Monitoring Deep Sea Currents With Seafloor Distributed Acoustic Sensing

Abstract

Underwater fiber optic cables commonly traverse a variety of seafloor conditions, which leads to an uneven mechanical coupling between the cable and the ocean bottom. On rough seafloor bathymetry, some cable portions might be suspended and thus susceptible to vortex‐induced vibrations (VIV) driven by deep ocean currents. Here, we examine the potential of distributed acoustic sensing (DAS) to monitor deep‐sea currents along suspended sections of underwater telecom fiber optic cables undergoing VIV. Oscillations of a seafloor fiber optic cable located in southern France are recorded by DAS along cable sections presumably hanging. Their characteristic frequencies are lower than 1 Hz, at different ocean depths, and have an amplitude‐dependency consistent with the driving mechanism being VIV. Based on a theoretical proportionality between current speed and VIV frequencies, we derive ocean current speed time series at 2,390 m depth from the vortex shedding frequencies recorded by DAS. The DAS‐derived current speed time series is in agreement with recordings by a current meter located 3.75 km away from the hanging cable section (similar dominant period, high correlation after time shift). The DAS‐derived current speed time series displays features, such as characteristic periods and spectral decay, associated with the generation of internal gravity waves and weak oceanic turbulence in the Mediterranean Sea. The results demonstrate the potential of DAS along hanging segments of fiber optic cables to monitor a wide range of oceanography processes, at depths barely studied with current instrumentation.

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

“…This is indicative of near-inertial internal waves (IWs). As expected from the microtidal character of the Mediterranean sea, the spectral energy peaks are not well correlated with the main tidal components but instead to inertial oscillations, as previously observed in the region 72 – 75 .…”

Defect Recognition in Ballastless Track Structures Based on Distributed Acoustic Sensors

“…DASs not only have the advantages of anti-EMI, non-corrosiveness and no required power supply but can also detect and locate weak vibration signals along optical fibers. They have been widely applied in fields [7][8][9][10][11][12] such as oil pipeline security monitoring, perimeter security and rail transit. Collecting the vibration signals of trains and events along a line by using DAS technology combined with signal processing, deep learning and other ways to identify track defects has provided a reliable helper method that has an important application value for the safe and high-quality development of high-speed railways.…”