REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION

Detalhes bibliográficos
Autor(a) principal: Steffens, Lindaura Maria
Data de Publicação: 2017
Outros Autores: Lanznaster, Dara Liandra
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Interdisciplinar de Pesquisa em Engenharia
Texto Completo: https://periodicos.unb.br/index.php/ripe/article/view/21703
Resumo: Results obtained by numerical simulations techniques are used in the whole productive life of the reservoir, since exploration until enhanced oil recovery. Numerical simulations involves many cells and heterogeneities and are still limited by the computational time and memory. Reducing Order Methods are a solution to these problems. These methods allow the transformation of high-dimensional models into meaningful representations. It reduces the dimension of the matrices used during the simulations, and consequently, the time and effort. One of the methods used to get a reduced model is the Proper Orthogonal Decomposition (POD). In this work, the mathematical model and equations of a considered reservoir are first presented, and in sequence the discrete system obtained by Finite Difference and Finite Volumes methods. Then, the POD procedure will be described and applied to the problem considered. Finally, the size of new matrices and pressures will be evaluated before and after the reduction, as well as the error involved. The results obtained after the reduction agreed with the physical of the problem and, as expected, the number of unknowns reduced significantly.
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spelling REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATIONReservoir Simulation. Reduced Order Methods. Proper Orthogonal Decomposition.Results obtained by numerical simulations techniques are used in the whole productive life of the reservoir, since exploration until enhanced oil recovery. Numerical simulations involves many cells and heterogeneities and are still limited by the computational time and memory. Reducing Order Methods are a solution to these problems. These methods allow the transformation of high-dimensional models into meaningful representations. It reduces the dimension of the matrices used during the simulations, and consequently, the time and effort. One of the methods used to get a reduced model is the Proper Orthogonal Decomposition (POD). In this work, the mathematical model and equations of a considered reservoir are first presented, and in sequence the discrete system obtained by Finite Difference and Finite Volumes methods. Then, the POD procedure will be described and applied to the problem considered. Finally, the size of new matrices and pressures will be evaluated before and after the reduction, as well as the error involved. The results obtained after the reduction agreed with the physical of the problem and, as expected, the number of unknowns reduced significantly.Programa de Pós-Graduação em Integridade de Materiais da Engenharia2017-02-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.unb.br/index.php/ripe/article/view/2170310.26512/ripe.v2i21.21703Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 21 (2016): ADVANCED GRIDDING AND DISCRETIZATION TECHNIQUES FOR PETROLEUM RESERVOIR; 145-156Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 21 (2016): ADVANCED GRIDDING AND DISCRETIZATION TECHNIQUES FOR PETROLEUM RESERVOIR; 145-1562447-6102reponame:Revista Interdisciplinar de Pesquisa em Engenhariainstname:Universidade de Brasília (UnB)instacron:UNBenghttps://periodicos.unb.br/index.php/ripe/article/view/21703/20015Copyright (c) 2019 Revista Interdisciplinar de Pesquisa em Engenharia - RIPEinfo:eu-repo/semantics/openAccessSteffens, Lindaura MariaLanznaster, Dara Liandra2019-05-22T14:41:57Zoai:ojs.pkp.sfu.ca:article/21703Revistahttps://periodicos.unb.br/index.php/ripePUBhttps://periodicos.unb.br/index.php/ripe/oaianflor@unb.br2447-61022447-6102opendoar:2019-05-22T14:41:57Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB)false
dc.title.none.fl_str_mv REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
title REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
spellingShingle REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
Steffens, Lindaura Maria
Reservoir Simulation. Reduced Order Methods. Proper Orthogonal Decomposition.
title_short REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
title_full REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
title_fullStr REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
title_full_unstemmed REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
title_sort REDUCING ORDER METHODS APPLIED TO RESERVOIR SIMULATION
author Steffens, Lindaura Maria
author_facet Steffens, Lindaura Maria
Lanznaster, Dara Liandra
author_role author
author2 Lanznaster, Dara Liandra
author2_role author
dc.contributor.author.fl_str_mv Steffens, Lindaura Maria
Lanznaster, Dara Liandra
dc.subject.por.fl_str_mv Reservoir Simulation. Reduced Order Methods. Proper Orthogonal Decomposition.
topic Reservoir Simulation. Reduced Order Methods. Proper Orthogonal Decomposition.
description Results obtained by numerical simulations techniques are used in the whole productive life of the reservoir, since exploration until enhanced oil recovery. Numerical simulations involves many cells and heterogeneities and are still limited by the computational time and memory. Reducing Order Methods are a solution to these problems. These methods allow the transformation of high-dimensional models into meaningful representations. It reduces the dimension of the matrices used during the simulations, and consequently, the time and effort. One of the methods used to get a reduced model is the Proper Orthogonal Decomposition (POD). In this work, the mathematical model and equations of a considered reservoir are first presented, and in sequence the discrete system obtained by Finite Difference and Finite Volumes methods. Then, the POD procedure will be described and applied to the problem considered. Finally, the size of new matrices and pressures will be evaluated before and after the reduction, as well as the error involved. The results obtained after the reduction agreed with the physical of the problem and, as expected, the number of unknowns reduced significantly.
publishDate 2017
dc.date.none.fl_str_mv 2017-02-08
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.unb.br/index.php/ripe/article/view/21703
10.26512/ripe.v2i21.21703
url https://periodicos.unb.br/index.php/ripe/article/view/21703
identifier_str_mv 10.26512/ripe.v2i21.21703
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.unb.br/index.php/ripe/article/view/21703/20015
dc.rights.driver.fl_str_mv Copyright (c) 2019 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2019 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Programa de Pós-Graduação em Integridade de Materiais da Engenharia
publisher.none.fl_str_mv Programa de Pós-Graduação em Integridade de Materiais da Engenharia
dc.source.none.fl_str_mv Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 21 (2016): ADVANCED GRIDDING AND DISCRETIZATION TECHNIQUES FOR PETROLEUM RESERVOIR; 145-156
Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 21 (2016): ADVANCED GRIDDING AND DISCRETIZATION TECHNIQUES FOR PETROLEUM RESERVOIR; 145-156
2447-6102
reponame:Revista Interdisciplinar de Pesquisa em Engenharia
instname:Universidade de Brasília (UnB)
instacron:UNB
instname_str Universidade de Brasília (UnB)
instacron_str UNB
institution UNB
reponame_str Revista Interdisciplinar de Pesquisa em Engenharia
collection Revista Interdisciplinar de Pesquisa em Engenharia
repository.name.fl_str_mv Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB)
repository.mail.fl_str_mv anflor@unb.br
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