Improving Reservoir Characterization and Simulation With Near-Wellbore Modeling
- Viswa Santhi Chandra (Heriot-Watt University) | Patrick W.M. Corbett (Heriot-Watt University) | Sebastian Geiger (Heriot-Watt University) | Hamidreza Hamdi (University of Calgary)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2013
- Document Type
- Journal Paper
- 183 - 193
- 2013. Society of Petroleum Engineers
- 5.5 Reservoir Simulation, 4.3.4 Scale, 5.1.5 Geologic Modeling, 5.5.3 Scaling Methods, 4.1.2 Separation and Treating, 5.6.1 Open hole/cased hole log analysis, 1.6.9 Coring, Fishing, 5.1 Reservoir Characterisation
- 2 in the last 30 days
- 1,263 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
New reservoir characterization methods are needed to integrate multiscale exploration and development data, particularly at the interface between well and field models. In this paper, we illustrate a novel workflow involving high-resolution near-wellbore modeling (NWM), which allows us to accurately include seismic, wireline data, image logs, and well core logs from highly heterogeneous reservoirs in field-scale reservoir simulations. We demonstrate that an NWM-enhanced geoengineering workflow has the potential to improve reservoir characterization by applying it to a realistic clastic reservoir with high variance at small scale. We have performed a number of sensitivities comparing conventional local grid refinement (LGR) in the near-wellbore region with that involving NWM, and we obtained a significant increase in the accuracy of reservoir characterization and the calibration of dynamic models. Centimeter-scale models, containing several million cells, representing the fine geological details of the nearwellbore region, were constructed with available data from core and openhole well-log suits. The resulting well models were upscaled into regular grids with the highest resolution possible through the NWM software and incorporated into a field-scale simulation model to evaluate the dynamic behavior of the reservoir with a static-model transient test. Our results show that the use of NWM tools for reservoir modeling yields more precise flow calculations and improves our fundamental understanding of the interactions between the reservoir and the wellbore.
|File Size||1 MB||Number of Pages||11|
Archer, R.A. and Yildiz, T.T. 2001. Transient Well Index for Numerical WellTest Analysis. Paper SPE 71572 presented at the SPE Annual Technical Conferenceand Exhibition, New Orleans, Louisiana, 30 September-3 October. http://dx,doi.org/10.2118/71572-MS.
Begg, S.H., Carter, R.R., and Dranfield, P. 1989. Assigning Effective Valuesto Simulator Gridblock Parameters for Heterogeneous Reservoirs. SPE ResEng 4 (4): 455-463. http://dx.doi.org/10.2118/16754-PA.
Brandsæter, I., Wist, H.T., Næss, A. et al. 2001. Ranking of StochasticRealizations of Complex Tidal Reservoirs Using Streamline Simulation Criteria.Pet. Geosci. 7 (5): 553-563. http://dx.doi.org/10.1144/petgeo.7.5.553.
Corbett, P.W.M. 2009. Petroleum Geoengineering: Integration of Static andDynamic Models (SEG/EAGE Distinguished Instructor Series, 12, SEG) 100 pp. ISBN978-1-56080-153-5.
Corbett, P.W.M., Geiger, S., Borges, L. et al. 2012. The Third PorositySystem: Understanding the Role of Hidden Pore Systems in Well-TestInterpretation in Carbonates. Pet. Geosci. 18 (1): 73-81.http://dx.doi.org/10.1144/1354-079311-010.
Corbett, P.W.M., Mesmari, A., and Stewart, G. 1996. A Method for Using theNaturally-Occurring Negative Geoskin in the Description of Fluvial Reservoirs.Paper SPE 36882 presented at the European Petroleum Conference, Milan, Italy,22-24 October. http://dx.doi.org/10.2118/36882-MS.
Corre, B., Thore, P., de Feraudy, V. et al. 2000. Integrated UncertaintyAssessment for Project Evaluation and Risk Analysis. Paper SPE 65205 presentedat the SPE European Petroleum Conference, Paris, France, 24-25 October. http://dx.doi.org/10.2118/65205-MS.
Deutsch, C.V. 2002. Geostatistical Reservoir Modeling. New York:Oxford University Press.
