Probabilistic Reservoir-Property Modeling Jointly Constrained by 3D-Seismic Data and Hydraulic-Unit Analysis
- Mohammad Emami Niri (University of Western Australia) | David Lumley (University of Western Australia)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2016
- Document Type
- Journal Paper
- 253 - 264
- 2016.Society of Petroleum Engineers
- Seismic inversion, Reservoir modeling, Hydraulic unit, 3D seismic data, Rock physics
- 6 in the last 30 days
- 356 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
We present a new method for seismic reservoir characterization and reservoir-property modeling on the basis of an integrated analysis of 3D-seismic data and hydraulic flow units, and apply it to an example of a producing reservoir offshore Western Australia. Our method combines hydraulic-unit analysis with a set of techniques for seismic reservoir characterization including rock physics analysis, Bayesian inference, prestack seismic inversion, and geostatistical simulation of reservoir properties. Hydraulic units are geologic layers and zones characterized by similar properties of fluid flow in porous permeable media, and are defined at well locations on the basis of logs, core measurements, and production data. However, the number of wells available for hydraulic- unit analysis is often extremely limited. In comparison, the lateral coverage and resolution of 3D-seismic data are excellent, and can thus be used to extend hydraulic-unit analysis away from well locations into the full 3D reservoir volume. We develop a probabilistic relationship between optimal 3D-seismic-data attributes and the hydraulic units that we determine at well locations. Because porosity and permeability distributions are estimated for each hydraulic flow unit as part of the process, we can use the 3D seismic probabilistic relationships to constrain geostatistical realizations of porosity and permeability in the reservoir, to be consistent with the flow-unit analysis. Reservoir models jointly constrained by both 3D-seismic data and hydraulic flow-unit analysis have the potential to improve the processes of reservoir characterization, fluid-flow performance forecasting, and production data or 4D-seismic history matching.
|File Size||2 MB||Number of Pages||12|
Amaefule, J., Altunbay, M., Tiab, D. et al. 1993. Enhanced Reservoir Description: Using Core and Log Data to Identify Hydraulic (Flow) Units and Predict Permeability in Uncored Intervals/Wells. Presented at the SPE Annual Technical Conference and Exhibition, Houston, USA, 3–6 October. SPE-26436-MS. http://dx.doi.org/10.2118/26436-MS.
Avseth, P., Mukerji, T., and Mavko, G. 2005. Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk. Cambridge University Press.
Bear, J. 1972. Dynamics of Fluids in Porous Media. American Elsevier.
Behrens, R. and Tran, T. 1999. Incorporating Seismic Data of Intermediate Vertical Resolution Into Three-Dimensional Reservoir Models: A New Method. SPE Res Eval & Eng 2 (4): 325–333. SPE-57481-PA. http://dx.doi.org/10.2118/57481-PA.
Bornard, R., Allo, F., Coleou, T. et al. 2005. Petrophysical Seismic Inversion to Determine More Accurate and Precise Reservoir Properties. Presented at the SPE Europec/EAGE Annual Conference, Madrid, Spain, 13–16 June. SPE-94144-MS. http://dx.doi.org/10.2118/94144-MS.
Bosch, M., Mukerji, T., and Gonzalez, E. F. 2010. Seismic Inversion for Reservoir Properties Combining Statistical Rock Physics and Geostatistics: A Review. Geophysics 75 (5): 75A165–175A176. http://dx.doi.org/10.1190/1.3478209.
Carman, P. 1997. Fluid Flow Through Granular Beds. Chemical Engineering Research & Design 75: S32–S48. http://dx.doi.org/10.1016/S0263-8762(97)80003-2.
Coléou, T., Formento, J. L., Gram-Jensen, M. et al. 2006. Petrophysical Seismic Inversion Applied to the Troll Field. SEG Technical Program Expanded Abstracts 25 (1): 2107–2111.
Davies, D. and Vessell, R. 1996. Identification and Distribution of Hydraulic Flow Units in a Heterogeneous Carbonate Reservoir: North Robertson Unit, West Texas. Presented at the Permian Basin Oil and Gas Recovery Conference, Midland, Texas, 27–29 March. SPE-35183-MS. http://dx.doi.org/10.2118/35183-MS.
Deutsch, C. V. and Journel, A. G. 1992. Geostatistical Software Library and User’s Guide. Oxford University Press.
Doyen, P. 2007. Seismic Reservoir Characterization: An Earth-Modeling Perspective. EAGE Publications bv ISBN 978-90-73781-77-1.
Duda, R. O., Hart, P. E., and Stork, D. G. 2000. Pattern Classification. New York: John Wiley & Sons.
