Analysis of Production History for Unconventional Gas Reservoirs With Statistical Methods
- Srimoyee Bhattacharya (University of Houston) | Michael Nikolaou (University of Houston)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2013
- Document Type
- Journal Paper
- 878 - 896
- 2013. Society of Petroleum Engineers
- 5.5.8 History Matching, 7.6.6 Artificial Intelligence
- 6 in the last 30 days
- 1,200 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Unconventional gas resources have dramatically changed the future energylandscape. Developing these resources involves substantial risk. Such risk canbe mitigated if information gathered at initial stages of the development of afield is used efficiently and effectively to guide future development. Avariety of tools--such as decline-curve analysis (DCA), type-curve analysis,simulator history matching, and artificial intelligence (AI)--is used to thateffect. These tools accomplish partially overlapping but different tasks.Additional tools that could not only facilitate the analysis of historical databut also guide future development would be of value. In this work, we proposean efficient methodology that can use historical production data from existingwells to answer questions such as the following: Which wells will behavesimilarly? Which wells will behave differently from each other or from standardexpectations? Which factors will contribute to these differences? How can datafrom existing wells be used to anticipate the performance of new wells? Theproposed methodology relies on standard principal component analysis (PCA) andprincipal-component regression (PCR). The application of PCA to historicalproduction data from twelve wells in the Holly Branch field quickly identifiedwells with distinct behavior. The subsequent investigation of pressure and thecompletion data for these wells revealed reasons for such distinct behavior.Finally, a simple linear model was built with PCR, with good ability to predictproduction from new wells, as assessed through cross-validation. The value ofthe efficiency offered by the proposed methodology would be much higher forlarger data sets, for which manual analysis of production data is morecumbersome.
|File Size||2 MB||Number of Pages||19|
Agarwal, R.G., Gardner, D.C., Kleinsteiber, S.W. et al. 1999. Analyzing WellProduction Data Using Combined-Type-Curve and Decline-Curve Analysis Concepts.SPE Res Eval & Eng 2: 26-28. http://dx.doi.org/10.2118/579156-PA.
Ahmad, T. 2006. Reservoir Engineering Handbook. Houston, Texas: GulfProfessional Publishing.
Amini, S., Ilk, D., and Blasingame, T.A. 2007. Evaluation of the EllipticalFlow Period for Hydraulically-Fractured Wells in Tight Gas Sands--TheoreticalAspects and Practical Considerations. Paper SPE 106308 presented at the SPEHydraulic Fracturing Technology Conference, College Station, Texas, 29-31January. http://dx.doi.org/10.2118/106308-MS.
Anderson, D.M. and Liang, P. 2011. Quantifying Uncertainty in Rate TransientAnalysis for Unconventional Gas Reservoirs. Paper SPE 145088 presented at theSPE Americas Unconventional Gas Conference and Exhibition. Society of PetroleumEngineers, The Woodlands, Texas, 14-16 June. http://dx.doi.org/10.2118/145088-MS.
Andreev, A. and Roberts, T. 2012. New Challenge for the Industry, GreatOpportunities for YPs. The Way Ahead 8 (1).
Aoudia, K., Miskimins, J., Harris, N.B. et al. 2010. Statistical Analysis ofthe Effects of Mineralogy on Rock Mechanical Properties of the Woodford Shaleand the Associated Impacts for Hydraulic Fracture Treatment Design. Paper 1-303presented at the US Rock Mechanics Symposium and US-Canada Rock MechanicsSymposium, Salt Lake City, Utah, 27-30 June.
Araya, A. and Ozkan, E. 2002. An Account of Decline-Type-Curve Analysis ofVertical, Fractured, and Horizontal Well Production Data. Paper SPE 77690presented at the Annual Technical Conference and Exhibition, San Antonio,Texas, 29 September-2 October. http://dx.doi.org/10.2118/77690-MS.
Arnold, R. and Darnell, J.L. 1919. Manual for the Oil and Gas IndustryUnder the Revenue Act of 1918. Washington, DC: Treasury Department--UnitedStates Internal Revenue Service (Creator).
Arps, J.J. 1945. Analysis of Decline Curves.
Bhattacharya, S. and Nikolaou, M. 2011. Using Data From Existing Wells ToPlan New Wells in Unconventional Gas Field Development. Paper SPE 147658presented at the Canadian Unconventional Resources Conference, Calgary,Alberta, Canada, 15-17 November. http://dx.doi.org/10.2118/147658-MS.
