Treatment of geophysical data as a non-stationary process

Detalhes bibliográficos
Autor(a) principal: ROCHA, Marcus Pinto da Costa da
Data de Publicação: 2003
Outros Autores: LEITE, Lourenildo Williame Barbosa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFPA
Texto Completo: http://repositorio.ufpa.br/jspui/handle/2011/4535
Resumo: The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.
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spelling 2013-12-12T15:29:24Z2013-12-12T15:29:24Z2003ROCHA, Marcus P. C.; LEITE, Lourenildo W.B. Treatment of geophysical data as a non-stationary process. Computational & Applied Mathematics, São Carlos, v. 22, n. 2, p. 149-166, 2003. Disponível em: <http://www.scielo.br/pdf/cam/v22n2/01v22n2.pdf>. Acesso em: 21 mar. 2011. <http://dx.doi.org/10.1590/S0101-82052003000200001>.1807-0302http://repositorio.ufpa.br/jspui/handle/2011/4535The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.engProcesso estocásticoDeconvoluçãoEspaço de estadoFiltro de Kalman-BucyTreatment of geophysical data as a non-stationary processinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleROCHA, Marcus Pinto da Costa daLEITE, Lourenildo Williame Barbosainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFPAinstname:Universidade Federal do Pará (UFPA)instacron:UFPAORIGINALArtigo_TreatmentGeophysicalData.pdfArtigo_TreatmentGeophysicalData.pdfapplication/pdf158097http://repositorio.ufpa.br/oai/bitstream/2011/4535/1/Artigo_TreatmentGeophysicalData.pdf61830e9d76583ef2375431fe5baee90dMD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-852http://repositorio.ufpa.br/oai/bitstream/2011/4535/2/license_url3d480ae6c91e310daba2020f8787d6f9MD52license_textlicense_texttext/html; charset=utf-80http://repositorio.ufpa.br/oai/bitstream/2011/4535/3/license_textd41d8cd98f00b204e9800998ecf8427eMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-823898http://repositorio.ufpa.br/oai/bitstream/2011/4535/4/license_rdfe363e809996cf46ada20da1accfcd9c7MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81774http://repositorio.ufpa.br/oai/bitstream/2011/4535/5/license.txtf0aa1a71c97d9c3e771021efac6d65e7MD55TEXTArtigo_TreatmentGeophysicalData.pdf.txtArtigo_TreatmentGeophysicalData.pdf.txtExtracted texttext/plain29458http://repositorio.ufpa.br/oai/bitstream/2011/4535/6/Artigo_TreatmentGeophysicalData.pdf.txt6285378376960c1d62d990c35db8cc39MD562011/45352018-01-31 12:54:21.409oai:repositorio.ufpa.br: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Repositório InstitucionalPUBhttp://repositorio.ufpa.br/oai/requestriufpabc@ufpa.bropendoar:21232018-01-31T15:54:21Repositório Institucional da UFPA - Universidade Federal do Pará (UFPA)false
dc.title.pt_BR.fl_str_mv Treatment of geophysical data as a non-stationary process
title Treatment of geophysical data as a non-stationary process
spellingShingle Treatment of geophysical data as a non-stationary process
ROCHA, Marcus Pinto da Costa da
Processo estocástico
Deconvolução
Espaço de estado
Filtro de Kalman-Bucy
title_short Treatment of geophysical data as a non-stationary process
title_full Treatment of geophysical data as a non-stationary process
title_fullStr Treatment of geophysical data as a non-stationary process
title_full_unstemmed Treatment of geophysical data as a non-stationary process
title_sort Treatment of geophysical data as a non-stationary process
author ROCHA, Marcus Pinto da Costa da
author_facet ROCHA, Marcus Pinto da Costa da
LEITE, Lourenildo Williame Barbosa
author_role author
author2 LEITE, Lourenildo Williame Barbosa
author2_role author
dc.contributor.author.fl_str_mv ROCHA, Marcus Pinto da Costa da
LEITE, Lourenildo Williame Barbosa
dc.subject.por.fl_str_mv Processo estocástico
Deconvolução
Espaço de estado
Filtro de Kalman-Bucy
topic Processo estocástico
Deconvolução
Espaço de estado
Filtro de Kalman-Bucy
description The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.
publishDate 2003
dc.date.issued.fl_str_mv 2003
dc.date.accessioned.fl_str_mv 2013-12-12T15:29:24Z
dc.date.available.fl_str_mv 2013-12-12T15:29:24Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.citation.fl_str_mv ROCHA, Marcus P. C.; LEITE, Lourenildo W.B. Treatment of geophysical data as a non-stationary process. Computational & Applied Mathematics, São Carlos, v. 22, n. 2, p. 149-166, 2003. Disponível em: <http://www.scielo.br/pdf/cam/v22n2/01v22n2.pdf>. Acesso em: 21 mar. 2011. <http://dx.doi.org/10.1590/S0101-82052003000200001>.
dc.identifier.uri.fl_str_mv http://repositorio.ufpa.br/jspui/handle/2011/4535
dc.identifier.issn.none.fl_str_mv 1807-0302
identifier_str_mv ROCHA, Marcus P. C.; LEITE, Lourenildo W.B. Treatment of geophysical data as a non-stationary process. Computational & Applied Mathematics, São Carlos, v. 22, n. 2, p. 149-166, 2003. Disponível em: <http://www.scielo.br/pdf/cam/v22n2/01v22n2.pdf>. Acesso em: 21 mar. 2011. <http://dx.doi.org/10.1590/S0101-82052003000200001>.
1807-0302
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