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Computational Geosciences

, Volume 21, Issue 3, pp 479–497 | Cite as

Multiple shooting applied to robust reservoir control optimization including output constraints on coherent risk measures

  • Andrés CodasEmail author
  • Kristian G. Hanssen
  • Bjarne Foss
  • Andrea Capolei
  • John Bagterp Jørgensen
Original Paper

Abstract

The production life of oil reservoirs starts under significant uncertainty regarding the actual economical return of the recovery process due to the lack of oil field data. Consequently, investors and operators make management decisions based on a limited and uncertain description of the reservoir. In this work, we propose a new formulation for robust optimization of reservoir well controls. It is inspired by the multiple shooting (MS) method which permits a broad range of parallelization opportunities and output constraint handling. This formulation exploits coherent risk measures, a concept traditionally used in finance, to bound the risk on constraint violation. We propose a reduced sequential quadratic programming (rSQP) algorithm to solve the underlying optimization problem. This algorithm exploits the structure of the coherent risk measures, thus a large set of constraints are solved within sub-problems. Moreover, a variable elimination procedure allows solving the optimization problem in a reduced space and an iterative active-set method helps to handle a large set of inequality constraints. Finally, we demonstrate the application of constraints to bound the risk of water production peaks rather than worst-case satisfaction.

Keywords

Risk management Reservoir management Waterflooding Control optimization 

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of Engineering CyberneticsNorwegian University of Science and TechnologyTrondheimNorway
  2. 2.Department of Applied Mathematics and Computer Science & Center for Energy Resources EngineeringTechnical University of DenmarkLyngbyDenmark
  3. 3.IBM ResearchRio de JaneiroBrazil

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