Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps
We present a new automated earthquake detection and location method based on beamforming (or back projection) and template matching and apply it to study the seismicity of the Southwestern Alps. We use beamforming with prior knowledge of the 3-D variations of seismic velocities as a first detection...
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American Geophysical Union (AGU)
2020
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Online Access: | https://hdl.handle.net/1721.1/126022 |
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author | Beaucé, Eric Frank, William B. Paul, Anne Campillo, Michel Campillo, Michel Henri Paul Hilst, Robert D. van der Hilst, Robert D |
author2 | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences |
author_facet | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Beaucé, Eric Frank, William B. Paul, Anne Campillo, Michel Campillo, Michel Henri Paul Hilst, Robert D. van der Hilst, Robert D |
author_sort | Beaucé, Eric |
collection | MIT |
description | We present a new automated earthquake detection and location method based on beamforming (or back projection) and template matching and apply it to study the seismicity of the Southwestern Alps. We use beamforming with prior knowledge of the 3-D variations of seismic velocities as a first detection run to search for earthquakes that are used as templates in a subsequent matched-filter search. Template matching allows us to detect low signal-to-noise ratio events and thus to obtain a high spatiotemporal resolution of the seismicity in the Southwestern Alps. We describe how we address the problem of false positives in energy-based earthquake detection with supervised machine learning and how to best leverage template matching to iteratively refine the templates and the detection. We detected 18,754 earthquakes over 1 year (our catalog is available online) and observed temporal clustering of the earthquake occurrence in several regions. This statistical study of the collective behavior of earthquakes provides insights into the mechanisms of earthquake occurrence. Based on our observations, we infer the mechanisms responsible for the seismic activity in three regions of interest: the Ubaye valley, the Briançonnais, and the Dora Maira massif. Our conclusions point to the importance of fault interactions to explain the earthquake occurrence in the Briançonnais and the Dora Maira massif, whereas fluids seem to be the major driving mechanism in the Ubaye valley. |
first_indexed | 2024-09-23T13:54:57Z |
format | Article |
id | mit-1721.1/126022 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T13:54:57Z |
publishDate | 2020 |
publisher | American Geophysical Union (AGU) |
record_format | dspace |
spelling | mit-1721.1/1260222022-09-28T17:02:48Z Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps Beaucé, Eric Frank, William B. Paul, Anne Campillo, Michel Campillo, Michel Henri Paul Hilst, Robert D. van der Hilst, Robert D Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences We present a new automated earthquake detection and location method based on beamforming (or back projection) and template matching and apply it to study the seismicity of the Southwestern Alps. We use beamforming with prior knowledge of the 3-D variations of seismic velocities as a first detection run to search for earthquakes that are used as templates in a subsequent matched-filter search. Template matching allows us to detect low signal-to-noise ratio events and thus to obtain a high spatiotemporal resolution of the seismicity in the Southwestern Alps. We describe how we address the problem of false positives in energy-based earthquake detection with supervised machine learning and how to best leverage template matching to iteratively refine the templates and the detection. We detected 18,754 earthquakes over 1 year (our catalog is available online) and observed temporal clustering of the earthquake occurrence in several regions. This statistical study of the collective behavior of earthquakes provides insights into the mechanisms of earthquake occurrence. Based on our observations, we infer the mechanisms responsible for the seismic activity in three regions of interest: the Ubaye valley, the Briançonnais, and the Dora Maira massif. Our conclusions point to the importance of fault interactions to explain the earthquake occurrence in the Briançonnais and the Dora Maira massif, whereas fluids seem to be the major driving mechanism in the Ubaye valley. 2020-06-30T13:31:11Z 2020-06-30T13:31:11Z 2019-11 2019-10 2020-05-07T17:57:24Z Article http://purl.org/eprint/type/JournalArticle 2169-9313 2169-9356 https://hdl.handle.net/1721.1/126022 Beaucé, Eric et al. "Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps." Journal of Geophysical Research: Solid Earth 124, 11 (November 2011): 11531-11548 © 2019 American Geophysical Union en http://dx.doi.org/10.1029/2019jb018110 Journal of Geophysical Research: Solid Earth Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf American Geophysical Union (AGU) Other repository |
spellingShingle | Beaucé, Eric Frank, William B. Paul, Anne Campillo, Michel Campillo, Michel Henri Paul Hilst, Robert D. van der Hilst, Robert D Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title | Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title_full | Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title_fullStr | Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title_full_unstemmed | Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title_short | Systematic Detection of Clustered Seismicity Beneath the Southwestern Alps |
title_sort | systematic detection of clustered seismicity beneath the southwestern alps |
url | https://hdl.handle.net/1721.1/126022 |
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