Radon transform-based microseismic event detection and signal-to-noise ratio enhancement

We present an adaptive filtering method to denoise downhole microseismic data. The methodology uses the apex-shifted parabolic Radon transform. The algorithm is implemented in two steps. In the first step we apply the apex-shifted parabolic Radon transform to the normalized root mean square envelope...

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Detalles Bibliográficos
Autores: Sabbione, Juan Ignacio, Sacchi, Mauricio D., Velis, Danilo Ruben
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/45978
Acceso en línea:http://hdl.handle.net/11336/45978
Access Level:acceso abierto
Palabra clave:Microseismic
Denosing
Adaptive Filtering
Radon Transform
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
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network_acronym_str AR
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repository_id_str
spelling Radon transform-based microseismic event detection and signal-to-noise ratio enhancementSabbione, Juan IgnacioSacchi, Mauricio D.Velis, Danilo RubenMicroseismicDenosingAdaptive FilteringRadon Transformhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We present an adaptive filtering method to denoise downhole microseismic data. The methodology uses the apex-shifted parabolic Radon transform. The algorithm is implemented in two steps. In the first step we apply the apex-shifted parabolic Radon transform to the normalized root mean square envelope of the microseismic data to detect the presence of an event. The Radon coefficients are efficiently calculated by restricting the integration paths of the Radon operator. In a second stage, a new (preconditioned) Radon transform is applied to individual components to enhance the recorded signal. The denoising is posed as an inverse problem preconditioned by the Radon coefficients obtained in the previous step. The algorithm was tested with synthetic and field datasets that were recorded with a vertical array of receivers. The method performs rapidly due to the parabolic approximation making it suitable for real-time monitoring. The P? and S?wave direct arrivals are properly denoised for high to moderate signal-to-noise ratio records.Fil: Sabbione, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Sacchi, Mauricio D.. University of Alberta; CanadáFil: Velis, Danilo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaElsevier Science2015-02info: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/11336/45978Sabbione, Juan Ignacio; Sacchi, Mauricio D.; Velis, Danilo Ruben; Radon transform-based microseismic event detection and signal-to-noise ratio enhancement; Elsevier Science; Journal Of Applied Geophysics; 113; 2-2015; 51-630926-9851CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jappgeo.2014.12.008info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0926985114003619info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2024-05-08T13:57:18Zoai:ri.conicet.gov.ar:11336/45978instacron: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:34982024-05-08 13:57:18.622CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
title Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
spellingShingle Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
Sabbione, Juan Ignacio
Microseismic
Denosing
Adaptive Filtering
Radon Transform
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
title_short Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
title_full Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
title_fullStr Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
title_full_unstemmed Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
title_sort Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
dc.creator.none.fl_str_mv Sabbione, Juan Ignacio
Sacchi, Mauricio D.
Velis, Danilo Ruben
author Sabbione, Juan Ignacio
author_facet Sabbione, Juan Ignacio
Sacchi, Mauricio D.
Velis, Danilo Ruben
author_role author
author2 Sacchi, Mauricio D.
Velis, Danilo Ruben
author2_role author
author
dc.subject.none.fl_str_mv Microseismic
Denosing
Adaptive Filtering
Radon Transform
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
topic Microseismic
Denosing
Adaptive Filtering
Radon Transform
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
description We present an adaptive filtering method to denoise downhole microseismic data. The methodology uses the apex-shifted parabolic Radon transform. The algorithm is implemented in two steps. In the first step we apply the apex-shifted parabolic Radon transform to the normalized root mean square envelope of the microseismic data to detect the presence of an event. The Radon coefficients are efficiently calculated by restricting the integration paths of the Radon operator. In a second stage, a new (preconditioned) Radon transform is applied to individual components to enhance the recorded signal. The denoising is posed as an inverse problem preconditioned by the Radon coefficients obtained in the previous step. The algorithm was tested with synthetic and field datasets that were recorded with a vertical array of receivers. The method performs rapidly due to the parabolic approximation making it suitable for real-time monitoring. The P? and S?wave direct arrivals are properly denoised for high to moderate signal-to-noise ratio records.
publishDate 2015
dc.date.none.fl_str_mv 2015-02
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/11336/45978
Sabbione, Juan Ignacio; Sacchi, Mauricio D.; Velis, Danilo Ruben; Radon transform-based microseismic event detection and signal-to-noise ratio enhancement; Elsevier Science; Journal Of Applied Geophysics; 113; 2-2015; 51-63
0926-9851
CONICET Digital
CONICET
url http://hdl.handle.net/11336/45978
identifier_str_mv Sabbione, Juan Ignacio; Sacchi, Mauricio D.; Velis, Danilo Ruben; Radon transform-based microseismic event detection and signal-to-noise ratio enhancement; Elsevier Science; Journal Of Applied Geophysics; 113; 2-2015; 51-63
0926-9851
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jappgeo.2014.12.008
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0926985114003619
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 Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
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 15.811543

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