Oilfield Production Optimisation Via Mixed-Integer Nonlinear Programming (MINLP)

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The integrated management of oil and gas operations is a challenging task involving short to long-term decisions. Some of these decisions include valve configurations, choke openings and complex well-manifold routings [1, 2]. Hence, novel advancements in mathematics, algorithm development [3, 4] and related scientific fields have found tremendous applications in the modelling, simulation and optimisation of complex phenomena for improved oilfield recovery. These methods hold strong potential for enhancing field profitability without additional facility/equipment installation costs or additional operations. In this study, it is demonstrated that a methodical application of simulation-based optimisation methods guarantees process enhancement by only finding the optimal well to manifold and pipeline to separator connections. This is achieved by developing explicit surrogate models, which are compatible with the adopted optimisation algorithms; thus, resulting in a Mixed-Integer Nonlinear Program (MINLP).
Original languageUndefined/Unknown
Title of host publication2020 AIChE Annual Meeting (Computing and Systems Technology Division; Systems and Process Operations)
Publication statusPublished - 20 Nov 2020
Event2020 Virtual AIChE Annual Meeting - Online
Duration: 16 Nov 202020 Nov 2020


Conference2020 Virtual AIChE Annual Meeting

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