Microseismic event location using global optimization algorithms: An integrated and automated workflow

Autores
Lagos, Soledad Rocío; Velis, Danilo Rubén
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.
Facultad de Ciencias Astronómicas y Geofísicas
Materia
Astronomía
Microseismic monitoring
Optimization
Location
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/127875

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network_name_str SEDICI (UNLP)
spelling Microseismic event location using global optimization algorithms: An integrated and automated workflowLagos, Soledad RocíoVelis, Danilo RubénAstronomíaMicroseismic monitoringOptimizationLocationWe perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.Facultad de Ciencias Astronómicas y Geofísicas2018-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf18-24http://sedici.unlp.edu.ar/handle/10915/127875enginfo:eu-repo/semantics/altIdentifier/issn/0926-9851info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jappgeo.2017.12.004info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-10T12:33:39Zoai:sedici.unlp.edu.ar:10915/127875Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 12:33:39.916SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Microseismic event location using global optimization algorithms: An integrated and automated workflow
title Microseismic event location using global optimization algorithms: An integrated and automated workflow
spellingShingle Microseismic event location using global optimization algorithms: An integrated and automated workflow
Lagos, Soledad Rocío
Astronomía
Microseismic monitoring
Optimization
Location
title_short Microseismic event location using global optimization algorithms: An integrated and automated workflow
title_full Microseismic event location using global optimization algorithms: An integrated and automated workflow
title_fullStr Microseismic event location using global optimization algorithms: An integrated and automated workflow
title_full_unstemmed Microseismic event location using global optimization algorithms: An integrated and automated workflow
title_sort Microseismic event location using global optimization algorithms: An integrated and automated workflow
dc.creator.none.fl_str_mv Lagos, Soledad Rocío
Velis, Danilo Rubén
author Lagos, Soledad Rocío
author_facet Lagos, Soledad Rocío
Velis, Danilo Rubén
author_role author
author2 Velis, Danilo Rubén
author2_role author
dc.subject.none.fl_str_mv Astronomía
Microseismic monitoring
Optimization
Location
topic Astronomía
Microseismic monitoring
Optimization
Location
dc.description.none.fl_txt_mv We perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.
Facultad de Ciencias Astronómicas y Geofísicas
description We perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.
publishDate 2018
dc.date.none.fl_str_mv 2018-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/127875
url http://sedici.unlp.edu.ar/handle/10915/127875
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0926-9851
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jappgeo.2017.12.004
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
18-24
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instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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