History Matching and Production Forecast With Logs as Effective Completion and Reservoir-Managing Tools in Horizontal and Vertical Wells
- Carlos F. Haro (Occidental Oil & Gas Corporation)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- October 2012
- Document Type
- Journal Paper
- 596 - 608
- 2012. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 3.3.1 Production Logging, 5.5.8 History Matching, 1.1 Well Planning, 4.1.2 Separation and Treating, 4.3.4 Scale, 5.6.1 Open hole/cased hole log analysis, 5.6.8 Well Performance Monitoring, Inflow Performance, 5.6.9 Production Forecasting
- 6 in the last 30 days
- 682 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 10.00|
|SPE Non-Member Price:||USD 30.00|
Simulation history matching is a daunting, time-consuming task with numerous unknowns and several plausible answers. Scale differences in the data frequently obscure results, limiting its application in completion strategies. Good history matching does not guarantee accurate production forecasts, however. Reliable predictions, required for well planning, depend on the ability of the user to reduce the uncertainties to find consistent and timely solutions. Logs can provide appropriate conditioning data for history matching to enable its use for reservoir management. Electrofacies, capillary pressure, and absolute and relative permeability, imprinted on logs, can be mathematically linked with irreducible water saturation (Swi). Unlike reservoir simulators, well logs are at the right scale for completion designs. Logs facilitate upscaling, honoring rock and fluid properties and the physics of flow (Haro 2006). Logs are snapshot measurements that are amenable for conversion into dynamic forecasting tools by use of flow and pressure equations. This concept permits creation of synthetic production logs (SPLTs) over time, from which production decline can be calculated. This method consists of integrating material balance, flow/pressure algorithms, fluid data, cores, and log data. Thus, the corresponding analytical expressions are required. In this approach, every well represents a finite, gridded tank, capable of producing a measurable volume of fluids, limited by its petrophysical constraints. Superposition, in terms of pressure and flow, combines the various components within and among wells. The quality of the results is ensured because material balance must be honored at every depth at all times under different production scenarios and the prevailing drive mechanism. This log-handling technique helps when making strategic economic decisions to maximize reserves and optimize the reservoir-development plan. This strategy is used to obtain oil in place (OIP), drainage radii, lateral connectivity, fluid-bank arrival times, productivity indices (PIs), inflow performance relationship (IPR), production allocation, and recovery per zone per well. Current log analyses or simulators generally do not provide these parameters at this detail. This refined use of logs streamlines completion designs and improves conformance, enabling us to comply with an important part of daily reservoir management.
|File Size||1 MB||Number of Pages||13|
Bogatkov, D. and Babadagli, T. 2009. Integrated Modeling of the FractureCarbonate Midale Field and Sensitivity Analysis Through Experimental Design.SPE Res Eval & Eng 12 (6): 951-961. SPE-131004-PA. http://dx.doi.org/10.2118/131004-PA.
Craft, B.C. and Hawkins, M. 1991. Applied Petroleum ReservoirEngineering, 59. Upper Saddle River, New Jersey: Prentice HallInternational.
Delfiner, P. 2007. Three Statistical Pitfalls of Phi-K Transforms. SPERes Eval & Eng 10 (6): 609-617. SPE-102093-PA. http://dx.doi.org/10.2118/102093-PA.
Ertekin, T., Abou-Kassem J.H., and King, G. 2001. Basic Applied ReservoirSimulation, Vol. 7, 376. Richardson, Texas: Textbook Series, SPE.
Fanchi, J.R. 1997. Principles of Applied Reservoir Simulation, 102.Houston, Texas: Gulf Publishing Company.
Guo, G., Diaz, M.A., Paz, F., et al. 2007. Rock Typing as an Effective Toolfor Permeability and Water-Saturation Modeling: A Case Study in a ClasticReservoir in the Oriente Basin. SPE Res Eval & Eng 10(6): 730-739. SPE-97033-PA. http://dx.doi.org/10.2118/97033-PA.
Haro, C.F. 2004. The Perfect Permeability Transform Using Logs and Cores.Paper SPE 89516 presented at the SPE Annual Technical Conference andExhibition, Houston, Texas, 26-29 September. http://dx.doi.org/10.2118/89516-MS.
Haro, C.F. 2006. Permeability Modeling. Setting Archie and Carman- KozenyRight. Paper SPE 100200 presented at the SPE Europec/ EAGE Annual Conferenceand Exhibition, Vienna, Austria, 12-15 June. http://dx.doi.org/10.2118/100200-MS.
Haro, C.F. 2010. The Equations Archie Forgot: Anisotropy of the Rocks.SPE Res Eval & Eng 13 (5): 823-836. SPE-123913-PA. http://dx.doi.org/10.2118/123913-PA.
