Optimisation of gas-lifted system using nonlinear model predictive control.
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/3/3139/tde-26042023-151430/ |
Resumo: | Gas-lifted system like every other artificial lift system is used when the natural energy for lifting crude oil from the reservoir into the downstream facilities becomes insufficient. This research focused on optimising crude oil recovery from gas-lifted oil well by using nonlinear model predictive control (NMPC). Two key approaches were used: (a) casingheading instability reduction/elimination and (b) fault-tolerant control in the system. At first a developed nonlinear model predictive controller (NMPC) was presented. The controller was tested on continuous stirred tank reactor (CSTR) using IPOPT solver in CasADi and fmincon optimizer in MATLAB. Finite horizon NMPC was selected and used to optimise the gas-lifted system. The controller stabilised the undisturbed system improving production by 5.63% compared to the open-loop operation when the system is in casing-heading instability. For the two input case, the steady state production, aided by the high input target, reached 12.25kg/s which is far more than 9.57 kg/s for the one input case. This controller showed a 3.76% improvement over PI controller for the same purpose. Estimation performances of three nonlinear filters were compared and Extended Kalman filter was selected to provide the estimated states of the system which were used for fault-tolerant control of the gas-lifted system. Passive FTC, altering control bound and altering control cost were used to implement the FTC problems. Passive FTC provided more robustness but small output change. Reducing the upper control bound ensured stability but production could decline. Increasing the controller cost that prioritised the input target increased production but it was prone to casing-heading instability. While the FTC scheme could reduce the downtime, the casing-heading instability removal increases the average oil production rate hence optimising the gas-lifted system. |
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Optimisation of gas-lifted system using nonlinear model predictive control.Otimização do sistema de elevação a gás usando controle preditivo de modelo não linear.Casing-heading instabilityControle preditivo de modelo não linearControle tolerante a falhasFault-tolerant controlGas liftInstabilidade do cabeçote do revestimentoModel predictive controlOptimisationOtimizaçãoSistema de elevação a gásGas-lifted system like every other artificial lift system is used when the natural energy for lifting crude oil from the reservoir into the downstream facilities becomes insufficient. This research focused on optimising crude oil recovery from gas-lifted oil well by using nonlinear model predictive control (NMPC). Two key approaches were used: (a) casingheading instability reduction/elimination and (b) fault-tolerant control in the system. At first a developed nonlinear model predictive controller (NMPC) was presented. The controller was tested on continuous stirred tank reactor (CSTR) using IPOPT solver in CasADi and fmincon optimizer in MATLAB. Finite horizon NMPC was selected and used to optimise the gas-lifted system. The controller stabilised the undisturbed system improving production by 5.63% compared to the open-loop operation when the system is in casing-heading instability. For the two input case, the steady state production, aided by the high input target, reached 12.25kg/s which is far more than 9.57 kg/s for the one input case. This controller showed a 3.76% improvement over PI controller for the same purpose. Estimation performances of three nonlinear filters were compared and Extended Kalman filter was selected to provide the estimated states of the system which were used for fault-tolerant control of the gas-lifted system. Passive FTC, altering control bound and altering control cost were used to implement the FTC problems. Passive FTC provided more robustness but small output change. Reducing the upper control bound ensured stability but production could decline. Increasing the controller cost that prioritised the input target increased production but it was prone to casing-heading instability. While the FTC scheme could reduce the downtime, the casing-heading instability removal increases the average oil production rate hence optimising the gas-lifted system.O sistema de elevação a gás (gas lift, do inglês), como qualquer outro sistema de elevação artificial, é usado quando a energia natural para elevar o petróleo bruto do reservatório para as instalações a jusante se torna insuficiente. Esta pesquisa se concentrou na otimização da recuperação de petróleo bruto do poço de petróleo levantado a gás usando o controle preditivo de modelo não linear (NMPC, do inglês). Duas abordagens principais foram usadas: (a) redução/eliminação da instabilidade do cabeçote do revestimento e (b) controle tolerante a falhas no sistema. Inicialmente foi apresentado um NMPC desenvolvido. O controlador foi testado em reator de tanque agitado contínuo (CSTR), usando o solver de otimizações IPOPT no CasADi e o otimizador fmincon no MATLAB. O NMPC de horizonte finito foi selecionado e usado para otimizar o sistema gas-lifted. O controlador estabilizou o sistema não perturbado, melhorando a produção em 5,63% em comparação com a operação em malha aberta quando o sistema está em instabilidade de cabeçote de revestimento. A produção em estado estacionário, auxiliada pela alto alvo de entrada, atingiu 