Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm

Autores
Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio D.
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We present a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velocity and density images and the associated sparse reflectivity levels. The method uses the three-term Aki and Richards approximation to linearise the seismic inversion problem. To this end, we adopt a weighted mixed l2, 1-norm that promotes structured forms of sparsity, thus leading to blocky solutions in time. In addition, our algorithm incorporates a covariance or scale matrix to simultaneously constrain P- and S-wave velocities and density. This a priori information is obtained by nearby well-log data. We also include a term containing a low-frequency background model. The l2, 1 mixed norm leads to a convex objective function that can be minimised using proximal algorithms. In particular, we use the fast iterative shrinkage-thresholding algorithm. A key advantage of this algorithm is that it only requires matrix–vector multiplications and no direct matrix inversion. The latter makes our algorithm numerically stable, easy to apply, and economical in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularised solutions, is able to provide consistent blocky and/or sparse estimators of P- and S-wave velocities and density from a noisy and limited number of observations.
Fil: Perez, Daniel Omar. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Velis, Danilo Ruben. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sacchi, Mauricio D.. University of Alberta; Canadá
Materia
Inverse Problem
Parameter Estimation
Seismic
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:11336/56431

id CONICETDig_f7fdb9ecc94ba970421101b23fb337b2
oai_identifier_str oai:ri.conicet.gov.ar:11336/56431
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Three-term inversion of prestack seismic data using a weighted l2, 1 mixed normPerez, Daniel OmarVelis, Danilo RubenSacchi, Mauricio D.Inverse ProblemParameter EstimationSeismichttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We present a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velocity and density images and the associated sparse reflectivity levels. The method uses the three-term Aki and Richards approximation to linearise the seismic inversion problem. To this end, we adopt a weighted mixed l2, 1-norm that promotes structured forms of sparsity, thus leading to blocky solutions in time. In addition, our algorithm incorporates a covariance or scale matrix to simultaneously constrain P- and S-wave velocities and density. This a priori information is obtained by nearby well-log data. We also include a term containing a low-frequency background model. The l2, 1 mixed norm leads to a convex objective function that can be minimised using proximal algorithms. In particular, we use the fast iterative shrinkage-thresholding algorithm. A key advantage of this algorithm is that it only requires matrix–vector multiplications and no direct matrix inversion. The latter makes our algorithm numerically stable, easy to apply, and economical in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularised solutions, is able to provide consistent blocky and/or sparse estimators of P- and S-wave velocities and density from a noisy and limited number of observations.Fil: Perez, Daniel Omar. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Velis, Danilo Ruben. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sacchi, Mauricio D.. University of Alberta; CanadáWiley Blackwell Publishing, Inc2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/56431Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio D.; Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm; Wiley Blackwell Publishing, Inc; Geophysical Prospecting; 65; 6; 11-2017; 1477-14950016-8025CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2478.12500info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1111/1365-2478.12500info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:15:33Zoai:ri.conicet.gov.ar:11336/56431instacron: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 10:15:34.048CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
title Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
spellingShingle Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
Perez, Daniel Omar
Inverse Problem
Parameter Estimation
Seismic
title_short Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
title_full Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
title_fullStr Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
title_full_unstemmed Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
title_sort Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm
dc.creator.none.fl_str_mv Perez, Daniel Omar
Velis, Danilo Ruben
Sacchi, Mauricio D.
author Perez, Daniel Omar
author_facet Perez, Daniel Omar
Velis, Danilo Ruben
Sacchi, Mauricio D.
author_role author
author2 Velis, Danilo Ruben
Sacchi, Mauricio D.
author2_role author
author
dc.subject.none.fl_str_mv Inverse Problem
Parameter Estimation
Seismic
topic Inverse Problem
Parameter Estimation
Seismic
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 a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velocity and density images and the associated sparse reflectivity levels. The method uses the three-term Aki and Richards approximation to linearise the seismic inversion problem. To this end, we adopt a weighted mixed l2, 1-norm that promotes structured forms of sparsity, thus leading to blocky solutions in time. In addition, our algorithm incorporates a covariance or scale matrix to simultaneously constrain P- and S-wave velocities and density. This a priori information is obtained by nearby well-log data. We also include a term containing a low-frequency background model. The l2, 1 mixed norm leads to a convex objective function that can be minimised using proximal algorithms. In particular, we use the fast iterative shrinkage-thresholding algorithm. A key advantage of this algorithm is that it only requires matrix–vector multiplications and no direct matrix inversion. The latter makes our algorithm numerically stable, easy to apply, and economical in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularised solutions, is able to provide consistent blocky and/or sparse estimators of P- and S-wave velocities and density from a noisy and limited number of observations.
Fil: Perez, Daniel Omar. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Velis, Danilo Ruben. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas. Departamento de Geofísica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sacchi, Mauricio D.. University of Alberta; Canadá
description We present a new inversion method to estimate, from prestack seismic data, blocky P- and S-wave velocity and density images and the associated sparse reflectivity levels. The method uses the three-term Aki and Richards approximation to linearise the seismic inversion problem. To this end, we adopt a weighted mixed l2, 1-norm that promotes structured forms of sparsity, thus leading to blocky solutions in time. In addition, our algorithm incorporates a covariance or scale matrix to simultaneously constrain P- and S-wave velocities and density. This a priori information is obtained by nearby well-log data. We also include a term containing a low-frequency background model. The l2, 1 mixed norm leads to a convex objective function that can be minimised using proximal algorithms. In particular, we use the fast iterative shrinkage-thresholding algorithm. A key advantage of this algorithm is that it only requires matrix–vector multiplications and no direct matrix inversion. The latter makes our algorithm numerically stable, easy to apply, and economical in terms of computational cost. Tests on synthetic and field data show that the proposed method, contrarily to conventional l2- or l1-norm regularised solutions, is able to provide consistent blocky and/or sparse estimators of P- and S-wave velocities and density from a noisy and limited number of observations.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
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/11336/56431
Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio D.; Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm; Wiley Blackwell Publishing, Inc; Geophysical Prospecting; 65; 6; 11-2017; 1477-1495
0016-8025
CONICET Digital
CONICET
url http://hdl.handle.net/11336/56431
identifier_str_mv Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio D.; Three-term inversion of prestack seismic data using a weighted l2, 1 mixed norm; Wiley Blackwell Publishing, Inc; Geophysical Prospecting; 65; 6; 11-2017; 1477-1495
0016-8025
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2478.12500
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1111/1365-2478.12500
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
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
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
_version_ 1844614093054410752
score 13.070432