Hui, M.H., Zhou, D., Wen, X.-H., et al. 2004. Development and Application ofa New Technique for Upscaling Miscible Processes. Paper SPE 89435 presented atthe SPE/DOE Symposium on Improved Oil Recovery, Tulsa, Oklahoma, 17-21 April.http://dx.doi.org/10.2118/89435-MS.
Jensen, J.L., Lake, L.W., Corbett, P.W.M., et al. 2000. Statistics forPetroleum Engineers and Geoscientists, 12. Amsterdam, The Netherlands:Elsevier.
Joshi, S.D. 1991. Horizontal Well Technology, 62. Tulsa, Oklahoma:Pen-Well Books.
Kaviani, D., Valko, P.P., Jensen, J.L. 2010. Application of the MultiwellProductivity Index-Based Method to Evaluate Interwell Connectivity. Paper SPE129965 presented at the SPE Improved Oil Recovery Symposium, Tulsa, Oklahoma,24-28 April. http://dx.doi.org/10.2118/129965-MS.
Lisigurski, O., Ferdiana, W., Haro, C.F., et al. 2009. Increasing Productionand Injection in Multilateral Wells in Naturally Fractured Carbonate Reservoirsby Rigless Interventions - A Case Study, Offshore, Qatar. Paper SPE 120326-MSpresented at the SPE Middle East Oil and Gas Show and Conference, Bahrain,Bahrain, 15-18 March. http://dx.doi.org/10.2118/120326-MS.
Mattax, C.C. and Dalton, R.L. 1990. Reservoir Simulation, Vol. 13,144. Richardson, Texas: Monograph Series, SPE.
Pérez, H.H., Datta-Gupta, A., and Mishra, S. 2005. The Role ofElectrofacies, Lithofacies, and Hydraulic Flow Units in Permeability Predictionfrom Well Logs: A Comparative Analysis Using Classification Trees. SPE ResEval & Eng 8 (2): 143-155. SPE-84301-PA. http://dx.doi.org/10.2118/84301-PA.
Poston, S.W. and Poe, B.D. Jr. 2008. Analysis of Production DeclineCurves, 106. Richardson, Texas: SPE.
Saleri, N.G. 1993. Reservoir Performance Forecasting: Acceleration byParallel Planning. J Pet Technol 45 (7): 652-657.SPE-25151-PA. http://dx.doi.org/10.2118/25151-PA.
Sayarpour, M., Kabir, C.S., Sepehrnoori, K., et al. 2010. ProbabilisticHistory Matching With the Capacitance-Resistance Model in Waterfloods: APrecursor to Numerical Modeling. Paper SPE 129604 presented at the SPE ImprovedOil Recovery Symposium, Tulsa, Oklahoma, 24-28 April. http://dx.doi.org/10.2118/129604-MS.
Schlumberger. 1989. Log Interpretation Principles and Applications,10-13. Sugarland, Texas: Schlumberger Educational Services.
Slider, H.C. 1983. Worldwide Practical Petroleum Reservoir EngineeringMethods, 523. Tulsa, Oklahoma: PenWell Books.
Stewart, G. and Wittmann, M.J. 1981. Well Performance Analysis: A SynergeticApproach to Dynamic Reservoir Description. Paper SPE 10209 presented at the SPEAnnual Technical Conference and Exhibition, San Antonio, Texas, 4-7 October.http://dx.doi.org/10.2118/10209- MS.
Sullivan, M.J., Belanger, D.L., Skalinski, M.T., et al. 2006. PermeabilityFrom Production Logs --Method and Application. Paper SPE 102894 presented atthe SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24-27September. http://dx.doi.org/10.2118/102894-MS.
Yousef, A.A., Gentil P., Jensen, J.L., et al. 2006. A Capacitance Model toInfer Interwell Connectivity from Production- and Injection-Rate Fluctuations.SPE Res Eval & Eng 9 (6): 630-646. SPE-95322-PA. http://dx.doi.org/10.2118/95322-PA.
Worthington, P.F. 2010. Net Pay—What is it? What does it do? How do wequantify it? How do we use it? SPE Res Eval & Eng 13(5): 812-822. SPE-123561-PA. http://dx.doi.org/10.2118/123561-PA.
Zhang, F., Skjervheim, J.A., Reynolds, A.C., et al. 2003. Automatic HistoryMatching in a Bayesian Framework, Example Applications. Paper SPE 84461presented at the SPE Annual Technical Conference and Exhibition, Denver,Colorado, 5-8 October. http://dx.doi.org/10.2118/84461-MS.