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dc.contributor.author
Velis, Danilo Ruben
dc.contributor.author
Sabbione, Juan Ignacio
dc.contributor.author
Sacchi, Mauricio D.
dc.date.available
2018-07-31T21:08:56Z
dc.date.issued
2015-07
dc.identifier.citation
Velis, Danilo Ruben; Sabbione, Juan Ignacio; Sacchi, Mauricio D.; Fast and automatic microseismic phase-arrival detection and denoising by pattern recognition and reduced-rank filtering; Society of Exploration Geophysicists; Geophysics; 80; 6; 7-2015; WC25-WC38
dc.identifier.issn
0016-8033
dc.identifier.uri
http://hdl.handle.net/11336/53691
dc.description.abstract
We have developed a fast method that allowed us to automatically detect and denoise microseismic phase arrivals from 3C multichannel data. The method is a two-step process. First, the detection is carried out by means of a pattern recognition strategy that seeks plausible hyperbolic phase arrivals immersed in noisy 3C multichannel data. Then, the microseismic phase arrivals are denoised and reconstructed using a reduced-rank approximation of the singular value decomposition of the data along the detected phase arrivals in the context of a deflation procedure that took into account multiple arrivals and/or phases. For the detection, we have defined an objective function that measured the energy and coherence of a potential microseismic phase arrival along an apex-shifted hyperbolic search window. The objective function, which was maximized using very fast simulated annealing, was based on the energy of the average signal and depended on the source position, receivers geometry, and velocity. In practice, the detection process did not require any a priori velocity model, leading to a fast algorithm that can be used in real time, even when the underlying velocity model was not constant. The reduced-rank filtering coupled with a crosscorrelation-based synchronization strategy allowed us to extract the most representative waveform for all the individual traces. Tests using synthetic and field data have determined the reliability and effectiveness of the proposed method for the accurate detection and denoising of 3C multichannel microseismic events under noisy conditions. Two confidence indicators to assess the presence of an actual phase arrival and the reliability of the denoised individual wave arrivals were also developed.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Society of Exploration Geophysicists
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Microseismic
dc.subject
Automatic Event Detection
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Denoising
dc.subject.classification
Meteorología y Ciencias Atmosféricas
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Ciencias de la Tierra y relacionadas con el Medio Ambiente
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CIENCIAS NATURALES Y EXACTAS
dc.title
Fast and automatic microseismic phase-arrival detection and denoising by pattern recognition and reduced-rank filtering
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-07-31T17:21:10Z
dc.identifier.eissn
1942-2156
dc.journal.volume
80
dc.journal.number
6
dc.journal.pagination
WC25-WC38
dc.journal.pais
Estados Unidos
dc.conicet.avisoEditorial
© 2015 Society of Exploration Geophysicists. All rights reserved.
dc.description.fil
Fil: Velis, Danilo Ruben. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Sabbione, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Alberta; Canadá
dc.description.fil
Fil: Sacchi, Mauricio D.. University of Alberta; Canadá
dc.journal.title
Geophysics
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://library.seg.org/doi/abs/10.1190/geo2014-0561.1
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1190/GEO2014-0561.1
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