Inversion of prestack seismic data using FISTA

Autores
Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio Dino
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work we present a new inversion method to obtain AVA high-resolution attributes from prestack seismic data. The method aims to find a series of sparse reflectors that, when convolved with the source wavelet, fit the observed data. To perform the inversion, we propose the use of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. The advantage of FISTA over other methods is that no inversion over any matrix is needed, making it numerically stable, easy to apply, economic in computational terms, and adequate for solving large-scale problems even with dense matrix data. Results on synthetic and field data show that the proposed method is capable to provide high-resolution AVA attributes that honor the observed data under noisy conditions, making it an interesting alternative to other known methods.
Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; Argentina
Fil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; Argentina
Fil: Sacchi, Mauricio Dino. University Of Alberta. Faculty Of Sciences; Canadá
Materia
Prestack
AVO/AVA
Inversion
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:11336/215645

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spelling Inversion of prestack seismic data using FISTAPerez, Daniel OmarVelis, Danilo RubenSacchi, Mauricio DinoPrestackAVO/AVAInversionFISTAhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1In this work we present a new inversion method to obtain AVA high-resolution attributes from prestack seismic data. The method aims to find a series of sparse reflectors that, when convolved with the source wavelet, fit the observed data. To perform the inversion, we propose the use of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. The advantage of FISTA over other methods is that no inversion over any matrix is needed, making it numerically stable, easy to apply, economic in computational terms, and adequate for solving large-scale problems even with dense matrix data. Results on synthetic and field data show that the proposed method is capable to provide high-resolution AVA attributes that honor the observed data under noisy conditions, making it an interesting alternative to other known methods.Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Sacchi, Mauricio Dino. University Of Alberta. Faculty Of Sciences; CanadáAsociación Argentina de Mecánica Computacional2012-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/215645Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio Dino; Inversion of prestack seismic data using FISTA; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; 33; 10-2012; 3255-32631666-6070CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://amcaonline.org.ar/ojs/index.php/mc/article/download/4258/4184info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:49:56Zoai:ri.conicet.gov.ar:11336/215645instacron: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:34982025-09-03 09:49:56.714CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Inversion of prestack seismic data using FISTA
title Inversion of prestack seismic data using FISTA
spellingShingle Inversion of prestack seismic data using FISTA
Perez, Daniel Omar
Prestack
AVO/AVA
Inversion
FISTA
title_short Inversion of prestack seismic data using FISTA
title_full Inversion of prestack seismic data using FISTA
title_fullStr Inversion of prestack seismic data using FISTA
title_full_unstemmed Inversion of prestack seismic data using FISTA
title_sort Inversion of prestack seismic data using FISTA
dc.creator.none.fl_str_mv Perez, Daniel Omar
Velis, Danilo Ruben
Sacchi, Mauricio Dino
author Perez, Daniel Omar
author_facet Perez, Daniel Omar
Velis, Danilo Ruben
Sacchi, Mauricio Dino
author_role author
author2 Velis, Danilo Ruben
Sacchi, Mauricio Dino
author2_role author
author
dc.subject.none.fl_str_mv Prestack
AVO/AVA
Inversion
FISTA
topic Prestack
AVO/AVA
Inversion
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 In this work we present a new inversion method to obtain AVA high-resolution attributes from prestack seismic data. The method aims to find a series of sparse reflectors that, when convolved with the source wavelet, fit the observed data. To perform the inversion, we propose the use of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. The advantage of FISTA over other methods is that no inversion over any matrix is needed, making it numerically stable, easy to apply, economic in computational terms, and adequate for solving large-scale problems even with dense matrix data. Results on synthetic and field data show that the proposed method is capable to provide high-resolution AVA attributes that honor the observed data under noisy conditions, making it an interesting alternative to other known methods.
Fil: Perez, Daniel Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; Argentina
Fil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; Argentina
Fil: Sacchi, Mauricio Dino. University Of Alberta. Faculty Of Sciences; Canadá
description In this work we present a new inversion method to obtain AVA high-resolution attributes from prestack seismic data. The method aims to find a series of sparse reflectors that, when convolved with the source wavelet, fit the observed data. To perform the inversion, we propose the use of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). FISTA, which can be viewed as an extension of the classical gradient algorithm, provides sparse solutions minimizing both the misfit between the modeled and the observed data, and the l1-norm of the solution. The advantage of FISTA over other methods is that no inversion over any matrix is needed, making it numerically stable, easy to apply, economic in computational terms, and adequate for solving large-scale problems even with dense matrix data. Results on synthetic and field data show that the proposed method is capable to provide high-resolution AVA attributes that honor the observed data under noisy conditions, making it an interesting alternative to other known methods.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
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/11336/215645
Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio Dino; Inversion of prestack seismic data using FISTA; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; 33; 10-2012; 3255-3263
1666-6070
CONICET Digital
CONICET
url http://hdl.handle.net/11336/215645
identifier_str_mv Perez, Daniel Omar; Velis, Danilo Ruben; Sacchi, Mauricio Dino; Inversion of prestack seismic data using FISTA; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; 33; 10-2012; 3255-3263
1666-6070
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://amcaonline.org.ar/ojs/index.php/mc/article/download/4258/4184
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 Asociación Argentina de Mecánica Computacional
publisher.none.fl_str_mv Asociación Argentina de Mecánica Computacional
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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