12,25 kg/s, muito mais do que 9,57 kg/s obtidos no caso de uma entrada. Este controlador apresentou uma melhoria de 3,76% em relação ao controlador PI (proporcional-integral) para o mesmo caso. O desempenho de estimativa de três filtros não lineares foram comparados e o filtro de Kalman estendido foi selecionado para estimar estados do sistema, que foram usados para controle tolerante a falhas (FTC, do inglês) do sistema de elevação a gás. FTC passivo, alterando limite de controle e alterando custo de controle foram usados para implementar os problemas de FTC. O FTC passivo forneceu mais robustez, mas pequena alteração na produção. Redução do limite superior de controle garantiu a estabilidade, mas a produção pode diminuir. Aumento do custo do controlador que priorizou o alvo de entrada aumentou a produção, mas estava propenso a instabilidade do cabeçote do revestimento. Enquanto o esquema FTC pudesse reduzir o tempo de inatividade, a remoção da instabilidade do cabeçote do revestimento aumenta a taxa média de produção de óleo, otimizando o sistema de elevação a gás.Biblioteca Digitais de Teses e Dissertações da USPKassab Junior, FuadAdukwu, Ojonugwa2023-03-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/3/3139/tde-26042023-151430/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2023-04-27T17:15:07Zoai:teses.usp.br:tde-26042023-151430Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212023-04-27T17:15:07Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Optimisation of gas-lifted system using nonlinear model predictive control. Otimização do sistema de elevação a gás usando controle preditivo de modelo não linear. |
title |
Optimisation of gas-lifted system using nonlinear model predictive control. |
spellingShingle |
Optimisation of gas-lifted system using nonlinear model predictive control. Adukwu, Ojonugwa Casing-heading instability Controle preditivo de modelo não linear Controle tolerante a falhas Fault-tolerant control Gas lift Instabilidade do cabeçote do revestimento Model predictive control Optimisation Otimização Sistema de elevação a gás |
title_short |
Optimisation of gas-lifted system using nonlinear model predictive control. |
title_full |
Optimisation of gas-lifted system using nonlinear model predictive control. |
title_fullStr |
Optimisation of gas-lifted system using nonlinear model predictive control. |
title_full_unstemmed |
Optimisation of gas-lifted system using nonlinear model predictive control. |
title_sort |
Optimisation of gas-lifted system using nonlinear model predictive control. |
author |
Adukwu, Ojonugwa |
author_facet |
Adukwu, Ojonugwa |
author_role |
author |
dc.contributor.none.fl_str_mv |
Kassab Junior, Fuad |
dc.contributor.author.fl_str_mv |
Adukwu, Ojonugwa |
dc.subject.por.fl_str_mv |
Casing-heading instability Controle preditivo de modelo não linear Controle tolerante a falhas Fault-tolerant control Gas lift Instabilidade do cabeçote do revestimento Model predictive control Optimisation Otimização Sistema de elevação a gás |
topic |
Casing-heading instability Controle preditivo de modelo não linear Controle tolerante a falhas Fault-tolerant control Gas lift Instabilidade do cabeçote do revestimento Model predictive control Optimisation Otimização Sistema de elevação a gás |
description |
Gas-lifted system like every other artificial lift system is used when the natural energy for lifting crude oil from the reservoir into the downstream facilities becomes insufficient. This research focused on optimising crude oil recovery from gas-lifted oil well by using nonlinear model predictive control (NMPC). Two key approaches were used: (a) casingheading instability reduction/elimination and (b) fault-tolerant control in the system. At first a developed nonlinear model predictive controller (NMPC) was presented. The controller was tested on continuous stirred tank reactor (CSTR) using IPOPT solver in CasADi and fmincon optimizer in MATLAB. Finite horizon NMPC was selected and used to optimise the gas-lifted system. The controller stabilised the undisturbed system improving production by 5.63% compared to the open-loop operation when the system is in casing-heading instability. For the two input case, the steady state production, aided by the high input target, reached 12.25kg/s which is far more than 9.57 kg/s for the one input case. This controller showed a 3.76% improvement over PI controller for the same purpose. Estimation performances of three nonlinear filters were compared and Extended Kalman filter was selected to provide the estimated states of the system which were used for fault-tolerant control of the gas-lifted system. Passive FTC, altering control bound and altering control cost were used to implement the FTC problems. Passive FTC provided more robustness but small output change. Reducing the upper control bound ensured stability but production could decline. Increasing the controller cost that prioritised the input target increased production but it was prone to casing-heading instability. While the FTC scheme could reduce the downtime, the casing-heading instability removal increases the average oil production rate hence optimising the gas-lifted system. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-03-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/3/3139/tde-26042023-151430/ |
url |
https://www.teses.usp.br/teses/disponiveis/3/3139/tde-26042023-151430/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
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1815257357980008448 |