi.org/10.2118/11639-PA.
  13. Hale, B.W. 1981. A Type Curve Approach to Reserves for the Big Piney Gas Field. Presented at the SPE/DOE Low Permeability Gas Reservoirs Symposium, Denver, Colorado, 27-29 May 1981. SPE-9840-MS. http://dx.doi.org/10.2118/9840-MS.
  14. Harlan, L.E. 1966. A Method for Determining Recovery Factors in Low Permeability Gas Reservoirs. Presented at the 41st Annual Meeting of the Society of Petroleum Engineers of AIME, Dallas, Texas, 2-5 October. http://dx.doi.org/10.2118/1555-MS.
  15. 15.0 15.1 Cronquist, C. 2001. Estimation and Classification of Reserves of Crude Oil, Natural Gas, and Condensate. Richardson, Texas: SPE.
  16. Cipolla, C.L. and Kyte, D.G. 1992. Infill Drilling in the Moxa Arch: A Case History of the Frontier Formation. Presented at the SPE Annual Technical Conference and Exhibition, Washington, D.C., 4-7 October 1992. SPE-24909-MS. http://dx.doi.org/10.2118/24909-MS.

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See also

PEH:Estimation_of_Primary_Reserves_of_Crude_Oil,_Natural_Gas,_and_Condensate

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