Enhancing offshore seismic hazard assessment with fibre‑optic DAS: probabilistic shear‑velocity imaging from ambient noise

High‑resolution submarine velocity models are essential for improving offshore seismic hazard assessment and for monitoring future carbon‑storage sites, yet these regions often lack the dense instrumentation required for robust imaging. We show that fibre‑optic distributed acoustic sensing (DAS) can help fill this observational gap by repurposing telecommunication infrastructure to characterize offshore Earth structure, enabling high‑density imaging where conventional seismic networks are sparse or difficult to deploy.

Using continuous strain recordings along a 30‑km fiber‑optic cable connecting the CASTOR offshore gas‑storage field (Gulf of Valencia, Spain) to the coast, we extract broadband empirical Green’s functions from ambient noise using wavelet phase cross‑correlation and time‑scale phase‑weighted stacking. A local slant-stack transform yields clear Scholte and Rayleigh wavefields along the marine and onshore sections of the cable. These signals enable the construction of a probabilistic 2‑D shear‑wave velocity model, obtained through pointwise depth inversions using Markov chain Monte Carlo methods, providing uncertainty estimates that are particularly valuable for hazard‑related applications.

The resulting model resolves the shallow marine sedimentary basin, the Amposta Central Fault, and the transition to basement at depths exceeding 1 km. This study highlights the suitability of DAS for imaging low‑velocity offshore basins through continuous, meter-scale sampling along existing telecommunication infrastructure, offering a cost‑effective complement to traditional ocean‑bottom deployments. Our results underscore the potential of fibre‑optic sensing to enhance offshore seismic hazard characterization and to support high-resolution monitoring strategies for subsurface energy and carbon‑storage infrastructures.