Simple and fast gradient-based impedance inversion using total variation regularization

Autores
Perez, Daniel Omar; Velis, Danilo Ruben
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from poststack seismic data. We regularize the resulting inverse problem, which is inherently ill-posed and non-unique, by means of the total variation semi-norm (TV). This allows us promote stable and blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. The use of the TV leads to a convex objective function easily minimized using a gradient-based algorithm that requires, in contrast to other AI inversion methods based on TV regularization, simple matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularized solutions, is able to provide blocky AI images that preserve the subsurface layered structure with good lateral continuity from noisy observations.
Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. YPF - Tecnología; Argentina
Fil: Velis, Danilo Ruben. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Materia
Total Variation
Acoustic Impedance
Inversion
Seismic
Poststack
Blocky
FISTA
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/84630
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/84630
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Simple and fast gradient-based impedance inversion using total variation regularizationPerez, Daniel OmarVelis, Danilo RubenTotal VariationAcoustic ImpedanceInversionSeismicPoststackBlockyFISTAhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from poststack seismic data. We regularize the resulting inverse problem, which is inherently ill-posed and non-unique, by means of the total variation semi-norm (TV). This allows us promote stable and blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. The use of the TV leads to a convex objective function easily minimized using a gradient-based algorithm that requires, in contrast to other AI inversion methods based on TV regularization, simple matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularized solutions, is able to provide blocky AI images that preserve the subsurface layered structure with good lateral continuity from noisy observations.Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. YPF - Tecnología; ArgentinaFil: Velis, Danilo Ruben. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaGeophysical Press2018-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/84630Perez, Daniel Omar; Velis, Danilo Ruben; Simple and fast gradient-based impedance inversion using total variation regularization; Geophysical Press; Journal of Seismic Exploration; 27; 5; 10-2018; 473-4860963-0651CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.geophysical-press.com/online/online.htminfo:eu-repo/semantics/altIdentifier/url/http://www.geophysical-press.com/online/VOL27-5-Art4.pdfinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:27:54Zoai:ri.conicet.gov.ar:11336/84630instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:27:54.865CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Simple and fast gradient-based impedance inversion using total variation regularization
title Simple and fast gradient-based impedance inversion using total variation regularization
spellingShingle Simple and fast gradient-based impedance inversion using total variation regularization
Perez, Daniel Omar
Total Variation
Acoustic Impedance
Inversion
Seismic
Poststack
Blocky
FISTA
title_short Simple and fast gradient-based impedance inversion using total variation regularization
title_full Simple and fast gradient-based impedance inversion using total variation regularization
title_fullStr Simple and fast gradient-based impedance inversion using total variation regularization
title_full_unstemmed Simple and fast gradient-based impedance inversion using total variation regularization
title_sort Simple and fast gradient-based impedance inversion using total variation regularization
dc.creator.none.fl_str_mv Perez, Daniel Omar
Velis, Danilo Ruben
author Perez, Daniel Omar
author_facet Perez, Daniel Omar
Velis, Danilo Ruben
author_role author
author2 Velis, Danilo Ruben
author2_role author
dc.subject.none.fl_str_mv Total Variation
Acoustic Impedance
Inversion
Seismic
Poststack
Blocky
FISTA
topic Total Variation
Acoustic Impedance
Inversion
Seismic
Poststack
Blocky
FISTA
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from poststack seismic data. We regularize the resulting inverse problem, which is inherently ill-posed and non-unique, by means of the total variation semi-norm (TV). This allows us promote stable and blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. The use of the TV leads to a convex objective function easily minimized using a gradient-based algorithm that requires, in contrast to other AI inversion methods based on TV regularization, simple matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularized solutions, is able to provide blocky AI images that preserve the subsurface layered structure with good lateral continuity from noisy observations.
Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. YPF - Tecnología; Argentina
Fil: Velis, Danilo Ruben. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
description We present an algorithm to estimate blocky images of the subsurface acoustic impedance (AI) from poststack seismic data. We regularize the resulting inverse problem, which is inherently ill-posed and non-unique, by means of the total variation semi-norm (TV). This allows us promote stable and blocky solutions which are, by virtue of the capability of TV to handle edges properly, adequate to model layered earth models with sharp contrasts. The use of the TV leads to a convex objective function easily minimized using a gradient-based algorithm that requires, in contrast to other AI inversion methods based on TV regularization, simple matrix-vector multiplications and no direct matrix inversion. The latter makes the algorithm numerically stable, easy to apply, and economic in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularized solutions, is able to provide blocky AI images that preserve the subsurface layered structure with good lateral continuity from noisy observations.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/84630
Perez, Daniel Omar; Velis, Danilo Ruben; Simple and fast gradient-based impedance inversion using total variation regularization; Geophysical Press; Journal of Seismic Exploration; 27; 5; 10-2018; 473-486
0963-0651
CONICET Digital
CONICET
url http://hdl.handle.net/11336/84630
identifier_str_mv Perez, Daniel Omar; Velis, Danilo Ruben; Simple and fast gradient-based impedance inversion using total variation regularization; Geophysical Press; Journal of Seismic Exploration; 27; 5; 10-2018; 473-486
0963-0651
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.geophysical-press.com/online/online.htm
info:eu-repo/semantics/altIdentifier/url/http://www.geophysical-press.com/online/VOL27-5-Art4.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Geophysical Press
publisher.none.fl_str_mv Geophysical Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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