Blasingame, T.A. and Rushing, J.A. 2005. A Production-Based Method forDirect Estimation of Gas-in-Place and Reserves. Paper SPE 98042 presented atthe SPE Eastern Regional Meeting, Morgantown, West Virginia, 14-16 September.http://dx.doi.org/10.2118/98042-MS.
Bravo, C., Saputelli, L., Rivas, F. et al. 2012. State-of-the-ArtApplication of Artificial Intelligence and Trends in the E&P Industry: ATechnology Survey. Paper SPE 150314 presented at the SPE Intelligent EnergyInternational Meeting, Utrecht, The Netherlands, 27-29 March. http://dx.doi.org/10.2118/150314-MS.
Carter, R.D. 1985. Type Curves for Finite Radial and Linear Gas-FlowSystems: Constant-Terminal-Pressure Case. SPE J. 25 (5):719-728. http://dx.doi.org/10.2118/12917-PA.
Chaudhri, M.M. 2012. Numerical Modeling of Multifracture Horizontal Well forUncertainty Analysis and History Matching: Case Studies From Oklahoma and TexasShale Gas Wells. Paper SPE 153888 at the Western Regional Meeting, Bakersfield,California, 21-23 March. http://dx.doi.org/10.2118/153888-MS.
Cheng, Y., McVay, D.A., and Lee, W.J. 2009. A Practical Approach forOptimization of Infill Well Placement in Tight Gas Reservoirs. J. NaturalGas Sci. Eng. 1 (6): 165-220. http://dx.doi.org/10.1016/j.jngse.2009.10.004.
Clarkson, C.R., Bustin, R.M., and Seidle, J.P. 2006. Production DataAnalysis of Single-Phase (Gas) CBM Wells. Paper SPE 100313 presented at the GasTechnology Symposium, Calgary, Alberta, Canada, 15-17 May. http://dx.doi.org/10.2118/100313-MS.
Clarkson, C.R., Bustin, R.M. and Seidle, J.P. 2007a. Production-DataAnalysis of Single-Phase (Gas) CBM Wells. SPE Res Eval & Eng 10 (3): 312-331. http://dx.doi.org/10.2118/100313-PA.
Clarkson, C.R., Jordan, C.L., Gierhart, R.R. et al. 2007b. Production DataAnalysis of CBM Wells. Paper SPE 107705 presented at the Rocky Mountain Oil andGas Technology Symposium, Denver, Colorado, 16-18 April. http://dx.doi.org/10.2118/107705-MS.
Clarkson, C.R., Jordan, C.L., Gierhart, R.R. et al. 2008. Production DataAnalysis of Coalbed-Methane Wells. SPE Res Eval & Eng 11 (2): 311-325. http://dx.doi.org/10.2118/107705-PA.
Clarkson, C.R., Jordan, C.L., Ilk, D. et al. 2009. Production Data Analysisof Fractured and Horizontal CBM Wells. Paper SPE 125929 presented at theEastern Regional Meeting, Charleston, West Virginia, 23-25 September. http://dx.doi.org/10.2118/125929-MS.
Cutler, W.W. 1924. Estimation of Underground Oil Reserves by Oil-WellProduction Curves. Vol. 228. US Bureau of Mines, Department of theInterior, Government Printing Office.
Doublet, L.E., Pande, P.K., McCollum, T.J. et al. 1994. Decline CurveAnalysis Using Type Curves--Analysis of Oil Well Production Data Using MaterialBalance Time: Application to Field Cases. Paper SPE 28688 presented at thePetroleum Conference and Exhibition of Mexico, Veracruz, Mexico, 10-13 October.http://dx.doi.org/10.2118/28688-MS.
Doveton, J.H. 1994. Geologic Log Analysis Using Computer Methods.Tulsa, Oklahoma: The American Association of Petroleum Geologists.
Economides, M.J. and Nikolaou, M. 2011. Technologies for Oil and GasProduction: Present and Future. AIChE J. 57 (8): 1974-1982.http://dx.doi.org/10.1002/aic.12714.
EIA (Energy Information Administration). 2012. Annual Energy Outlook Report2012 With Projections to 2035. website: www.eia.gov/forecasts/aeo.
Esbensen, K.H. 2002. Multivariate Data Analysis—In Practice, fourthedition. Oslo, Norway: Camo Process AS. http://dx.doi.org/10.1002/cem.692.
Fanchi, J.R. 2005. Principles of Applied Reservoir Simulation, thirdedition. Amsterdam, The Netherlands: Elsevier Science.
