A Practical Methodology For Integration of 4D Seismic in Steam-Assisted-Gravity-Drainage Reservoir Characterization
- Mostafa Hadavand (University of Alberta) | Clayton Vernon Deutsch (University of Alberta)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- September 2016
- Document Type
- Journal Paper
- 2016.Society of Petroleum Engineers
- 4D Seismic, Geostatistics, SAGD Reservoir Characterization
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- 74 since 2007
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4D seismic is a dynamic source of data that provides information about changes in reservoir-rock and -fluid properties over time. Seismic attributes are sensitive to variations in the fluid content, temperature, and pressure distribution; therefore, 4D-seismic images contain information on the nature of fluid flow within the reservoir. Perhaps the most-reliable and-important information that can be learned from 4D-seismic images is related to anomalies in fluid flow within the reservoir. During steam-assisted gravity drainage (SAGD), the steam-chamber propagation is fairly clear from 4D-seismic images, mainly because of higher gas saturation in the chamber. Therefore, anomalies are revealed by the absence or unexpected location of the steam chamber. In this paper, a practical methodology is proposed for consideration of anomalies identified from 4D-seismic images in geostatistical reservoir models. The geostatistical realizations are updated to enforce missing anomalies and improve reservoir characterization. The updated models are suitable for reservoir decision making and management.
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Abdollahzadeh, A., Christie, M., Corne, D. et al. 2013. An Adaptive Evolutionary Algorithm for History-Matching. Presented at the EAGE Annual Conference & Exhibition Incorporating SPE Europec. London, 10–13 June. SPE-164824-MS. http://dx.doi.org/10.2118/164824-MS.
Andersen, T., Zachariassen, E., Otterlei, C. et al. 2006. Method For Conditioning The Reservoir Model On 3D And 4D Elastic Inversion Data Applied To A Fluvial Reservoir In The North Sea. Presented at the SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, 12–15 June. SPE-100190-MS. http://dx.doi.org/10.2118/100190-MS.
Arenas, E., van Kruijsdijk, C. and Oldenziel, T. 2001. Semi-Automatic History Matching Using the Pilot Point Method Including Time-Lapse Seismic Data. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 30 September–3 October. SPE-71634-MS. http://dx.doi.org/10.2118/71634-MS.
Castro, S., Caers, J. K., Otterlei, C. et al. 2006. A Probabilistic Integration of Well Log, Geological Information, 3D/4D Seismic, and Production Data: Application to the Oseberg Field. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24–27 September. SPE-103152-MS. http://dx.doi.org/10.2118/103152-MS.
CMG. 2012. STARS User Manual, Version 2012. Calgary, Alberta: Computer Modelling Group.
Deutsch, C. V. and Journel, A. G. 1994. The Application of Simulated Annealing to Stochastic Reservoir Modeling. SPE Advanced Technology Series 2 (2): 222–227. SPE-23565-PA. http://dx.doi.org/10.2118/23565-PA.
Deutsch, C. V. and Journel, A. G. 1998. GSLIB: Geostatistical Software Library and User's Guide, second edition. New York City: Oxford University Press.
Efron, B. 1979. Bootstrap Methods: Another Look at the Jackknife. Ann. Stat. 7 (1): 1–26. http://dx.doi.org/10.1214/aos/1176344552.
Gassmann, F. 1951. On Elasticity of Porous Media. Über die Elastizität poröser Medien. Vierteljahrsschrift der naturforschenden Gesellschaft in Zürich. 96 (31 March): 1–23.
Gosselin, O., van den Berg, S. and Cominelli, A. 2001. Integrated History-Matching of Production and 4D Seismic Data. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 30 September–3 October. SPE-71599-MS. http://dx.doi.org/10.2118/71599-MS.
Isaaks, E. H. 1991. The Application of Monte Carlo Methods to the Analysis of Spatially Correlated Data. PhD dissertation, Stanford University, Stanford, California.
Mezghani, M., Fornel, A., Langlais, V. et al. 2004. History Matching and Quantitative Use of 4D Seismic Data for an Improved Reservoir Characterization. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 26–29 September. SPE-90420-MS. http://dx.doi.org/10.2118/90420-MS.
Ouenes, A., Fasanino, G. and Lee, R. L. 1992. Simulated Annealing for Interpreting Gas/Water Laboratory Corefloods. Presented at the SPE Annual Technical Conference and Exhibition, Washington, DC, 4–7 October. SPE-24870-MS. http://dx.doi.org/10.2118/24870-MS.
Rama Rao, B. S., LaVenue, A. M., De Marsily, G. et al. 1995. Pilot Point Methodology for Automated Calibration of an Ensemble of conditionally Simulated Transmissivity Fields: 1. Theory and Computational Experiments. Water Resour. Res. 31 (3): 475–493. http://dx.doi.org/10.1029/94WR02258.
Rwechungura, R. W., Dadashpour, M. and Kleppe, J. 2011. Advanced History Matching Techniques Reviewed. Presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, 25–28 September. SPE-142497-MS. http://dx.doi.org/10.2118/142497-MS.
Solow, A. R. 1985. Bootstrapping Correlated Data. Math. Geol. 17 (7): 769–775. http://dx.doi.org/10.1007/BF01031616.
Tolstukhin, E., Lyngnes, B. and Sudan, H. H. 2012. Ekofisk 4D Seismic - Seismic History Matching Workflow. Presented at the SPE Europec/EAGE Annual Conference, Copenhagen, Denmark, 4–7 June. SPE-154347-MS. http://dx.doi.org/10.2118/154347-MS.
Warren, J. and Price, H. 1961. Flow in Heterogeneous Porous Media. SPE J. 1 (3): 153–169. SPE-1579-G. http://dx.doi.org/10.2118/1579-G.
Wen, X.-H., Tran, T., Behrens, R. et al. 2000. Production Data Integration in Sand/Shale Reservoirs Using Sequential Self-Calibration and GeoMorphing: A Comparison. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 1–4 October. SPE-63063-MS. http://dx.doi.org/10.2118/63063-MS.