In oil and gas industry, production optimization is a viable technique to maximize the recovery or the net present value (NPV). Robust optimization is one type of production optimization techniques where the geological uncertainty of reservoir is considered. When well operating conditions, e.g., well flow rates settings of inflow control valves and bottom-hole pressures, are the optimization variables, ensemble-based optimization (EnOpt) is the most popular ensemble-based algorithm for the robust life-cycle production optimization. Recently, a superior algorithm, stochastic simplex approximate gradient (StoSAG), was proposed. Fonseca and co-workers (2016, A Stochastic Simplex Approximate Gradient (StoSAG) for Optimization Under Uncertainty, Int. J. Numer. Methods Eng., 109(13), pp. 1756–1776) provided a theoretical argument on the superiority of StoSAG over EnOpt. However, it has not drawn significant attention in the reservoir optimization community. The purpose of this study is to provide a refined theoretical discussion on why StoSAG is generally superior to EnOpt and to provide a reasonable example (Brugge field) where StoSAG generates estimates of optimal well operating conditions that give a life-cycle NPV significantly higher than the NPV obtained from EnOpt.
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September 2019
Research-Article
Stochastic Simplex Approximate Gradient for Robust Life-Cycle Production Optimization: Applied to Brugge Field
Bailian Chen,
Bailian Chen
1
Computational Earth Science,
Los Alamos, NM 87544
e-mail: bailianchen@lanl.gov
Los Alamos National Laboratory
,Los Alamos, NM 87544
e-mail: bailianchen@lanl.gov
1Corresponding authors.
Search for other works by this author on:
Jianchun Xu
Jianchun Xu
1
School of Petroleum Engineering,
Qingdao, Shandong 266580,
e-mail: 20170048@upc.edu.cn
China University of Petroleum (East China)
,Qingdao, Shandong 266580,
China
e-mail: 20170048@upc.edu.cn
1Corresponding authors.
Search for other works by this author on:
Bailian Chen
Computational Earth Science,
Los Alamos, NM 87544
e-mail: bailianchen@lanl.gov
Los Alamos National Laboratory
,Los Alamos, NM 87544
e-mail: bailianchen@lanl.gov
Jianchun Xu
School of Petroleum Engineering,
Qingdao, Shandong 266580,
e-mail: 20170048@upc.edu.cn
China University of Petroleum (East China)
,Qingdao, Shandong 266580,
China
e-mail: 20170048@upc.edu.cn
1Corresponding authors.
Contributed by the Petroleum Division of ASME for publication in the Journal of Energy Resources Technology. Manuscript received May 17, 2018; final manuscript received March 12, 2019; published online April 4, 2019. Assoc. Editor: Fanhua Zeng.
J. Energy Resour. Technol. Sep 2019, 141(9): 092905 (11 pages)
Published Online: April 4, 2019
Article history
Received:
May 17, 2018
Revision Received:
March 12, 2019
Accepted:
March 14, 2019
Citation
Chen, B., and Xu, J. (April 4, 2019). "Stochastic Simplex Approximate Gradient for Robust Life-Cycle Production Optimization: Applied to Brugge Field." ASME. J. Energy Resour. Technol. September 2019; 141(9): 092905. https://doi.org/10.1115/1.4043244
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