dc.contributor.author | Jahanshahi, Esmaeil | |
dc.contributor.author | Krishnamoorthy, Dinesh | |
dc.contributor.author | Codas Duarte, Andres | |
dc.contributor.author | Foss, Bjarne Anton | |
dc.contributor.author | Skogestad, Sigurd | |
dc.date.accessioned | 2021-02-19T10:48:12Z | |
dc.date.available | 2021-02-19T10:48:12Z | |
dc.date.created | 2020-11-05T09:37:47Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Computers and Chemical Engineering. 2020, 136 1-14. | en_US |
dc.identifier.issn | 0098-1354 | |
dc.identifier.uri | https://hdl.handle.net/11250/2729166 | |
dc.description.abstract | In this paper, we consider Real-Time Optimization (RTO) and control of an oil production system. We follow a systematic plantwide control procedure. The process consists of two gas-lift oil wells connected to a pipeline-riser system, and a separator at the topside platform. When the gas injection rates are low, the desired steady flow regime may become unstable and change to slug flow due to the casing-heading phenomenon. Therefore, a regulatory control layer is required to stabilize the desired two-phase flow regime. To this end, we propose a new control structure using two pressure measurements, one at the well-head and one at the annulus. For the optimization layer, we compare the performance of nonlinear Economic Model Predictive Control (EMPC), dynamic Feedback-RTO (FRTO) and Self-Optimizing Control (SOC). Based on dynamic simulations using the realistic OLGA simulator, we find that SOC is the most practical approach. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Plantwide control of an oil production network | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.pagenumber | 1-14 | en_US |
dc.source.volume | 136 | en_US |
dc.source.journal | Computers and Chemical Engineering | en_US |
dc.identifier.doi | 10.1016/j.compchemeng.2020.106765 | |
dc.identifier.cristin | 1845116 | |
dc.description.localcode | © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/) | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |