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An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels
The velocity model is one of the main factors affecting the accuracy of microseismic event localization. This paper addresses the issue of the low accuracy of microseismic event localization in tunnels and, combined with active-source technology, proposes a “source–station” velocity model. The veloc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220534/ https://www.ncbi.nlm.nih.gov/pubmed/37430584 http://dx.doi.org/10.3390/s23104670 |
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author | Shen, Tong Wang, Songren Jiang, Xuan Peng, Guili Tuo, Xianguo |
author_facet | Shen, Tong Wang, Songren Jiang, Xuan Peng, Guili Tuo, Xianguo |
author_sort | Shen, Tong |
collection | PubMed |
description | The velocity model is one of the main factors affecting the accuracy of microseismic event localization. This paper addresses the issue of the low accuracy of microseismic event localization in tunnels and, combined with active-source technology, proposes a “source–station” velocity model. The velocity model assumes that the velocity from the source to each station is different, and it can greatly improve the accuracy of the time-difference-of-arrival algorithm. At the same time, for the case of multiple active sources, the MLKNN algorithm was selected as the velocity model selection method through comparative testing. The results of numerical simulation and laboratory tests in the tunnel showed that the average location accuracy of the “source–station” velocity model was improved compared with that of the isotropic velocity and sectional velocity models, with numerical simulation experiments improving accuracy by 79.82% and 57.05% (from 13.28 m and 6.24 m to 2.68 m), and laboratory tests in the tunnel improving accuracy by 89.26% and 76.33% (from 6.61 m and 3.00 m to 0.71 m). The results of the experiments showed that the method proposed in this paper can effectively improve the location accuracy of microseismic events in tunnels. |
format | Online Article Text |
id | pubmed-10220534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102205342023-05-28 An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels Shen, Tong Wang, Songren Jiang, Xuan Peng, Guili Tuo, Xianguo Sensors (Basel) Article The velocity model is one of the main factors affecting the accuracy of microseismic event localization. This paper addresses the issue of the low accuracy of microseismic event localization in tunnels and, combined with active-source technology, proposes a “source–station” velocity model. The velocity model assumes that the velocity from the source to each station is different, and it can greatly improve the accuracy of the time-difference-of-arrival algorithm. At the same time, for the case of multiple active sources, the MLKNN algorithm was selected as the velocity model selection method through comparative testing. The results of numerical simulation and laboratory tests in the tunnel showed that the average location accuracy of the “source–station” velocity model was improved compared with that of the isotropic velocity and sectional velocity models, with numerical simulation experiments improving accuracy by 79.82% and 57.05% (from 13.28 m and 6.24 m to 2.68 m), and laboratory tests in the tunnel improving accuracy by 89.26% and 76.33% (from 6.61 m and 3.00 m to 0.71 m). The results of the experiments showed that the method proposed in this paper can effectively improve the location accuracy of microseismic events in tunnels. MDPI 2023-05-11 /pmc/articles/PMC10220534/ /pubmed/37430584 http://dx.doi.org/10.3390/s23104670 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shen, Tong Wang, Songren Jiang, Xuan Peng, Guili Tuo, Xianguo An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title | An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title_full | An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title_fullStr | An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title_full_unstemmed | An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title_short | An Anisotropic Velocity Model for Microseismic Events Localization in Tunnels |
title_sort | anisotropic velocity model for microseismic events localization in tunnels |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220534/ https://www.ncbi.nlm.nih.gov/pubmed/37430584 http://dx.doi.org/10.3390/s23104670 |
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