Ebanks, W. 1987. Flow Unit Concept—Integrated Approach to Reservoir Description for Engineering Projects. AAPG Bull. 71 (5): 551–552. http://dx.doi.org/10.1306/94887168-1704-11D7-8645000102C1865D.
Emami Niri, M. and Misaghi, A. 2009. Seismic Velocity–Reservoir Permeability Relations Within Hydraulic Units in an Oil Field Southwest Iran. In Extended Abstracts for Shiraz 2009—1st EAGE International Petroleum Conference and Exhibition. http://dx.doi.org/10.3997/2214-4609.20145882.
Emami Niri, M. and Lumley, D. 2015a. Initializing Reservoir Models for History Matching Using Pre-Production 3D Seismic Data: Constraining Methods and Uncertainties. In Exploration Geophysics. http://dx.doi.org/10.1071/EG15013.
Emami Niri, M. and Lumley, D. 2015b. Simultaneous Optimization of Multiple Objective Functions for Reservoir Modeling. Geophysics 80 (5): M53–M67. http://dx.doi.org/10.1190/geo2015-0006.1.
Ementon, N., Hill, R., Flynn, M. et al. 2004. Stybarrow Oil Field—From Seismic to Production: The Integrated Story So Far. Presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Perth, Australia, 18–20 October. SPE-88574-MS. http://dx.doi.org/10.2118/88574-MS.
Faruk, C. 2003. Leaky-Tube Permeability Model for Identification, Characterization, and Calibration of Reservoir Flow Units. Presented at the SPE Annual Technical Conference and Exhibition, Denver, USA, 5–8 October. SPE-84603-MS. http://dx.doi.org/10.2118/84603-MS.
Fatti, J. L., Smith, G. C., Vail, P. J. et al. 1994. Detection of Gas in Sandstone Reservoirs Using AVO Analysis: A 3D Seismic Case History Using the Geostack Technique. Geophysics 59 (9): 1362–1376. http://dx.doi.org/10.1190/1.1443695.
Grana, D., Mukerji, T., Dvorkin, J. et al. 2012. Stochastic Inversion of Facies From Seismic Data Based On Sequential Simulations and Probability Perturbation Method. Geophysics 77 (4): M53–M72. http://dx.doi.org/10.1190/geo2011-0417.1.
Grana, D., Paparozzi, E., Mancini, S. et al. 2013. Seismic-Driven Probabilistic Classification of Reservoir Facies for Static Reservoir Modeling: A Case History in the Barents Sea. Geophysical Prospecting 61: 613–629. http://dx.doi.org/10.1111/j.1365-2478.2012.01115.x.
Gunter, G., Finneran, J., Hartmann, D. et al. 1997. Early Determination of Reservoir Flow Units Using an Integrated Petrophysical Method. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 5–8 October. SPE-38679-MS. http://dx.doi.org/10.2118/38679-MS.
Haldorsen, H. H. and Damsleth, E. 1990. Stochastic Modeling (includes associated papers 21255 and 21299). J Pet Technol 42 (4): 404–412. SPE-20321-PA. http://dx.doi.org/10.2118/20321-PA.
Hampson, D., Russell, B., and Bankhead, B. 2005. Simultaneous Inversion of Pre-Stack Seismic Data. In SEG Technical Program Expanded Abstracts, 1633–1637. http://dx.doi.org/10.1190/1.2148008.
Hearn, C., Ebanks W. J., Tye, R. et al. 1984. Geological Factors Influencing Reservoir Performance of the Hartzog Draw Field, Wyoming. J Pet Technol 36 (8): 1335–1344. SPE-12016-PA. http://dx.doi.org/10.2118/12016-PA.
Hill, R. A., O’Halloran, G., Napalowski, R. et al. 2008. Development of the Stybarrow Field Western Australia. Presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Perth, Australia, 20–22 October. SPE-115373-MS. http://dx.doi.org/10.2118/115373-MS.
Hossain, M. E. and Islam, M. R. 2009. The Mystery and Uncertainty Cloud During Reservoir Simulation in Petroleum Industry. Advances in Sustainable Petroleum Engineering Science 2 (3): 283–300.
Hurren, C. A., Broad, C., Duncan, G. et al. 2012. Successful Application of 4D Seismic in the Stybarrow Field Eastern Australia. Presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Perth, Australia, 22–24 October. SPE-158753-MS. http://dx.doi.org/10.2118/158753-MS.
Journel, A. G. 2002. Combining Knowledge From Diverse Sources: An Alternative to Traditional Data Independence Hypotheses. Mathematical Geology 34 (5): 573–596.
