Deconvolution of Pressure and Rate Data From Gas Reservoirs With Significant Pressure Depletion
- Michael M. Levitan (BP plc) | Mike R. Wilson (Well-Test Solutions)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- September 2012
- Document Type
- Journal Paper
- 727 - 741
- 2012. Society of Petroleum Engineers
- 4.1.4 Gas Processing, 3 Production and Well Operations, 5.2.1 Phase Behavior and PVT Measurements
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- 638 since 2007
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Deconvolution is a technique for converting the pressure and rate data obtained from a well operating under variable-rate conditions into a much simpler form of constant-rate drawdown-pressure response function from the same well. However, deconvolution should only be applied to pressure and rate data that result from fluid flow in the reservoir that is governed by a linear set of equations. In gas reservoirs, the fluid-flow problem is nonlinear because the gas properties are strongly dependent on pressure. In some specific situations, this gas-flow problem can be linearized by the use of a pseudopressure transform that allows deconvolution to be successfully applied to those data. However, there are situations in which a pseudopressure transform alone does not fully linearize the gas-flow problem, and the resulting data will exhibit nonlinear behavior caused by the pressure dependence of the gas compressibility. Direct application of deconvolution to such data will produce erroneous results.
This paper presents an enhancement of the deconvolution algorithm that allows it to be used with pressure data affected by a nonlinear pressure-dependent compressibility. We discuss the detailed considerations for this enhancement of the deconvolution algorithm and demonstrate its performance on simulated test data exhibiting this nonlinear behavior. We also demonstrate the application of this enhanced deconvolution algorithm to a set of pressure data from a gas well fitted with a permanent gauge and covering the first 3 years of production from that well.
|File Size||1 MB||Number of Pages||15|
Agarwal, R.A. 1979. "Real Gas Pseudo-Time"--A New Function for PressureBuildup Analysis of MHF Gas Wells. Paper SPE 8279 presented at the SPE AnnualTechnical Conference and Exhibition, Las Vegas, Nevada, USA, 23-26 September.http://dx.doi.org/10.2118/8279-MS.
Al-Hussainy, R., Ramey, H.J. Jr., and Crawford, P.B. 1966. The Flow of RealGases Through Porous Media. J Pet Technol 18 (5): 624-636.SPE-1243-A-PA. http://dx.doi.org/10.2118/1243-A-PA.
Barenblatt, G.I., Entov, V.M., and Ryzhik, V.M. 1990. Theory of FluidFlows Through Natural Rocks. Dordrecht, The Netherlands: Kluwer AcademicPublishers.
Bourgeois, M.J. and Wilson, M.R. 1996. Additional Use of Well TestAnalytical Solutions for Production Prediction. Paper SPE 36820 presented atthe European Petroleum Conference, Milan, Italy, 22-24 October. http://dx.doi.org/10.2118/36820-MS.
Dake, L.P. 1978. Fundamentals of Reservoir Engineering, No. 8, 25-27.Amsterdam: Developments in Petroleum Science, Elsevier Science BV.
Houzé, O.P., Tauzin, E., and Allain, O.F. 2010. New Method to DeconvolveWell-Test Data Under Changing Well Conditions. Paper SPE 132478 presented atthe SPE Annual Technical Conference and Exhibition, Florence, Italy, 19-22September. http://dx.doi.org/10.2118/132478-MS.
Kamal, M.M. 2009. Transient Well Testing, No. 23, Sec. 7, 171-177.Richardson, Texas: Monograph Series, SPE.
Lee, W.J. and Holditch, S.A. 1982. Application of Pseudotime to Buildup TestAnalysis of Low-Permeability Gas Wells With Long-Duration Wellbore StorageDistortion. J Pet Technol 34 (12): 2877-2888. SPE-9888-PA.http://dx.doi.org/10.2118/9888-PA.
Leibenzon, L.S. 1934. Mechanics in Oil Production, Part II (inRussian). Moscow, Russia: Gorgeonefteizdat.
Levitan, M.M. 2005. Practical Application of Pressure/Rate Deconvolution toAnalysis of Real Well Tests. SPE Res Eval & Eng 8 (2):113-121. SPE-84290-PA. http://dx.doi.org/10.2118/84290-PA.
Levitan, M.M. 2007. Deconvolution of Multiwell Test Data. SPE J. 12 (4): 420-428. SPE-102484-PA. http://dx.doi.org/10.2118/102484-PA.
Levitan, M.M., Crawford, G.E., and Hardwick, A. 2006. PracticalConsiderations for Pressure-Rate Deconvolution of Well-Test Data. SPE J. 11 (1): 35-47. SPE-90680-PA. http://dx.doi.org/10.2118/90680-PA.
Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P.1992. Numerical Recipes in FORTRAN: The Art of Scientific Computing,second edition, Chap. 9. Cambridge, Massachusetts: Cambridge UniversityPress.
Rahman, N.M.A., Mattar, L., and Zaoral, K. 2006. A New Method forComputing Pseudo-Time for Real Gas Flow Using the Material Balance Equation.J Can Pet Technol 45 (10): 36-44. JCPT Paper No. 06-10-03.http://dx.doi.org/10.2118/06-10-03.
von Schroeter, T., Hollaender, F., and Gringarten, A.C. 2001.Deconvolution of Well Test Data as a Nonlinear Total Least Squares Problem.Paper SPE 71574 presented at the SPE Annual Technical Conference andExhibition, New Orleans, 30 September-3 October. http://dx.doi.org/10.2118/71574-MS.
von Schroeter, T., Hollaender, F., and Gringarten, A.C. 2004.Deconvolution of Well-Test Data as a Nonlinear Total Least-Squares Problem.SPE J. 9 (4): 375-390. SPE-77688-PA. http://dx.doi.org/10.2118/77688-PA.
Whittle, T.M. and Gringarten, A.C. 2008. The Determination of Minimum TestedVolume From the Deconvolution of Well Test Pressure Transients. Paper SPE116575 presented at the SPE Annual Technical Conference and Exhibition, Denver,21-24 September. http://dx.doi.org/10.2118/116575-MS.