The Use of Rate-Transient-Analysis Modeling To Quantify Uncertainties in Commingled Tight Gas Production-Forecasting and Decline-Analysis Parameters in theAlberta Deep Basin
- Hongtao Luo (Shell) | Glenn Mahiya (Shell) | Stephen Pannett (Shell) | Philip H. Benham (Shell)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- May 2014
- Document Type
- Journal Paper
- 209 - 219
- 2014.Society of Petroleum Engineers
- 5.8.1 Tight Gas, 5.6.9 Production Forecasting
- tight gas, commingled, rate transient analysis, production forecasting
- 7 in the last 30 days
- 603 since 2007
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The evaluation of expected ultimate recovery (EUR) for tight gas wells has generally relied upon the Arps equation for decline-curve analysis (DCA) as a popular approach. However, it is typical in tight gas reservoirs to have limited production history that has yet to reach boundary-dominated flow because of the low permeability of such systems. Commingled production makes the situation even more complicated with multiboundary behavior. When suitable analogs are not available, rate-transient analysis (RTA) can play an important role to justify DCA assumptions for production forecasting. The Deep-basin East field has been developed with hydraulically fractured vertical wells through commingled production from multiple formations since 2002. To evaluate potential of this field, DCA type curves for various areas were established according to well performance and geological trending. Multiple-segment DCA methodology demonstrated reasonable forecasts, in which one Arps equation is used to describe the rapidly decreasing transient period in early time and another equation is used for boundary-dominated flow. However, a limitation of this approach is the uncertainty of the forecast in the absence of extended production data because the EUR can be sensitive to adjustments in some assumed DCA parameters of the second segment. In this paper, we used RTA to assess reservoir and fracture properties in multiple layers and built RTA-type well models around which uncertainty analyses were performed. The distributions of the model properties were then used in Monte Carlo analysis to forecast production and define uncertainty ranges for EUR and DCA parameters. The resulting forecasts and EUR distribution from RTA modeling generally support the DCA assumptions used for the type curves for corresponding areas of the field. The study also showed how the contribution from the various commingled layers changes with time. The proposed workflow provides a fit for-purpose way to quantify uncertainties in tight gas production forecasting, especially for cases when production history is limited and field-level numerical simulation is not practicable.
|File Size||2 MB||Number of Pages||11|
Cinco-Ley, H. and Samaniego, F.V. 1978. Transient Pressure Behavior for Fractured Wells. Paper SPE 7490 presented at the SPE 53rd Annual Technical Conference and Exhibition, Houston, Texas, 1–3 October.
Cinco-Ley, H., Samaniego, F.V. and Dominguez, N.A. 1978. Transient Pressure Behavior for a Well With a Finite Conductivity Vertical Fracture. SPE J. 18 (4): 253–264. http://dx.doi.org/10.2118/6014-PA.
Currie, S.M., Ilk, D. and Blasingame, T.A. 2010. Application of the “Continuous Estimation of Ultimate Recovery” Methodology to Estimate Reserves in Unconventional Reservoirs. Paper SPE 138155 presented at the Canadian Unconventional Resources & International Petroleum Conference, Calgary, Alberta, Canada, 19–21 October. http://dx.doi.org/10.2118/138155-MS.
Fall, A., Eichhubl, P., Cumella, S.P., et al. 2012. Testing the Basin-Centered Gas Accumulation Model Using Fluid Inclusion Observations: Southern Piceance Basin, Colorado. AAPG Bull. 96 (12): 2297–2318. http://dx.doi.org/10.1306/05171211149.
Ilk, D., Rushing, J.A. and Blasingame, T.A. 2011. Integration of Production analysis and Rate-Time Analysis via Parametric Correlations—Theoretical Considerations and Practical Applications. Paper SPE 140556 presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, 24–26 January. http://dx.doi.org/10.2118/140556-MS.
Ilk, D., Rushing, J.A., Perego, A.D., et al. 2008. Exponential vs. Hyperbolic Decline in Tight Gas Sands: Understanding the Origin and Implications for Reserve Estimates Using Arps’ Decline Curves. Paper SPE 116731 presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, 21–24 September. http://dx.doi.org/10.2118/116731-MS.
Laubach, S.E. 2003. Practical Approaches to Identifying Sealed and Open Fractures. AAPG Bull. 87 (4): 561–579. http://dx.doi.org/10.1306/11060201106.
Law, B.E. 2002. Basin-Centered Gas Systems. AAPG Bull. 86 (11): 1891–1919. http://dx.doi.org/10.1306/61EEDDB4-173E-11D7-8645000102C1865D.
McMaster, G.E. 1981. Gas Reservoirs, Deep Basin, Western Canada. J. Cdn. Pet. Tech. 20 (3): 62–66. http://dx.doi.org/10.2118/81-03-04.
Olson, J.E., Laubach, S.E. and Lander, R.H. 2009. Natural Fracture Characterization in Tight Gas Sandstones: Integrating Mechanics and Diagenesis. AAPG Bull. 93 (11): 1535–1549. http://dx.doi.org/10.1306/08110909100.
Spivey, J.P. 2006. Estimating Layer Properties for Wells in Multilayer Low-Permeability Gas Reservoirs by Automatic History Matching Production and Production Log Data. Paper SPE 100509 presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, 15–17 May. http://dx.doi.org/10.2118/100509-MS.
Topaze, version 4.12. 2010. Houston, Texas, KAPPA Engineering.
Valko, P.P. and Lee, W.J. 2010. A Better Way to Forecast Production From Unconventional Gas Wells. Paper SPE 134231 presented at the SPE Annual Technical Conference and Exhibition, Florence, Italy, 19–22 September. http://dx.doi.org/10.2118/134231-MS.