A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding

Detalhes bibliográficos
Autor(a) principal: Ferreira, Niraldo R.
Data de Publicação: 2003
Outros Autores: Porsani, Milton José, Oliveira, Saulo Pomponet de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFBA
Texto Completo: http://www.repositorio.ufba.br/ri/handle/ri/3315
Resumo: The inversion of vertical electrical sounding (VES) is normally performed considering a stratified medium formed by homogeneous, isotropic and horizontal layers. The simplicity of this geophysical model makes the inversion simple and computationally fast, and together with the main characteristics of the electroresistivity method, it was greatly responsible to make VES one of the most popular geophysical method for groundwater exploration and engineering geophysics. However, even in a sedimentary basin where the geology is more conform, the assumption of horizontal and homogeneous layers is not necessarily valid, limiting the reliability of the inversion results. In this paper we present a fast and robust 2D resistivity modeling and inversion algorithm for the interpretation of sets of VES. We consider three inversion algorithms: the Gauss-Newton method of linearized inversion (LI), the genetic algorithm (GA), and a hybrid approach (GA-LI) that uses LI to improve the best model at the end of each step of the GA. The medium parametrization consists of the partition of the domain into fixed homogeneous rectangular blocks such that their resistivities are the only free parameters. The apparent resistivity is evaluated by an iterative scheme that is derived from a finite-difference discretization of the potential differential equation. We enhance the convergence rate of the scheme by adopting an incomplete Cholesky preconditioner. Numerical results using synthetic and real 2D apparent resistivity data formed by sets of VES for the Schlumberger configuration illustrate the performance of the hybrid GA-LI algorithm. The VES field data were acquired near Conceição do Coité, state of Bahia, Brazil. We compare the performance of the LI, GA and GA-LI algorithms.
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spelling Ferreira, Niraldo R.Porsani, Milton JoséOliveira, Saulo Pomponet deFerreira, Niraldo R.Porsani, Milton JoséOliveira, Saulo Pomponet de2011-10-13T18:31:06Z2011-10-13T18:31:06Z20030102-261Xhttp://www.repositorio.ufba.br/ri/handle/ri/3315v.21, n.3The inversion of vertical electrical sounding (VES) is normally performed considering a stratified medium formed by homogeneous, isotropic and horizontal layers. The simplicity of this geophysical model makes the inversion simple and computationally fast, and together with the main characteristics of the electroresistivity method, it was greatly responsible to make VES one of the most popular geophysical method for groundwater exploration and engineering geophysics. However, even in a sedimentary basin where the geology is more conform, the assumption of horizontal and homogeneous layers is not necessarily valid, limiting the reliability of the inversion results. In this paper we present a fast and robust 2D resistivity modeling and inversion algorithm for the interpretation of sets of VES. We consider three inversion algorithms: the Gauss-Newton method of linearized inversion (LI), the genetic algorithm (GA), and a hybrid approach (GA-LI) that uses LI to improve the best model at the end of each step of the GA. The medium parametrization consists of the partition of the domain into fixed homogeneous rectangular blocks such that their resistivities are the only free parameters. The apparent resistivity is evaluated by an iterative scheme that is derived from a finite-difference discretization of the potential differential equation. We enhance the convergence rate of the scheme by adopting an incomplete Cholesky preconditioner. Numerical results using synthetic and real 2D apparent resistivity data formed by sets of VES for the Schlumberger configuration illustrate the performance of the hybrid GA-LI algorithm. The VES field data were acquired near Conceição do Coité, state of Bahia, Brazil. We compare the performance of the LI, GA and GA-LI algorithms.Submitted by Santiago Fabio (fabio.ssantiago@hotmail.com) on 2011-10-13T18:31:06Z No. of bitstreams: 1 55555.pdf: 878136 bytes, checksum: 9687a521def08ade280c32b51afe7a01 (MD5)Made available in DSpace on 2011-10-13T18:31:06Z (GMT). No. of bitstreams: 1 55555.pdf: 878136 bytes, checksum: 9687a521def08ade280c32b51afe7a01 (MD5) Previous issue date: 2003São PauloRevista Brasileira de GeofísicaIncomplete Cholesky2D resistivity modelinggeophysical inversiongenetic algorithmslinearized inversionhybrid optimizationfatoração incompleta de Choleskymodelagem bidimensional de resistividadeinversão geofísicaalgoritmos genéticosinversão linearizadaotimização híbridaA hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical soundingRevista Brasileira de Geofísicainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional da UFBAinstname:Universidade Federal da Bahia (UFBA)instacron:UFBAinfo:eu-repo/semantics/openAccessORIGINAL55555.pdf55555.pdfapplication/pdf878136https://repositorio.ufba.br/bitstream/ri/3315/1/55555.pdf9687a521def08ade280c32b51afe7a01MD51LICENSElicense.txtlicense.txttext/plain1906https://repositorio.ufba.br/bitstream/ri/3315/2/license.txt4f0518d8da3870d13d2ef405777dee61MD52TEXT55555.pdf.txt55555.pdf.txtExtracted texttext/plain38258https://repositorio.ufba.br/bitstream/ri/3315/3/55555.pdf.txt67b74ceec480c8c518ec4a7390e7a1e9MD53ri/33152022-07-05 14:03:24.151oai:repositorio.ufba.br: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Repositório InstitucionalPUBhttp://192.188.11.11:8080/oai/requestopendoar:19322022-07-05T17:03:24Repositório Institucional da UFBA - Universidade Federal da Bahia (UFBA)false
dc.title.pt_BR.fl_str_mv A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
dc.title.alternative.pt_BR.fl_str_mv Revista Brasileira de Geofísica
title A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
spellingShingle A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
Ferreira, Niraldo R.