Fetkovich, M.J. 1980. Decline Curve Analysis Using Type Curves. SPE J.Pet Tech 32 (6): 1065-1077.
Fraim, M.L. and Wattenbarger, R.A. 1987. Gas Reservoir Decline-CurveAnalysis Using Type Curves with Real Gas Pseudopressure and Normalized Time.SPE Form Eval. 2 (4): 671-682. http://dx.doi.org/10.2118/14238-PA.
Gaskari, R., Mohaghegh, S.D., and Jalali, J. 2006. An Integrated Techniquefor Production Data Analysis With Application to Mature Fields. Paper SPE100562 presented at the Gas Technology Symposium, Calgary, Alberta, Canada,15-17 May. http://dx.doi.org/10.2118/100562-MS.
Gaskari, R., Mohaghegh, S.D., and Jalali, J. 2007. An Integrated Techniquefor PDA with Application to Mature Fields. SPE Prod & Oper 22 (4): 403-416. http://dx.doi.org/10.2118/100562-PA.
Grujic, O., Mohaghegh, S.D., and Bromhal, G. 2010. Fast Track ReservoirModeling of Shale Formations in the Appalachian Basin. Application to LowerHuron Shale in Eastern Kentucky. Paper SPE 139101 presented at the SPE EasternRegional Meeting, Morgantown, West Virginia, 12-14 October. http://dx.doi.org/10.2118/139101-MS.
Guo, H., Marfurt, K., Liu, J. et al. 2006. Principal Component Analysisof Spectral Components. SEG, Expanded Abstracts, 988-992.
Ilk, D., Anderson, D., Stotts, G. et al. 2010. Production DataAnalysis-Challenges, Pitfalls, Diagnostics. SPE Res Eval & Eng 13 (3): 538-552. http://dx.doi.org/10.2118/102048-PA.
Ilk, D. and Blasingame, T.A. 2010. Decline Curve Analysis and ProductionAnalysis for Holly Branch Field Kernel Wells. Internal report for RPSEAproject.
Ilk, D., Perego, A.D., Rushing, J.A. et al. 2008a. Integrating MultipleProduction Analysis Techniques To Assess Tight Gas Sand Reserves: Defining aNew Paradigm for Industry Best Practices. Paper SPE 114947 presented at theCIPC/SPE Gas Technology Symposium 2008 Joint Conference, Calgary, Alberta,Canada, 16-19 June. http://dx.doi.org/10.2118/114947-MS.
Ilk, D., Rushing, J.A., Perego, A.D. et al. 2008b. Exponential vs.Hyperbolic Decline in Tight Gas Sands—Understanding the Origin and Implicationsfor Reserve Estimates Using Arps' Decline Curves. Paper SPE 116731 presented atthe Annual Technical Conference and Exhibition, Denver, Colorado, 21-24September. http://dx.doi.org/10.2118/116731-MS.
Ilk, D., Rushing, J.A., Perego, A.D. et al. 2008c. Exponential vs.Hyperbolic Decline in Tight Gas Sands—Understanding the Origin and Implicationsfor Reserve Estimates Using Arps' Decline Curves. Paper SPE 116731 presented atthe Annual Technical Conference and Exhibition, Denver, Colorado, 21-24September. http://dx.doi.org/10.2118/116731-MS.
Ilk, D., Rushing, J.A., Sullivan, R.B. et al. 2007. Evaluating the Impact ofWaterfrac Technologies on Gas Recovery Efficiency: Case Studies UsingElliptical Flow Production Data Analysis. Paper SPE 110187 presented at theAnnual Technical Conference and Exhibition, Anaheim, California, 11-14November. http://dx,doi.org/10.2118/110187-MS.
Johnson, R.H. and Bollens, A.L. 1927. The Loss Ratio Method of ExtrapolatingOil Well Decline Curves. Trans. AIME 77: 771.
Jolliffe, I.T. 2002. Principal Component Analysis, second edition.New York: Springer Series in Statistics.
Kalantari-Dahaghi, A. and Mohaghegh, S.D. 2009. Top Down IntelligentReservoir Modelling of New Albany Shale. Paper SPE 125859 presented at the SPEEastern Regional Meeting, Charleston, West Virginia, 23-25 September. http://dx.doi.org/10.2118/125859-MS.
