Surface Gravity Wave Interferometry and Ocean Current Monitoring With Ocean‐Bottom DAS

Abstract

The cross‐correlation of a diffuse or random wavefield at two points has been demonstrated to recover an empirical estimate of the Green's function under a wide variety of source conditions. Over the past two decades, the practical development of this principle, termed ambient noise interferometry, has revolutionized the fields of seismology and acoustics. Yet, because of the spatial sparsity of conventional water column and seafloor instrumentation, such array‐based processing approaches have not been widely utilized in oceanography. Ocean‐bottom distributed acoustic sensing (OBDAS) repurposes pre‐existing optical fibers laid in seafloor cables as dense arrays of broadband strain sensors, which observe both seismic waves and ocean waves. The thousands of sensors in an OBDAS array make ambient noise interferometry of ocean waves straightforward for the first time. Here, we demonstrate the application of ambient noise interferometry to surface gravity waves observed on an OBDAS array near the Strait of Gibraltar. We focus particularly on a 3‐km segment of the array on the continental shelf, containing 300 channels at 10‐m spacing. By cross‐correlating the raw strain records, we compute empirical ocean surface gravity wave Green's functions for each pair of stations. We first apply beamforming to measure the time‐averaged dispersion relation along the cable. Then, we exploit the non‐reciprocity of waves propagating in a flow to recover the depth‐averaged current velocity as a function of time using a waveform stretching method. The result is a spatially continuous matrix of current velocity measurements with resolution <100 m and <1 hr.

PubDAS: a PUBlic Distributed Acoustic Sensing datasets repository for geosciences

“…DAS recordings were also used for ambient noise interferometry (e.g., Zeng et al, 2017; E. R. , offering the possibility to retrieve repeatable signals (i.e., Rayleigh and Love waves) for near-surface characterization (E. Dou et al, 2017) and aquifer monitoring (Rodríguez Tribaldos & Ajo-Franklin, 2021). In addition, subsea telecommunication fibers have been used to monitor ocean dynamics (Lindsey et al, 2019;Sladen et al, 2019;Williams et al, 2019Williams et al, , 2022 but also to detect earthquakes (Lior et al, 2021; and acoustic phases (Rivet et al, 2021;Ugalde et al, 2022;, image the near-shore subsurface (Z. J. Spica, Nishida, et al, 2020;Z.…”

High resolution seafloor thermometry and internal wave monitoring using Distributed Acoustic Sensing

“…Among these, Distributed Acoustic Sensing (DAS) has gained wide interest thanks to its ability to monitor seismo-acoustic signals and dynamic strain with high sensitivity, making it suitable for a wide range of monitoring applications (e.g. Becker & Coleman, 2019;Lindsey et al, 2019;Sladen et al, 2019;Williams et al, 2019;Cheng et al, 2021;Rivet et al, 2021;Ugalde et al, 2021;Bouffaut et al, 2022;Guerin et al, 2022;Williams et al, 2022).…”

Monitoring Shelf Sea Dynamics with Ocean-Bottom Distributed Acoustic Sensing

“…This method was extended to ocean surface gravity waves (OSGWs) and infra-gravity waves recorded by buoys (Brown & Lu, 2016) and seafloor pressure gauges Neale et al, 2015;Tonegawa et al, 2018;Harmon et al, 2012). Recently, OBDAS has also been demonstrated to capture the pressure perturbations on the seafloor caused by the propagation of OSGWs, and has been used to monitor ocean near-surface currents (Williams et al, 2022).…”

“…The Distributed Acoustic Sensing (DAS) technology uses an interrogator unit (IU) to probe fiber-optic cables and measure the vibrations (i.e., strain or strain rate) of the Earth over tens of kilometers with a high spatio-temporal resolution (every ∼1-50 m at ∼100-1000 Hz depending on the experimental setting, Hartog, 2017). Over the past few years, DAS experiments have probed underwater telecommunication cables and recorded a variety of physical signals including near-coast microseisms (Guerin et al, 2022;Xiao et al, 2022;Spica et al, 2020;Viens, Perton, et al, 2022), local, regional and teleseismic earthquakes (Lior et al, 2021;Shinohara et al, 2019;Spica et al, 2022;Viens, Bonilla, et al, 2022), T-phases and other acoustic waves (Rivet et al, 2021;Ugalde et al, 2021;Spica et al, 2022), and ocean surface gravity waves (OSGWs) and deep-ocean water mixing processes (Mata Flores et al, 2022;Ide et al, 2021;Lindsey et al, 2019;Sladen et al, 2019;Williams et al, 2019Williams et al, , 2022. Most of these datasets are relatively short, spanning from a few days to a few weeks, and therefore do not capture the ocean's seasonal dynamics.…”