Energy optimization of an FPSO operating in the Brazilian Pre-salt region
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.energy.2018.08.203 http://hdl.handle.net/11449/184977 |
Resumo: | FPSO (Floating, Production, Storage and Offloading) units are used for primary petroleum processing. The FPSO units have a technical advantage for short-lived well exploration and for remote marginal fields, where building a pipeline is cost-prohibitive. Considering the relevance of the FPSOs for the Brazilian petroleum market, the main goal of this paper is to present an optimization procedure to find the best operating conditions of a primary petroleum platform processing crude oil with high gas-oil ratio (GOR) and moderate CO2 content. Seven input parameters related to operating pressures of plant are selected for the optimization procedure aiming to minimize the total fuel consumption (FUE) of the FPSO. For the optimization procedure, the processing plant of the FPSO is modeled and simulated by using Aspen HYSYS (R), and the Genetic Algorithm is used for minimizing the objective function. The optimum operating condition found by the optimization procedure presented a reduction in fuel consumption by 4.6% when compared to a conventional operating condition. Moreover, because of the fuel consumption optimization, a significant reduction by 63% in the power consumption of the plant and an improvement in the recovery of the volatile components were verified, in comparison with the baseline case. (C) 2018 Elsevier Ltd. All rights reserved. |
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Energy optimization of an FPSO operating in the Brazilian Pre-salt regionOffshore oil and gas processing platformThermodynamic analysisOptimizationGenetic algorithmFPSO (Floating, Production, Storage and Offloading) units are used for primary petroleum processing. The FPSO units have a technical advantage for short-lived well exploration and for remote marginal fields, where building a pipeline is cost-prohibitive. Considering the relevance of the FPSOs for the Brazilian petroleum market, the main goal of this paper is to present an optimization procedure to find the best operating conditions of a primary petroleum platform processing crude oil with high gas-oil ratio (GOR) and moderate CO2 content. Seven input parameters related to operating pressures of plant are selected for the optimization procedure aiming to minimize the total fuel consumption (FUE) of the FPSO. For the optimization procedure, the processing plant of the FPSO is modeled and simulated by using Aspen HYSYS (R), and the Genetic Algorithm is used for minimizing the objective function. The optimum operating condition found by the optimization procedure presented a reduction in fuel consumption by 4.6% when compared to a conventional operating condition. Moreover, because of the fuel consumption optimization, a significant reduction by 63% in the power consumption of the plant and an improvement in the recovery of the volatile components were verified, in comparison with the baseline case. (C) 2018 Elsevier Ltd. All rights reserved.National Agency of Petroleum, Natural Gas and Biofuels (ANP)Shell Brazil Ltda, through the Investment in Research, Development and Innovation ClauseConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Sao Paulo, Sch Engn, Dept Mech Engn, Sao Paulo, BrazilSao Paulo State Univ, Dept Mech Engn, Ilha Solteira, BrazilFed Univ ABC, Energy Engn, Santo Andre, BrazilSao Paulo State Univ, Dept Mech Engn, Ilha Solteira, BrazilCNPq: 304935/2016-6CNPq: 307421/2014-7Elsevier B.V.Universidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Allahyarzadeh-Bidgoli, AliSalviano, Leandro Oliveira [UNESP]Dezan, Daniel JonasOliveira Junior, Silvio deYanagihara, Jurandir Itizo2019-10-04T12:31:33Z2019-10-04T12:31:33Z2018-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article390-399http://dx.doi.org/10.1016/j.energy.2018.08.203Energy. Oxford: Pergamon-elsevier Science Ltd, v. 164, p. 390-399, 2018.0360-5442http://hdl.handle.net/11449/18497710.1016/j.energy.2018.08.203WOS:000448098600031Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnergyinfo:eu-repo/semantics/openAccess2024-07-04T20:06:14Zoai:repositorio.unesp.br:11449/184977Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:26:55.941300Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
title |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
spellingShingle |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region Allahyarzadeh-Bidgoli, Ali Offshore oil and gas processing platform Thermodynamic analysis Optimization Genetic algorithm |
title_short |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
title_full |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
title_fullStr |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
title_full_unstemmed |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
title_sort |
Energy optimization of an FPSO operating in the Brazilian Pre-salt region |
author |
Allahyarzadeh-Bidgoli, Ali |
author_facet |
Allahyarzadeh-Bidgoli, Ali Salviano, Leandro Oliveira [UNESP] Dezan, Daniel Jonas Oliveira Junior, Silvio de Yanagihara, Jurandir Itizo |
author_role |
author |
author2 |
Salviano, Leandro Oliveira [UNESP] Dezan, Daniel Jonas Oliveira Junior, Silvio de Yanagihara, Jurandir Itizo |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Estadual Paulista (Unesp) Universidade Federal do ABC (UFABC) |
dc.contributor.author.fl_str_mv |
Allahyarzadeh-Bidgoli, Ali Salviano, Leandro Oliveira [UNESP] Dezan, Daniel Jonas Oliveira Junior, Silvio de Yanagihara, Jurandir Itizo |
dc.subject.por.fl_str_mv |
Offshore oil and gas processing platform Thermodynamic analysis Optimization Genetic algorithm |
topic |
Offshore oil and gas processing platform Thermodynamic analysis Optimization Genetic algorithm |
description |
FPSO (Floating, Production, Storage and Offloading) units are used for primary petroleum processing. The FPSO units have a technical advantage for short-lived well exploration and for remote marginal fields, where building a pipeline is cost-prohibitive. Considering the relevance of the FPSOs for the Brazilian petroleum market, the main goal of this paper is to present an optimization procedure to find the best operating conditions of a primary petroleum platform processing crude oil with high gas-oil ratio (GOR) and moderate CO2 content. Seven input parameters related to operating pressures of plant are selected for the optimization procedure aiming to minimize the total fuel consumption (FUE) of the FPSO. For the optimization procedure, the processing plant of the FPSO is modeled and simulated by using Aspen HYSYS (R), and the Genetic Algorithm is used for minimizing the objective function. The optimum operating condition found by the optimization procedure presented a reduction in fuel consumption by 4.6% when compared to a conventional operating condition. Moreover, because of the fuel consumption optimization, a significant reduction by 63% in the power consumption of the plant and an improvement in the recovery of the volatile components were verified, in comparison with the baseline case. (C) 2018 Elsevier Ltd. All rights reserved. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-01 2019-10-04T12:31:33Z 2019-10-04T12:31:33Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.energy.2018.08.203 Energy. Oxford: Pergamon-elsevier Science Ltd, v. 164, p. 390-399, 2018. 0360-5442 http://hdl.handle.net/11449/184977 10.1016/j.energy.2018.08.203 WOS:000448098600031 |
url |
http://dx.doi.org/10.1016/j.energy.2018.08.203 http://hdl.handle.net/11449/184977 |
identifier_str_mv |
Energy. Oxford: Pergamon-elsevier Science Ltd, v. 164, p. 390-399, 2018. 0360-5442 10.1016/j.energy.2018.08.203 WOS:000448098600031 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Energy |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
390-399 |
dc.publisher.none.fl_str_mv |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128933795725312 |