Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study
© 2017 The Author(s). Ambient-noise-based seismic monitoring of the near surface often has limited spatiotemporal resolutions because dense seismic arrays are rarely sufficiently affordable for such applications. In recent years, however, distributed acoustic sensing (DAS) techniques have emerged to...
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ftcdlib:qt7xq3n9zj 2023-05-15T17:57:49+02:00 Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study Dou, S Lindsey, N Wagner, AM Daley, TM Freifeld, B Robertson, M Peterson, J Ulrich, C Martin, ER Ajo-Franklin, JB 2017-12-01 application/pdf http://www.escholarship.org/uc/item/7xq3n9zj english eng eScholarship, University of California qt7xq3n9zj http://www.escholarship.org/uc/item/7xq3n9zj public Dou, S; Lindsey, N; Wagner, AM; Daley, TM; Freifeld, B; Robertson, M; et al.(2017). Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study. Scientific Reports, 7(1). doi:10.1038/s41598-017-11986-4. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/7xq3n9zj article 2017 ftcdlib https://doi.org/10.1038/s41598-017-11986-4 2018-11-02T23:53:38Z © 2017 The Author(s). Ambient-noise-based seismic monitoring of the near surface often has limited spatiotemporal resolutions because dense seismic arrays are rarely sufficiently affordable for such applications. In recent years, however, distributed acoustic sensing (DAS) techniques have emerged to transform telecommunication fiber-optic cables into dense seismic arrays that are cost effective. With DAS enabling both high sensor counts ("large N") and long-term operations ("large T"), time-lapse imaging of shear-wave velocity (VS) structures is now possible by combining ambient noise interferometry and multichannel analysis of surface waves (MASW). Here we report the first end-to-end study of time-lapse VSimaging that uses traffic noise continuously recorded on linear DAS arrays over a three-week period. Our results illustrate that for the top 20 meters the VSmodels that is well constrained by the data, we obtain time-lapse repeatability of about 2% in the model domain-A threshold that is low enough for observing subtle near-surface changes such as water content variations and permafrost alteration. This study demonstrates the efficacy of near-surface seismic monitoring using DAS-recorded ambient noise. Article in Journal/Newspaper permafrost University of California: eScholarship Scientific Reports 7 1 |
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University of California: eScholarship |
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English |
description |
© 2017 The Author(s). Ambient-noise-based seismic monitoring of the near surface often has limited spatiotemporal resolutions because dense seismic arrays are rarely sufficiently affordable for such applications. In recent years, however, distributed acoustic sensing (DAS) techniques have emerged to transform telecommunication fiber-optic cables into dense seismic arrays that are cost effective. With DAS enabling both high sensor counts ("large N") and long-term operations ("large T"), time-lapse imaging of shear-wave velocity (VS) structures is now possible by combining ambient noise interferometry and multichannel analysis of surface waves (MASW). Here we report the first end-to-end study of time-lapse VSimaging that uses traffic noise continuously recorded on linear DAS arrays over a three-week period. Our results illustrate that for the top 20 meters the VSmodels that is well constrained by the data, we obtain time-lapse repeatability of about 2% in the model domain-A threshold that is low enough for observing subtle near-surface changes such as water content variations and permafrost alteration. This study demonstrates the efficacy of near-surface seismic monitoring using DAS-recorded ambient noise. |
format |
Article in Journal/Newspaper |
author |
Dou, S Lindsey, N Wagner, AM Daley, TM Freifeld, B Robertson, M Peterson, J Ulrich, C Martin, ER Ajo-Franklin, JB |
spellingShingle |
Dou, S Lindsey, N Wagner, AM Daley, TM Freifeld, B Robertson, M Peterson, J Ulrich, C Martin, ER Ajo-Franklin, JB Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
author_facet |
Dou, S Lindsey, N Wagner, AM Daley, TM Freifeld, B Robertson, M Peterson, J Ulrich, C Martin, ER Ajo-Franklin, JB |
author_sort |
Dou, S |
title |
Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
title_short |
Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
title_full |
Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
title_fullStr |
Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
title_full_unstemmed |
Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study |
title_sort |
distributed acoustic sensing for seismic monitoring of the near surface: a traffic-noise interferometry case study |
publisher |
eScholarship, University of California |
publishDate |
2017 |
url |
http://www.escholarship.org/uc/item/7xq3n9zj |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Dou, S; Lindsey, N; Wagner, AM; Daley, TM; Freifeld, B; Robertson, M; et al.(2017). Distributed Acoustic Sensing for Seismic Monitoring of the Near Surface: A Traffic-Noise Interferometry Case Study. Scientific Reports, 7(1). doi:10.1038/s41598-017-11986-4. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/7xq3n9zj |
op_relation |
qt7xq3n9zj http://www.escholarship.org/uc/item/7xq3n9zj |
op_rights |
public |
op_doi |
https://doi.org/10.1038/s41598-017-11986-4 |
container_title |
Scientific Reports |
container_volume |
7 |
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1 |
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1766166329377685504 |