Abstract
This work proposes a new hierarchical multiscale optimization technique to improve the performance of life-cycle production optimization. This approach represents a combination of two previous multiscale approaches presented in the literature and is theoretically motivated by the concept of refinement indicators. The new algorithm is applied to two example problems, and its performance is compared with other life-cycle production optimization algorithms that have been proposed in the literature including the two hierarchical multiscale optimization methods on which it is based. In a separate paper (Oliveira and Reynolds 2015), the proposed algorithm is successfully applied to a field case.
Similar content being viewed by others
References
Asadollahi, M., Nævdal, G.: Selection of decision variables for large-scale production optimization problems applied to Brugge field. In: Proceedings of the SPE Russian Oil & Gas Techinical Conference and Exhibition. SPE 136378 (2010)
Asheim, H.: Maximization of water sweep efficiency by controlling production and injection rates. In: Proceedings of the SPE European Petroleum Conference. SPE 18365 (1988)
Ben Ameur, H., Chavent, G., Jaffré, J.: Refinement and coarsening indicators for adaptive parametrization: application to the estimation of hydraulic transmissivities. Inverse Prob. 18, 775–794 (2002)
Brouwer, D.R., Nævdal, G., Jansen, J.D., Vefring, E.H., van Kruijsdijk, C.P.J.W.: Improved reservoir management through optimal control and continuous model updating. In: Proceedings of the SPE Annual Technical Conference and Exhibition, Houston, Texas, 26–29 September. SPE 90149 (2004)
Chavent, G.M., Bissell, R.: Indicators for the refinement of parametrization. In: Tanaka, M., Dulikravich, G.S. (eds.) Inverse Problems in Engineering Mechanics. Elsevier, Amsterdam (1998)
Chen, C.: Adjoint-gradient-based production optimization with the augmented Lagrangian Method, PhD. thesis, University of Tulsa, Tulsa, Oklahoma, USA (2011)
Chen, Y., Oliver, D.S., Zhang, D.: Efficient ensemble-based closed-loop production optimization. SPE J. 14(4), 634–645 (2009)
Conn, A., Gould, N., Toint, P.: A globally convergent augmented langrangian algorithm for optimization with general constraints and simple bounds. SIAM J. Numer. Anal. 28(2), 545–572 (1991)
Gao, G., Reynolds, A.C.: An improved implementation of the LBFGS algorithm for automatic history matching. SPE J. 11(1), 5–17 (2006)
Jansen, J., Brouwer, D., Naevdal, G., van Kruijsdijk, C.: Closed-loop reservoir management. First Break 23, 43–48 (2005)
Lien, M., Brouwer, D.R., Mannseth, T., Jansen, J.D.: Multiscale regularization of flooding optimization for smart field management. SPE J. 13(2), 195–204 (2008)
Lorentzen, R.J., Berg, A.M., Nævdal, G., Vefring, E.H.: A new approach for dynamic optimization of waterflooding problems. In: Proceedings of the SPE Intelligent Energy Conference and Exhibition. SPE 99690 (2006)
Nocedal, J., Wright, S.J.: Numerical Optimization. Springer, New York (2006)
Oliveira, D.F., Reynolds, A.: An adaptive hierarchical multiscale algorithm for estimation of optimal well. SPE J. 19(5), 909–930 (2014). SPE-163645-PA
Oliveira, D.F., Reynolds, A.C.: Hierarchical multiscale methods for life-cycle production optimization: a field case study. SPE J. Preprint. SPE-173273-PA (2015)
Oliveira, D.F.B.: A new hierarchical multiscale optimization method: gradient and non-gradient approaches for waterflooding optimization, Ph.D. thesis, The University of Tulsa, Tulsa, Oklahoma (2014)
Peters, L., Arts, R., Brouwer, G., Geel, C., Cullick, S., Lorentzen, R., Chen, Y., Dunlop, K., Vossepoel, F., Xu, R., Sarma, P., Alhuthali, A., Reynolds, A.: Results of the Brugge benchmark study for flooding optimisation and history matching. SPE Reserv. Eval. Eng. 13(3), 391–405 (2010)
Sarma, P., Chen, W., Durlofsky, L., Aziz, K.: Production optimization with adjoint models under nonlinear control-state path inequality constraints. SPE Reserv. Eval. Eng. 11(2), 326–339 (2008)
Sarma, P., Durlofsky, L., Aziz, K.: Implementation of adjoint solution for optimal control of smart wells. In: Proceedings of the SPE Reservoir Simulation Symposium. SPE 92864 (2005)
Sarma, P., Durlofsky, L., Aziz, K., Chen, W.: Efficient real-time reservoir management using adjoint-based optimal control and model updating. Comput. Geosci. 10, 3–36 (2006)
Schlumberger Ltd.: ECLIPSE Reservoir Simulation Software: Reference Manual, Schlumberger Software, London, UK www.slb.com, version 2011.2 edn., 2011
Shuai, Y., White, C.D., Zhang, H., Sun, T.: Using multiscale regularization to obtain realistic optimal control strategies. In: Proccedings of the SPE Reservoir Simulation Symposium, The Woodlands, Texas, USA, 21–23 February. SPE 142043 (2011)
Wang, C., Li, G., Reynolds, A.C.: Production optimization in closed-loop reservoir management. SPE J. 14(3), 506–523 (2009)
Zakirov, I.S., Aanonsen, S.I., Zakirov, E.S., Palatnik, B.M.: Optimizating reservoir performance by automatic allocation of well rates. In: Proceedings of the 5th European Conference on the Mathematical Oil Recovery - Leoben, Austria, 3–5 September (1996)
Zhao, H., Chen, C., Do, S., Oliveira, D., Li, G., Reynolds, A.: Maximization of a dynamic quadratic interpolation model for production optimization. SPE J. 18(6), 1012–1025 (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Oliveira, D.F.B., Reynolds, A.C. & Jansen, J.D. An improved multiscale method for life-cycle production optimization. Comput Geosci 19, 1139–1157 (2015). https://doi.org/10.1007/s10596-015-9530-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10596-015-9530-7