Kalantari-Dahaghi, A., Mohaghegh, S.D., and Khazaeni, Y. 2010. New InsightInto Integrated Reservoir Management Using Top-Down, Intelligent ReservoirModeling Technique; Application to a Giant and Complex Oil Field in the MiddleEast. Paper SPE 132621 presented at the SPE Western Regional Meeting, Anaheim,California, 27-29 May. http://dx.doi.org/10.2118/132621-MS.
Kazakov, N.Y. and Miskimins, J.L. 2011. Application of MultivariateStatistical Analysis to Slickwater Fracturing Parameters in UnconventionalReservoir Systems. Paper SPE 140478 presented at the SPE Hydraulic FracturingTechnology Conference, The Woodlands, Texas, 24-26 January. http://dx.doi.org/10.2118/140478-MS.
Khazaeni, Y. and Mohaghegh, S.D. 2010. Intelligent Time-SuccessiveProduction Modeling. Paper SPE 132643 presented at the SPE Western RegionalMeeting, Anaheim, California, 27-29 May. http://dx.doi.org/10.2118/132643-MS.
Lee, S.H., Kharghoria, A., and Datta-Gupta, A. 2002. ElectrofaciesCharacterization and Permeability Predictions in Complex Reservoirs. SPE ResEval & Eng 5 (3): 237-248. http://dx.doi.org/10.2118/78662-PA.
Lewis, J.O. and Beal, C.H. 1918. Some New Methods for Estimating the FutureProduction of Oil Wells. Trans. AIME 59: 492-525.
Marhaendrajana, T. and Blasingame, T.A. 2001. Decline Curve Analysis UsingType Curves— Evaluation of Well Performance Behavior in a Multiwell ReservoirSystem. Paper SPE 71517 presented at the Annual Technical Conference andExhibition, New Orleans, Louisiana, 30 September -3 October. http://dx.doi.org/10.2118/71517-MS.
Mattar, L. and Anderson, D.M. 2003. A Systematic and ComprehensiveMethodology for Advanced Analysis of Production Data. Paper SPE 84472 presentedat the SPE Annual Technical Conference and Exhibition, Denver, Colorado, 5-8October. http://dx.doi.org/10.2118/84472-MS.
Mattar, L., Rushing, J.A., and Anderson, D.M. 2006. Production DataAnalysis—Challenges, Pitfalls, Diagnostics. Paper SPE 102048 presented at theAnnual Technical Conference and Exhibition, San Antonio, Texas, 24-27September. http://dx.doi.org/10.2118/102048-MS.
Mohaghegh, S.D. 2010. Top-Down, Intelligent Reservoir Model. EuropeanGeological Union General Assembly (Vol. 12, EGU2010-233, 2010). Vienna,Austria.
Mohaghegh, S.D., Grujic, O., Zargari, S. et al. 2011. Modeling, HistoryMatching, Forecasting and Analysis of Shale Reservoirs Performance UsingArtificial Intelligence. Paper SPE 143875 presented at the Digital EnergyConference and Exhibition, The Woodlands, Texas, 19-21 April. http://dx.doi.org/10.2118/143875-MS.
Morad, K. and Clarkson, C.R. 2008. Application of Flowing p/Z* MaterialBalance for Dry Coalbed-Methane Reservoirs. Paper SPE 114995 presented a t theCIPC/SPE Gas Technology Symposium 2008 Joint Conference, Calgary, Alberta,Canada, 16-19 June. http://dx.doi.org/10.2118/114995-MS.
Moridis, G.J., Kuzma, H.A., Reagan, M.T. et al. 2011. SeTES: A Self-TeachingExpert System for the Analysis, Design, and Prediction of Gas Production FromUnconventional Gas Resources. Paper SPE 149485 presented at the CanadianUnconventional Resources Conference, Calgary, Alberta, Canada, 15-17 November.http://dx.doi.org/10.2118/149485-MS.
Nobakht, M. and Clarkson, C.R. 2012. A New Analytical Method for AnalyzingLinear Flow in Tight/Shale Gas Reservoirs: Constant-Flowing-Pressure BoundaryCondition. SPE Res Eval & Eng 15 (3): 370-384.http://dx.doi.org/10.2118/143989-PA.
Nobakht, M., Clarkson, C.R., and Kaviani, D. 2011. New Type Curves forAnalyzing Horizontal Well With Multiple Fractures in Shale Gas Reservoirs.Paper SPE 149397 presented at the Canadian Unconventional Resources Conference,Calgary, Alberta, Canada, 15-17 November. http://dx.doi.org/10.2118/149397-MS.
