A hybrid genetic-linear algorithm for 2D inversion of sets of vertical electrical sounding
Autor(a) principal: | |
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Data de Publicação: | 2003 |
Outros Autores: | , |
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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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 |
eu_rights_str_mv |
openAccess |
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) instacron:UFBA |
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Universidade Federal da Bahia (UFBA) |
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UFBA |
institution |
UFBA |
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Repositório Institucional da UFBA |
collection |
Repositório Institucional da UFBA |
bitstream.url.fl_str_mv |
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