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Published March 1, 2022 | Published
Journal Article Open

Seismic Monitoring with Distributed Acoustic Sensing from the Near-surface to the Deep Oceans

Abstract

Distributed acoustic sensing (DAS) delivers real-time observation ofphysical perturbations such as vibrations or strain variations in conventional optical fibers with high sensitivity. The high density of sensing points and large network footprint provided by a single DAS system, along with the availability of a vast optical fiber network already deployed both in land and in oceanic regions, contrast with the high deployment and maintenance cost of conventional instrumentation networks for seismology. This situation has triggered a rapid growth of DAS deployments for seismic monitoring in recent years. Photonic engineers and geophysicists have joined efforts to prove the value of optical fibers as distributed seismometers, which has resulted in a wide panoply of tests demonstrating diverse applicability across the geosciences. For example, DAS has been successfully applied recording local to teleseismic earthquakes, monitoring glacial icequakes, and observing oceanographic phenomena at the sea floor. Most of the realized tests have been performed using commercially available optical fiber interrogators based on phase-sensitive optical time-domain reflectometry. Among them, DAS based on chirped pulse distributed acoustic sensing have provided optimized performance in terms of both range and sensitivity, particularly at low frequencies. In this communication, we provide a comprehensive review of the current situation of DAS for seismology applications, focusing on near surface monitoring, where already deployed optical fibers can be repurposed as sensor networks.

Additional Information

© 2021 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. Manuscript received July 29, 2021; revised November 5, 2021; accepted November 6, 2021. Date of publication November 16, 2021; date of current version March 2, 2022. This work was supported in part by Comunidad de Madrid and FEDER Program under Grant SINFOTON2-CM: P2018/NMT-4326, in part by European Research Council under Grant OCEAN-DAS: ERC-2019-POC-875302, in part by Spanish Government under Projects RTI2018–097957-B-C31 and RTI2018–097957-B-C33, in part by the Spanish Ministry of Science and Innovation under Grant MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR Program, under Project PSI ref. PLEC2021-007875, and in part by the University of Alcalá under Project CCG20/IA-028. E.F.W. was supported by an NSF Graduate Research Fellowship. R.M., L.C., M.R.F.R. and H.F.M. acknowledge financial support from the EU's Horizon 2020 research and innovation program (MSCA grant no. 722509EU ITN-FINESSE) and the Spanish MICINN under contracts no. IJC2018–035684-I and IJCI-2017–33856, respectively. Z.Z. acknowledges support from the Moore Foundation and NSF under CAREER Award 1848166.

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023