Ocean bottom distributed acoustic sensing for oceanic seismicity detection and seismic ocean thermometry

dc.contributor.author Shen, Zhichao
dc.contributor.author Wu, Wenbo
dc.date.accessioned 2024-10-10T17:57:54Z
dc.date.available 2024-10-10T17:57:54Z
dc.date.issued 2024-03-07
dc.description Author Posting. © American Geophysical Union, 2024. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Shen, Z., & Wu, W. (2024). Ocean bottom distributed acoustic sensing for oceanic seismicity detection and seismic ocean thermometry. Journal of Geophysical Research: Solid Earth, 129(3), e2023JB027799, https://doi.org/10.1029/2023jb027799.
dc.description.abstract A T-wave is a seismo-acoustic wave that can travel a long distance in the ocean with little attenuation, making it valuable for monitoring remote tectonic activity and changes in ocean temperature using seismic ocean thermometry (SOT). However, current high-quality T-wave stations are sparsely distributed, limiting the detectability of oceanic seismicity and the spatial resolution of global SOT. The use of ocean bottom distributed acoustic sensing (OBDAS), through the conversion of telecommunication cables into dense seismic arrays, is a cost-effective and scalable means to complement existing seismic stations. Here, we systematically investigate the performance of OBDAS for oceanic seismicity detection and SOT using a 4-day Ocean Observatories Initiative community experiment offshore Oregon. We first present T-wave observations from distant and regional earthquakes and develop a curvelet denoising scheme to enhance T-wave signals on OBDAS. After denoising, we show that OBDAS can detect and locate more and smaller T-wave events than regional OBS network. During the 4-day experiment, we detect 92 oceanic earthquakes, most of which are missing from existing catalogs. Leveraging the sensor density and cable directionality, we demonstrate the feasibility of source azimuth estimation for regional Blanco earthquakes. We also evaluate the SOT performance of OBDAS using pseudo-repeating earthquake T-waves. Our results show that OBDAS can utilize repeating earthquakes as small as M3.5 for SOT, outperforming ocean bottom seismometers. However, ocean ambient natural and instrumental noise strongly affects the performance of OBDAS for oceanic seismicity detection and SOT, requiring further investigation.
dc.description.sponsorship This project is supported by the Woods Hole Oceanographic Institution Independent Research & Development Program and the National Science Foundation Grant OCE-2241663. This work is based on data provided by the Ocean Observatories Initiative (OOI), a major facility fully funded by the National Science Foundation under Cooperative Agreement No. 1743430, and the Woods Hole Oceanographic Institution OOI Program Office. We thank the high-performance computing resources at Woods Hole Oceanographic Institution made available for conducting this research. Z. S. also acknowledges the support of the Weston Howland Jr. Postdoctoral Scholarship.
dc.identifier.citation Shen, Z., & Wu, W. (2024). Ocean bottom distributed acoustic sensing for oceanic seismicity detection and seismic ocean thermometry. Journal of Geophysical Research: Solid Earth, 129(3), e2023JB027799.
dc.identifier.doi 10.1029/2023jb027799
dc.identifier.uri https://hdl.handle.net/1912/70752
dc.publisher American Geophysical Union
dc.relation.uri https://doi.org/10.1029/2023jb027799
dc.subject DAS
dc.subject T-wave
dc.subject Curvelet denoising
dc.subject Oceanic seismicity
dc.subject Seismic ocean thermometry
dc.title Ocean bottom distributed acoustic sensing for oceanic seismicity detection and seismic ocean thermometry
dc.type Article
dspace.entity.type Publication
relation.isAuthorOfPublication 161bf62b-5901-40b9-8b1b-773746767e88
relation.isAuthorOfPublication e3c6f093-9c22-426d-b7c0-854a98007cbc
relation.isAuthorOfPublication.latestForDiscovery 161bf62b-5901-40b9-8b1b-773746767e88
Files
Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
ShenZ_2024.pdf
Size:
5 MB
Format:
Adobe Portable Document Format
Description:
Thumbnail Image
Name:
ShenZ_2024supplementary.pdf
Size:
1.82 MB
Format:
Adobe Portable Document Format
Description: