dc.contributor.author | Hulse, Eduardo O. | |
dc.contributor.author | Silva, Thiago Lima | |
dc.contributor.author | Camponogara, Eduardo | |
dc.contributor.author | Rosa, Vinicius R. | |
dc.contributor.author | Vieira, Bruno F. | |
dc.contributor.author | Furtado, Alex Teixeira | |
dc.date.accessioned | 2020-02-13T11:43:23Z | |
dc.date.available | 2020-02-13T11:43:23Z | |
dc.date.created | 2020-02-10T09:54:55Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 0098-1354 | |
dc.identifier.uri | http://hdl.handle.net/11250/2641516 | |
dc.description.abstract | Most of the literature on short-term production optimization concerns the computation of optimal system settings for steady-state operations. Such methodologies are applicable when the scales of time are faster than reservoir dynamics, and slower than the dynamics of top-side equipment. Effectively static problems are solved over time in response to changes in the prevailing conditions, which will remain persistent for long periods. However, when platform conditions change frequently or suddenly possibly due to reduced processing capacity, the dynamics of wells should not be neglected and well operations should be scheduled over time. To this end, this paper proposes a novel mathematical formulation for production optimization when dynamics matters, specifically when wells are shut-in (due to processing capacity drops) and restarted later as the normal conditions are recovered. The effectiveness of the methodology to schedule well operations is assessed by simulation of synthetic and field cases involving an offshore production platform. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Elsevier | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Introducing Approximate Well Dynamics into Production Optimization for Operations Scheduling | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.journal | Computers and Chemical Engineering | nb_NO |
dc.identifier.doi | 10.1016/j.compchemeng.2020.106773 | |
dc.identifier.cristin | 1792457 | |
dc.description.localcode | © 2020. This is the authors’ accepted and refereed manuscript to the article. Locked until 6.2.2022 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | nb_NO |
cristin.unitcode | 194,64,90,0 | |
cristin.unitname | Institutt for geovitenskap og petroleum | |
cristin.ispublished | false | |
cristin.fulltext | postprint | |
cristin.qualitycode | 2 | |