Nobakht, M., Clarkson, C.R., and Kaviani, D. 2012. New and Improved Methodsfor Performing Rate-Transient Analysis of Shale Gas Reservoirs. SPE Res Eval& Eng 15 (3): 335-350. http://dx.doi.org/10.2118/147869-PA.
Oliver, D.S. and Chen, Y. 2011. Recent Progress on Reservoir HistoryMatching: A Review. Computat. Geosci. 15 (1): 185-221. http://dx.doi.org/10.1007/s10596-010-9194-2.
Oliver, D.S., Reynolds, A.C., and Liu, N. 2008. Inverse Theory forPetroleum Reservoir Characterization and History Matching. Cambridge,England: Cambridge University Press.
Olorode, O., Freeman, C., Moridis, G.J. et al. 2012. High-ResolutionNumerical Modeling of Complex and Irregular Fracture Patterns in Shale Gas andTight Gas Reservoirs. Paper SPE 152482 presented at the Latin America andCaribbean Petroleum Engineering Conference, Mexico City, Mexico, 16-18 April.http://dx.doi.org/10.2118/152482-MS.
Poston, S.W. and Poe, Jr., B.D. 2008. Analysis of Production DeclineCurves. Richardson, Texas: Society of Petroleum Engineers.
Pratikno, H., Rushing, J.A., and Blasingame, T.A. 2003. Decline CurveAnalysis Using Type Curves—Fractured Wells. Paper SPE 84287 presented at theAnnual Technical Conference and Exhibition, Denver, Colorado, 5-8 October. http://dx.doi.org/10.2118/84287-MS.
Rwechungura, R., Dadashpour, M., and Kleppe, J. 2011. Advanced HistoryMatching Techniques Reviewed. Paper SPE 142497 presented at the Middle East Oiland Gas Show and Conference, Manama, Bahrain, 25-28 September. http://dx.doi.org/10.2118/142497-MS.
Singh, Y. and Carigalli, P. 2007. Lithofacies Detection Through SimultaneousInversion and Principal Component Attributes. The Leading Edge 26 (17): 1568-1575.
Souza, O.C.D.D., Sharp, A.J., Martinez, R.C. et al. 2012. IntegratedUnconventional Shale Gas Reservoir Modeling: A Worked Example From theHaynesville Shale, De Soto Parish, North Louisiana. Paper SPE 154692 presentedat the Americas Unconventional Resources Conference, Pittsburgh, Pennsylvania,5-7 June. http://dx.doi.org/10.2118/154692-MS.
Tague, J.R. 2000. Multivariate Statistical Analysis Improves FormationDamage Remediation. Paper SPE 63004 presented at the Annual TechnicalConference and Exhibition, Dallas, Texas, 1-4 October. http://dx.doi.org/10.2118/63004-MS.
Tingdahl, K. 1999. Estimating Fault-Attribute Orientation With GradientAnalysis, Principal Component Analysis and the Localized Hough-Transform.Seg Technical Program Expanded Abstracts 22 (1).
Velazquez, R.C., Vasquez-Cruz, M.A., Castrejon-Aivar, R. et al. 2005.Pressure-Transient and Decline-Curve Behaviors in Naturally Fractured VuggyCarbonate Reservoirs. SPE Res Eval & Eng 8 (2): 95-112.http://dx.doi.org/10.2118/77689-PA.
Xu, B., Haghighi, M., Cooke, D. et al. 2012. Production Data Analysis inEagle Ford Shale Gas Reservoir. Paper SPE 153072 presented at the SPE/EAGEEuropean Unconventional Resources Conference and Exhibition, Vienna, Austria,20-22 March. http://dx.doi.org/10.2118/153072-MS.
Yergin, D. 2012. The Quest: Energy, Security, and the Remaking of theModern World. London, England: Penguin Books.
Zargari, S. and Mohaghegh, S.D. 2010. Field Development Strategies forBakken Shale Formation. Paper SPE 139032 presented at the SPE Eastern RegionalMeeting, Morgantown, West Virginia, 12-14 October. http://dx.doi.org/10.2118/139032-MS.
Zhu, Y., Yuan, S., Liu, M. et al. 1999. A New Method for Effective ReservoirRecognition Using Principal Component Analysis of Conventional Well-LoggingInterpretation in Fractured Complex Lithologic Reservoir. Paper SPE 54386presented at the Asia Pacific Oil and Gas Conference and Exhibition, Jakarta,Indonesia, 20-22 April. http://dx.doi.org/10.2118/54386-MS.