NMPC for Oil Reservoir Production Optimization

Carsten Völcker; John Bagterp Jørgensen; Per Grove Thomsen; Erling Halfdan Stenby

doi:10.1016/B978-0-444-54298-4.50148-3 |

NMPC for Oil Reservoir Production Optimization

Carsten Völcker, John Bagterp Jørgensen, Per Grove Thomsen, Erling Halfdan Stenby

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

In this paper, we use nonlinear model predictive control (NMPC) to maximize secondary oil recovery from an oil reservoir by controlling two-phase subsurface porous flow using adjustable down-hole control valves. The resulting optimal control problem is nonlinear and large-scale. We solve this problem numerically using a single shooting sequential quadratic programming (SQP) based optimization method. Explicit singly diagonally implicit Runge-Kutta (ESDIRK) methods are used for integration of the stiff system of differential equations describing the two-phase flow, and the adjoint method is used for sensitivity computations. We report computational experiences and oil recovery improvements for a standard test case.

Original language	English
Title of host publication	21st European Symposium on Computer Aided Process Engineering
Number of pages	2029
Publisher	Elsevier
Publication date	2011
Pages	1849-1853
ISBN (Print)	978-0-444-53895-6
DOIs	https://doi.org/10.1016/B978-0-444-54298-4.50148-3 \|
Publication status	Published - 2011
Event	21st European Symposium on Computer Aided Process Engineering - Chalkidiki, Greece Duration: 29 May 2011 → 1 Jun 2011 http://www.escape-21.gr/

Conference

Conference	21st European Symposium on Computer Aided Process Engineering
Country/Territory	Greece
City	Chalkidiki
Period	29/05/2011 → 01/06/2011
Internet address	http://www.escape-21.gr/

Series	Computer Aided Chemical Engineering
Number	29
ISSN	1570-7946

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title = "NMPC for Oil Reservoir Production Optimization",

abstract = "In this paper, we use nonlinear model predictive control (NMPC) to maximize secondary oil recovery from an oil reservoir by controlling two-phase subsurface porous flow using adjustable down-hole control valves. The resulting optimal control problem is nonlinear and large-scale. We solve this problem numerically using a single shooting sequential quadratic programming (SQP) based optimization method. Explicit singly diagonally implicit Runge-Kutta (ESDIRK) methods are used for integration of the stiff system of differential equations describing the two-phase flow, and the adjoint method is used for sensitivity computations. We report computational experiences and oil recovery improvements for a standard test case.",

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Völcker, C, Jørgensen, JB, Thomsen, PG & Stenby, EH 2011, NMPC for Oil Reservoir Production Optimization. in 21st European Symposium on Computer Aided Process Engineering. Elsevier, Computer Aided Chemical Engineering, no. 29, pp. 1849-1853, 21st European Symposium on Computer Aided Process Engineering, Chalkidiki, Greece, 29/05/2011. https://doi.org/10.1016/B978-0-444-54298-4.50148-3 |

NMPC for Oil Reservoir Production Optimization. / Völcker, Carsten; Jørgensen, John Bagterp; Thomsen, Per Grove et al.
21st European Symposium on Computer Aided Process Engineering. Elsevier, 2011. p. 1849-1853 (Computer Aided Chemical Engineering; No. 29).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - In this paper, we use nonlinear model predictive control (NMPC) to maximize secondary oil recovery from an oil reservoir by controlling two-phase subsurface porous flow using adjustable down-hole control valves. The resulting optimal control problem is nonlinear and large-scale. We solve this problem numerically using a single shooting sequential quadratic programming (SQP) based optimization method. Explicit singly diagonally implicit Runge-Kutta (ESDIRK) methods are used for integration of the stiff system of differential equations describing the two-phase flow, and the adjoint method is used for sensitivity computations. We report computational experiences and oil recovery improvements for a standard test case.

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Y2 - 29 May 2011 through 1 June 2011

ER -

NMPC for Oil Reservoir Production Optimization

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