LAPSE:2018.0204
Published Article
LAPSE:2018.0204
Real-Time Optimization under Uncertainty Applied to a Gas Lifted Well Network
Dinesh Krishnamoorthy, Bjarne Foss, Sigurd Skogestad
July 30, 2018
In this work, we consider the problem of daily production optimization in the upstream oil and gas domain. The objective is to find the optimal decision variables that utilize the production systems efficiently and maximize the revenue. Typically, mathematical models are used to find the optimal operation in such processes. However, such prediction models are subject to uncertainty that has been often overlooked, and the optimal solution based on nominal models can thus render the solution useless and may lead to infeasibility when implemented. To ensure robust feasibility, worst case optimization may be employed; however, the solution may be rather conservative. Alternatively, we propose the use of scenario-based optimization to reduce the conservativeness. The results of the nominal, worst case and scenario-based optimization are compared and discussed.
Keywords
gas lift optimization, real-time optimization (RTO), scenario tree, uncertainty, worst case optimization
Suggested Citation
Krishnamoorthy D, Foss B, Skogestad S. Real-Time Optimization under Uncertainty Applied to a Gas Lifted Well Network. (2018). LAPSE:2018.0204
Author Affiliations
Krishnamoorthy D: Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway [ORCID]
Foss B: Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
Skogestad S: Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
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Journal Name
Processes
Volume
4
Issue
4
Article Number
E52
Year
2016
Publication Date
2016-12-15
Published Version
ISSN
2227-9717
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PII: pr4040052, Publication Type: Journal Article
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LAPSE:2018.0204
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doi:10.3390/pr4040052
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Jul 30, 2018
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