Using passive distributed acoustic sensing data for ocean surface wave detection and subsurface imaging in shallow water

In recent years, the emerging technology of Distributed Acoustic Sensing (DAS), measuring the strain in an optic fiber (OF) caused by acoustic waves, has been used in land and water for monitoring and imaging of moving vehicles (trains, ships), stationary installations (pipelines), physical phenomena (earthquakes), marine mammals, oil fields, etc. DAS systems have an advantage over traditional measuring systems since they can provide a densely sampled array along the OF and exploit the features of wide-band signals, including low frequency range. In this study, the Tampnet DAS dataset released from “The Global DAS Month of February 2023” is used on the purpose of studying its efficiency for the retrieval of critical parameters of the marine environment. The dataset is not entirely continuous in time but contains patches of continuous data. A patch of two-hour continuous passive strain data is analyzed. The passive data are dominated by periodic shoaling waves and their interaction with the seabed, which generates primary and secondary microseims (PMs and SMs). The PMs and SMs are observed and separated by frequency-wavenumber decomposition, which demonstrates the excellent low-frequency performance of the DAS system. The opposing wind-wave trains mix nonlinearly and produce Scholte waves at near-acoustic speeds. Passive seismic interferometry (PSI) is performed on the two-hour passive strain data to obtain the Greens’ function which contains dispersive Scholte wave. The shear-wave speeds of the upper sediments are estimated by a non-linear geoacoustic inversion algorithm using the dispersion property of the Scholte wave.