A simple method inspired by empirical mode decomposition for denoising seismic data

Autores
Gómez, Julián Luis; Velis, Danilo Ruben
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We developed a new and simple method for denoising seismic data, which was inspired by data-driven empirical mode decomposition (EMD) algorithms. The method, which can be applied either as a trace-by-trace process or in the f-x domain, replaces the use of the cubic interpolation scheme, which is required to calculate the mean envelopes of the signal and the residues, by window averaging. The resulting strategy is not viewed as an EMD per se, but a userfriendly version of EMD-based algorithms that permits us to attain, in a fraction of the time, the same level of noise cancellation as standard EMD implementations. Furthermore, the proposed method requires less user intervention and easily processes millions of traces in minutes rather than in hours as required by conventional EMD-based techniques on a standard PC. We compared the performance of the new method against standard EMD methods in terms of computational cost and signal preservation and applied them to denoise synthetic and field (microseismic and poststack) data containing random, erratic, and coherent noise. The corresponding f-x EMDs implementations for lateral continuity enhancement were analyzed and compared against the classical f-x deconvolution to test the method.
Fil: Gómez, Julián Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
signal processing
algorithm
noise
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:11336/54882
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling A simple method inspired by empirical mode decomposition for denoising seismic dataGómez, Julián LuisVelis, Danilo Rubensignal processingalgorithmnoisehttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We developed a new and simple method for denoising seismic data, which was inspired by data-driven empirical mode decomposition (EMD) algorithms. The method, which can be applied either as a trace-by-trace process or in the f-x domain, replaces the use of the cubic interpolation scheme, which is required to calculate the mean envelopes of the signal and the residues, by window averaging. The resulting strategy is not viewed as an EMD per se, but a userfriendly version of EMD-based algorithms that permits us to attain, in a fraction of the time, the same level of noise cancellation as standard EMD implementations. Furthermore, the proposed method requires less user intervention and easily processes millions of traces in minutes rather than in hours as required by conventional EMD-based techniques on a standard PC. We compared the performance of the new method against standard EMD methods in terms of computational cost and signal preservation and applied them to denoise synthetic and field (microseismic and poststack) data containing random, erratic, and coherent noise. The corresponding f-x EMDs implementations for lateral continuity enhancement were analyzed and compared against the classical f-x deconvolution to test the method.Fil: Gómez, Julián Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaSociety of Exploration Geophysicists2015-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/54882Gómez, Julián Luis; Velis, Danilo Ruben; A simple method inspired by empirical mode decomposition for denoising seismic data; Society of Exploration Geophysicists; Geophysics; 81; 6; 12-2015; V403-V4130016-8033CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1190/geo2015-0566.1info:eu-repo/semantics/altIdentifier/url/https://library.seg.org/doi/10.1190/geo2015-0566.1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:31:54Zoai:ri.conicet.gov.ar:11336/54882instacron: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 10:31:54.829CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A simple method inspired by empirical mode decomposition for denoising seismic data
title A simple method inspired by empirical mode decomposition for denoising seismic data
spellingShingle A simple method inspired by empirical mode decomposition for denoising seismic data
Gómez, Julián Luis
signal processing
algorithm
noise
title_short A simple method inspired by empirical mode decomposition for denoising seismic data
title_full A simple method inspired by empirical mode decomposition for denoising seismic data
title_fullStr A simple method inspired by empirical mode decomposition for denoising seismic data
title_full_unstemmed A simple method inspired by empirical mode decomposition for denoising seismic data
title_sort A simple method inspired by empirical mode decomposition for denoising seismic data
dc.creator.none.fl_str_mv Gómez, Julián Luis
Velis, Danilo Ruben
author Gómez, Julián Luis
author_facet Gómez, Julián Luis
Velis, Danilo Ruben
author_role author
author2 Velis, Danilo Ruben
author2_role author
dc.subject.none.fl_str_mv signal processing
algorithm
noise
topic signal processing
algorithm
noise
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 developed a new and simple method for denoising seismic data, which was inspired by data-driven empirical mode decomposition (EMD) algorithms. The method, which can be applied either as a trace-by-trace process or in the f-x domain, replaces the use of the cubic interpolation scheme, which is required to calculate the mean envelopes of the signal and the residues, by window averaging. The resulting strategy is not viewed as an EMD per se, but a userfriendly version of EMD-based algorithms that permits us to attain, in a fraction of the time, the same level of noise cancellation as standard EMD implementations. Furthermore, the proposed method requires less user intervention and easily processes millions of traces in minutes rather than in hours as required by conventional EMD-based techniques on a standard PC. We compared the performance of the new method against standard EMD methods in terms of computational cost and signal preservation and applied them to denoise synthetic and field (microseismic and poststack) data containing random, erratic, and coherent noise. The corresponding f-x EMDs implementations for lateral continuity enhancement were analyzed and compared against the classical f-x deconvolution to test the method.
Fil: Gómez, Julián Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description We developed a new and simple method for denoising seismic data, which was inspired by data-driven empirical mode decomposition (EMD) algorithms. The method, which can be applied either as a trace-by-trace process or in the f-x domain, replaces the use of the cubic interpolation scheme, which is required to calculate the mean envelopes of the signal and the residues, by window averaging. The resulting strategy is not viewed as an EMD per se, but a userfriendly version of EMD-based algorithms that permits us to attain, in a fraction of the time, the same level of noise cancellation as standard EMD implementations. Furthermore, the proposed method requires less user intervention and easily processes millions of traces in minutes rather than in hours as required by conventional EMD-based techniques on a standard PC. We compared the performance of the new method against standard EMD methods in terms of computational cost and signal preservation and applied them to denoise synthetic and field (microseismic and poststack) data containing random, erratic, and coherent noise. The corresponding f-x EMDs implementations for lateral continuity enhancement were analyzed and compared against the classical f-x deconvolution to test the method.
publishDate 2015
dc.date.none.fl_str_mv 2015-12
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/11336/54882
Gómez, Julián Luis; Velis, Danilo Ruben; A simple method inspired by empirical mode decomposition for denoising seismic data; Society of Exploration Geophysicists; Geophysics; 81; 6; 12-2015; V403-V413
0016-8033
CONICET Digital
CONICET
url http://hdl.handle.net/11336/54882
identifier_str_mv Gómez, Julián Luis; Velis, Danilo Ruben; A simple method inspired by empirical mode decomposition for denoising seismic data; Society of Exploration Geophysicists; Geophysics; 81; 6; 12-2015; V403-V413
0016-8033
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1190/geo2015-0566.1
info:eu-repo/semantics/altIdentifier/url/https://library.seg.org/doi/10.1190/geo2015-0566.1
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
dc.publisher.none.fl_str_mv Society of Exploration Geophysicists
publisher.none.fl_str_mv Society of Exploration Geophysicists
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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