Deutsch, C.V. and Journel, A.G. 1997. GSLIB. Geostatistical SoftwareLibrary and User's Guide. New York: Oxford University Press.
Elfenbein, C., Ringrose, P., and Christie, M. 2005. Small-Scale ReservoirModeling Tool Optimizes Recovery Offshore Norway. World Oil 226 (10): 45-50.
Ewing, R.E. and Lazarov, R.D. 1988. Adaptive Local Grid Refinement. PaperSPE 17806 presented at the SPE Rocky Mountain Regional Meeting, Casper,Wyoming, 11-13 May. http://dx.doi.org/10.2118/17806-MS.
Hamdi, H. 2012. Illumination of Channelised Fluvial Reservoirs UsingGeological Well-Testing and Seismic Modelling. Unpublished PhD thesis,Heriot-Watt University, UK.
Hogg, A.J.C., Evans, I.J., Harrison, P.F. et al. 1999. ReservoirManagement of the Wytch Farm Oil Field, Dorset, UK: Providing Options forGrowth Into Later Field Life. Petroleum Geology Conference Series, Vol. 5,1157-1172. http://dx.doi.org/10.1144/0051157.
Jackson, M.D., Yoshida, S., Muggeridge, A.H. et al. 2005. Three-DimensionalReservoir Characterization and Flow Simulation of Heterolithic TidalSandstones. AAPG Bull. 89 (4): 507-528. http://dx.doi.org/10.1306/11230404036.
McKinley, J.M., Lloyd, C.D., Ruffell, A.H. 2004. Use of Variography inPermeability Characterization of Visually Homogeneous Sandstone Reservoirs withExamples From Outcrop Studies. Math. Geol. 36 (7):761-779.
Newell, A.J. 2006. Calcrete as a Source of Heterogeneity in Triassic FluvialSandstone Aquifers (Otter Sandstone Formation, SW England). In Fluid Flowand Solute Movement in Sandstones: The Onshore UK Permo-Triassic Red BedSequence, ed. R.D. Barker and J.H. Tellam, Special Publications, Vol. 263(1), 119-127. London: Geological Society.
Nordahl, K. 2004. A Petrophysical Evaluation of Tidal Heterolithic Deposits:Application of a Near Wellbore Model for Reconciliation of Scale Dependent WellData. PhD thesis, Norwegian University of Science and Technology, Trondheim,Norway (April 2004).
Nordahl, K., Ringrose, P.S., and Wen, R. 2005. PetrophysicalCharacterization of a Heterolithic Tidal Reservoir Interval Using aProcess-Based Modeling Tool. Pet. Geosci. 11: 17-28. http://dx.doi.org/10.1144/1354-079303-613.
Ringrose, P.S., Martinius, A.W., and Alvestad, J. 2008. MultiscaleGeological Reservoir Modelling in Practice. Special Publications, Vol.309, 123-134. London: Geological Society. http://dx.doi.org/10.1144/SP309.9.
Ringrose, P.S., Nordahl, K., and Wen, R. 2005. Vertical PermeabilityEstimation in Heterolithic Tidal Deltaic Sandstones. Pet. Geosci. 11 (1): 29-36. http://dx.doi.org/10.1144/1354-079303-614.
Toro-Rivera, M.L.E., Corbett, P.W.M., and Stewart, G. 1994. Well TestInterpretation in a Heterogeneous Braided Fluvial Reservoir. Paper SPE 28828presented at the European Petroleum Conference, London, United Kingdom, 25-27October. http://dx.doi.org/10.2118/28828-MS.
Wasserman, M.L. 1987. Local Grid Refinement for Three-DimensionalSimulators. Paper SPE 16013 presented at the SPE Symposium on ReservoirSimulation, San Antonio, Texas, 1-4 February. http://dx.doi.org/10.2118/16013-MS.
Wen, R., Martinius, A.W., Naess, A. et al. 1998. Three-DimensionalSimulation of Small-Scale Heterogeneity in Tidal Deposits—A Process-BasedStochastic Method. Proceedings of 4th Annual Conference of the InternationalAssociation of Mathematical Geology. Ischia De Frede, Naples, 129-134.