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

Andrés Codas*, Kristian G. Hanssen, Bjarne Foss, Andrea Capolei, John Bagterp Jørgensen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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.

Original languageEnglish
JournalComputational Geosciences
Volume21
Issue number3
Pages (from-to)479-497
ISSN1420-0597
DOIs
Publication statusPublished - 2017

Keywords

  • Control optimization
  • Reservoir management
  • Risk management
  • Waterflooding

Cite this

Codas, Andrés ; Hanssen, Kristian G. ; Foss, Bjarne ; Capolei, Andrea ; Jørgensen, John Bagterp. / Multiple shooting applied to robust reservoir control optimization including output constraints on coherent risk measures. In: Computational Geosciences. 2017 ; Vol. 21, No. 3. pp. 479-497.
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Multiple shooting applied to robust reservoir control optimization including output constraints on coherent risk measures. / Codas, Andrés; Hanssen, Kristian G.; Foss, Bjarne; Capolei, Andrea; Jørgensen, John Bagterp.

In: Computational Geosciences, Vol. 21, No. 3, 2017, p. 479-497.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Multiple shooting applied to robust reservoir control optimization including output constraints on coherent risk measures

AU - Codas, Andrés

AU - Hanssen, Kristian G.

AU - Foss, Bjarne

AU - Capolei, Andrea

AU - Jørgensen, John Bagterp

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Control optimization

KW - Reservoir management

KW - Risk management

KW - Waterflooding

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