Incomplete Cholesky
2D resistivity modeling
geophysical inversion
genetic algorithms
linearized inversion
hybrid optimization
fatoração incompleta de Cholesky
modelagem bidimensional de resistividade
inversão geofísica
algoritmos genéticos
inversão linearizada
otimização híbrida
title_short A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
title_full A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
title_fullStr A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
title_full_unstemmed A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
title_sort A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
author Ferreira, Niraldo R.
author_facet Ferreira, Niraldo R.
Porsani, Milton José
Oliveira, Saulo Pomponet de
author_role author
author2 Porsani, Milton José
Oliveira, Saulo Pomponet de
author2_role author
author
dc.contributor.author.fl_str_mv Ferreira, Niraldo R.
Porsani, Milton José
Oliveira, Saulo Pomponet de
Ferreira, Niraldo R.
Porsani, Milton José
Oliveira, Saulo Pomponet de
dc.subject.por.fl_str_mv Incomplete Cholesky
2D resistivity modeling
geophysical inversion
genetic algorithms
linearized inversion
hybrid optimization
fatoração incompleta de Cholesky
modelagem bidimensional de resistividade
inversão geofísica
algoritmos genéticos
inversão linearizada
otimização híbrida
topic Incomplete Cholesky
2D resistivity modeling
geophysical inversion
genetic algorithms
linearized inversion
hybrid optimization
fatoração incompleta de Cholesky
modelagem bidimensional de resistividade
inversão geofísica
algoritmos genéticos
inversão linearizada
otimização híbrida
description The inversion of vertical electrical sounding (VES) is normally performed considering a stratified medium formed by homogeneous, isotropic and horizontal layers. The simplicity of this geophysical model makes the inversion simple and computationally fast, and together with the main characteristics of the electroresistivity method, it was greatly responsible to make VES one of the most popular geophysical method for groundwater exploration and engineering geophysics. However, even in a sedimentary basin where the geology is more conform, the assumption of horizontal and homogeneous layers is not necessarily valid, limiting the reliability of the inversion results. In this paper we present a fast and robust 2D resistivity modeling and inversion algorithm for the interpretation of sets of VES. We consider three inversion algorithms: the Gauss-Newton method of linearized inversion (LI), the genetic algorithm (GA), and a hybrid approach (GA-LI) that uses LI to improve the best model at the end of each step of the GA. The medium parametrization consists of the partition of the domain into fixed homogeneous rectangular blocks such that their resistivities are the only free parameters. The apparent resistivity is evaluated by an iterative scheme that is derived from a finite-difference discretization of the potential differential equation. We enhance the convergence rate of the scheme by adopting an incomplete Cholesky preconditioner. Numerical results using synthetic and real 2D apparent resistivity data formed by sets of VES for the Schlumberger configuration illustrate the performance of the hybrid GA-LI algorithm. The VES field data were acquired near Conceição do Coité, state of Bahia, Brazil. We compare the performance of the LI, GA and GA-LI algorithms.
publishDate 2003
dc.date.issued.fl_str_mv 2003
dc.date.accessioned.fl_str_mv 2011-10-13T18:31:06Z
dc.date.available.fl_str_mv 2011-10-13T18:31:06Z
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://www.repositorio.ufba.br/ri/handle/ri/3315
dc.identifier.issn.none.fl_str_mv 0102-261X
dc.identifier.number.pt_BR.fl_str_mv v.21, n.3
identifier_str_mv 0102-261X
v.21, n.3
url http://www.repositorio.ufba.br/ri/handle/ri/3315
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Revista Brasileira de Geofísica
publisher.none.fl_str_mv Revista Brasileira de Geofísica
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFBA
instname:Universidade Federal da Bahia (UFBA)
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reponame_str Repositório Institucional da UFBA
collection Repositório Institucional da UFBA
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