The novel technique of distributed acoustic sensing (DAS) holds great potential for underwater seismology by transforming standard telecommunication cables, such as those currently traversing various regions of the world’s oceans, into dense arrays of seismo-acoustic sensors. To harness these measurements for seismic monitoring, the ability to record transient ground deformations is investigated by analyzing ambient noise, earthquakes, and their associated phase velocities, on DAS records from three dark fibers in the Mediterranean Sea. Recording quality varies dramatically along the fibers and is strongly correlated with the bathymetry and the apparent phase velocities of recorded waves. Apparent velocities are determined for several well-recorded earthquakes and used to convert DAS S-wave strain spectra to ground motion spectra. Excellent agreement is found between the spectra of nearby underwater and on-land seismometers and DAS converted spectra, when the latter are corrected for site effects. Apparent velocities greatly affect the ability to detect seismic deformations: for the same ground motions, slower waves induce higher strains and thus are more favorably detected than fast waves. The effect of apparent velocity on the ability to detect seismic phases, quantified by expected signal-to-noise ratios, is investigated by comparing signal amplitudes predicted by an earthquake model to recorded noise levels. DAS detection capabilities on underwater fibers are found to be similar to those of nearby broadband sensors, and superior to those of on-land fiber segments, owing to lower velocities at the ocean-bottom. The results demonstrate the great potential of underwater DAS for seismic monitoring and earthquake early warning.
Bibliographical noteFunding Information:
We thank the editor, Yehuda Ben-Zion, for his work, and Lucia Gualtieri and an anonymous reviewer for their very constructive remarks. This work and I.L. were supported by the SEAFOOD project, funded in part by grant ANR-17-CE04-0007 of the French Agence Nationale de la Recherche. Part of the project was also supported by Université Côte d’Azur IDEX program UCAJEDI ANR-15-IDEX-0001 and the Doeblin Federation (FR2800 CNRS). H.F.M. acknowledge financial support from the Spanish MICINN under contract no. IJCI-2017-33856.
We thank the editor, Yehuda Ben‐Zion, for his work, and Lucia Gualtieri and an anonymous reviewer for their very constructive remarks. This work and I.L. were supported by the SEAFOOD project, funded in part by grant ANR‐17‐CE04‐0007 of the French Agence Nationale de la Recherche. Part of the project was also supported by Université Côte d’Azur IDEX program UCA ANR‐15‐IDEX‐0001 and the Doeblin Federation (FR2800 CNRS). H.F.M. acknowledge financial support from the Spanish MICINN under contract no. IJCI‐2017‐33856. JEDI
DAS data were acquired using a first generation Febus A1 interrogator and an Aragon Photonics hDAS interrogator. Broadband seismometer data were acquired by Géoazur except for OBS records: data for the ASEAF, POSAN, and POSAS stations were downloaded from RESIF ( http://seismology.resif.fr/ , last accessed May 2020). The MEUST infrastructure is financed with the support of the CNRSIN2P3, the Region Sud, France (CPER the State (DRRT), and the Europe (FEDER). The fiber optic DAS earthquake recordings used to generate Figures 2–7 , S2 , and S3 , and the curves plotted in Figure 3 are available in the following OSF repository: https://osf.io/4bjph/ .
© 2021. American Geophysical Union. All Rights Reserved.
- ambient noise
- distributed acoustic sensing
- earthquake seismology
- ocean-bottom seismology
- signal to noise
- strain measurements