Abstract
In this work we presents a comparison of different optimization methods for the automatic history matching problem of reservoir simulation. The history matching process is an inverse problem that searches a set of parameters that minimizes the difference between the model performance and the historical performance of the field. This model validation process is essential and gives credibility to the predictions of the reservoir model. Derivative-based methods are compared to a free-derivative algorithm. In particular, we compare the Quasi-Newton method, non-linear Conjugate-Gradient, Steepest-Descent and a Genetic Algorithm implementation. Several tests are performed and the preliminary results are presented and discussed.
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Oliver, D.S., Albert, C.R., Liu, N.: Inverse theory for Petroleum Reservoir Characterization and History Matching. Cambridge University Press, Cambridge (2008)
Watson, A.T., Wade, J.G., Ewing, R.E.: Parameter and system identification for fluid flow in underground reservoirs. In: Conference on Inverse Problems and Optimal Design in Industry, Philadelphia (1994)
Brun, B., Gosselin, O., Barker, J.W.: Use of Prior Information in Gradient-Based History-Matching. In: SPE Reservoir Simulation Symposium, pp. 13–23 (2001)
Soleng, H.: Oil reservoir production forecasting with uncertainty estimation using genetic algorithms. In: Congress on Evolutionary Computation, pp. 1217–1223 (1999)
Versteeg, H., Malalasekra, W.: An Introduction to Computational Fluid Dynamics: The Finite Volume Method, 2nd edn. Prentice Hall, Harlow (2007)
Chen, Z., Huan, G., Li, B.: An improved IMPES method for two-phase flow in porous media. Transport in Porous Media 32, 261–276 (2004)
Luenberg, D.G.: Introduction to Linear and Nonlinear Programming. Addison-Wesley, Reading (1973)
Coley, D.A.: An Introduction to Genetic Algorithms for Scientists and Engineers. World Scientific Publishing Company, River Egde (1997)
Balay, S., Buschelman, K., Gropp, W.D., et al.: PETSc users manual. Technical Report ANL-95/11, Argonne National Laboratory (2002)
Galassi, M., Davies, J., Theiler, J., et al.: GNU Scientific Library Reference Manual. Network Theory, Bristol (2006)
Message Passing Interface Forum: MPI, a message-passing interface standard. Oregon Graduate Institute School of Science & Engineering (1994)
Chen, Z.: Reservoir Simulation: Mathematical Techniques in Oil Recovery. Society for Industrial and Applied Mathematics (2007)
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dos Santos, E.P., Xavier, C.R., Goldfeld, P., Dickstein, F., Weber dos Santos, R. (2009). Comparing Genetic Algorithms and Newton-Like Methods for the Solution of the History Matching Problem. In: Allen, G., Nabrzyski, J., Seidel, E., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2009. Lecture Notes in Computer Science, vol 5544. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01970-8_37
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DOI: https://doi.org/10.1007/978-3-642-01970-8_37
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