Distributed Acoustic Sensing for Seismic Monitoring of The Near Surface: A Traffic-Noise Interferometry Case Study
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 telecommuni...
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ftcdlib:oai:escholarship.org:ark:/13030/qt7xq3n9zj 2024-01-07T09:45:57+01:00 Distributed Acoustic Sensing for Seismic Monitoring of The Near Surface: A Traffic-Noise Interferometry Case Study Dou, Shan Lindsey, Nate Wagner, Anna M Daley, Thomas M Freifeld, Barry Robertson, Michelle Peterson, John Ulrich, Craig Martin, Eileen R Ajo-Franklin, Jonathan B 11620 2017-01-01 application/pdf https://escholarship.org/uc/item/7xq3n9zj unknown eScholarship, University of California qt7xq3n9zj https://escholarship.org/uc/item/7xq3n9zj public Scientific Reports, vol 7, iss 1 Earth Sciences Engineering Geophysics article 2017 ftcdlib 2023-12-11T19:07:37Z 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 (V S ) 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 V S imaging 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 V S models 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 |
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University of California: eScholarship |
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topic |
Earth Sciences Engineering Geophysics |
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Earth Sciences Engineering Geophysics Dou, Shan Lindsey, Nate Wagner, Anna M Daley, Thomas M Freifeld, Barry Robertson, Michelle Peterson, John Ulrich, Craig Martin, Eileen R Ajo-Franklin, Jonathan B Distributed Acoustic Sensing for Seismic Monitoring of The Near Surface: A Traffic-Noise Interferometry Case Study |
topic_facet |
Earth Sciences Engineering Geophysics |
description |
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 (V S ) 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 V S imaging 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 V S models 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, Shan Lindsey, Nate Wagner, Anna M Daley, Thomas M Freifeld, Barry Robertson, Michelle Peterson, John Ulrich, Craig Martin, Eileen R Ajo-Franklin, Jonathan B |
author_facet |
Dou, Shan Lindsey, Nate Wagner, Anna M Daley, Thomas M Freifeld, Barry Robertson, Michelle Peterson, John Ulrich, Craig Martin, Eileen R Ajo-Franklin, Jonathan B |
author_sort |
Dou, Shan |
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 |
https://escholarship.org/uc/item/7xq3n9zj |
op_coverage |
11620 |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Scientific Reports, vol 7, iss 1 |
op_relation |
qt7xq3n9zj https://escholarship.org/uc/item/7xq3n9zj |
op_rights |
public |
_version_ |
1787427617610137600 |