Kemper, M. 2010. Rock Physics Driven Inversion: The Importance of Workflow. First Break 28 (10): 69–81.
King, M., Burn, K., Wang, P. et al. 2006. Optimal Coarsening of 3D Reservoir Models for Flow Simulation. SPE Res Eval & Eng 9 (4): 317–334. SPE-95759-PA. http://dx.doi.org/10.2118/95759-PA.
Kozeny, J. 1927. Ueber Kapillare Leitung Des Wassers Im Boden. Sitzungsber Akad. Wiss. Wien 136: 271–306.
Lippmann, M., Goldstein, N., Halfman, S. et al. 1984. Exploration and Development of the Cerro Prieto Geothermal Field. J Pet Technol 36 (9): 1579–1591. SPE-12098-PA. http://dx.doi.org/10.2118/12098-PA.
Lumley, D., Adams, D., Meadows, M. et al. 2003. 4D Seismic Pressure-Saturation Inversion at Gullfaks Field, Norway. First Break 21 (9): 3–9.
Mukerji, T., Jørstad, A., Avseth, P. et al. 2001. Mapping Lithofacies and Pore-Fluid Probabilities in a North Sea Reservoir: Seismic Inversions and Statistical Rock Physics. Geophysics 66 (4): 988–1001. http://dx.doi.org/10.1190/1.1487078.
Nivlet, P., Lefeuvre, F., and Piazza, J. L. 2007. 3D Seismic Constraint Definition in Deep-Offshore Turbidite Reservoir. Oil & Gas Science and Technology–Revue de l’IFP 62 (2): 249–264. http://dx.doi.org/10.2516/ogst:2007021.
Nooruddin, H. A. and Hossain, M. E. 2011. Modified Kozeny–Carmen Correlation for Enhanced Hydraulic Flow Unit Characterization. J. Petrol. Sci. & Eng. 80 (1): 107–115. http://dx.doi.org/10.1016/j.petrol.2011.11.003.
Nur, A. M., Walls, J. D., Winkler, K. et al. 1980. Effects of Fluid Saturation on Waves in Porous Rock and Relations to Hydraulic Permeability. SPE J. 20 (6): 450–458. SPE-8235-PA. http://dx.doi.org/10.2118/8235-PA.
Prasad, M. 2003. Velocity-Permeability Relations Within Hydraulic Units. Geophysics 68 (1): 108–117. http://dx.doi.org/10.1190/1.1543198.
Satter, A. and Thakur, G. C. 1994. Integrated Petroleum Reservoir Management: A Team Approach. PennWell Books.
Schatz, B. and Heinemann, Z. 2007. Flow-Based Determination of Hydraulic Units. Presented at the SPE Europec/EAGE Annual Conference and Exhibition, London, 11–14 June. SPE-107158-MS. http://dx.doi.org/10.2118/107158-MS.
Shedid, S. 2001. A Multi-Purpose Reservoir Characterization Model. Presented at the SPE Middle East Oil Show, Manama, Bahrain, 17–20 March. SPE-68105-MS. http://dx.doi.org/10.2118/68105-MS.
Shenawi, S., White, J., Elrafie, E. et al. 2007. Permeability and Water Saturation Distribution by Lithologic Facies and Hydraulic Units: A Reservoir Simulation Case Study. Presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 11–14 March. SPE-105273-MS. http://dx.doi.org/10.2118/105273-MS.
Shenawi, S., Al-Mohammadi, H., and Faqehy, M. 2009. Development of Generalized Porosity-Permeability Transforms by Hydraulic Units for Carbonate Oil Reservoirs in Saudi Arabia. Presented at the SPE/EAGE Reservoir Characterization and Simulation Conference, Abu Dhabi, 19–21 October. SPE-125380-MS. http://dx.doi.org/10.2118/125380-MS.
Singleton, S. 2009. The Effects of Seismic Data Conditioning on Prestack Simultaneous Impedance Inversion. The Leading Edge 28 (7): 772–781.
Tiab, D. and Donaldson, E. C. 2011. Petrophysics: Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties. Gulf Professional Publishing.
Tura, A. and Lumley, D. 2000. Estimating Pressure and Saturation Changes From Time-Lapse AVO Data. Presented at the Offshore Technology Conference, Houston, USA, 1–4 May. http://dx.doi.org/10.4043/12130-MS.
Younis, R. M. and Caers, J. 2002. A Method for Static-Based Up-gridding. In Extended Abstracts for ECMOR VIII 8th European Conference on the Mathematics of Oil Recovery, Freiberg, Germany, 3–6 September.
Zakrevsky, K. 2011. Geological 3D Modeling. EAGE Publications bv, ISBN 978-90-73781-96-2.