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Seismic interferometry applied to Distributed Acoustic Sensing (DAS) arrays is an increasingly common approach for subsurface investigations. In this study, we show that analysis of urban seismic noise acquired on a linear underwater DAS array can be used to track depth-dependent seismic velocity variations caused by groundwater level changes in an alluvial aquifer. We apply our methodology to the Crpieux-Charmy wellfield, a strategic site for the water supply of the Lyon metropolitan area in France. We analyze 4 weeks of ambient noise recorded during a water infiltration experiment along a 200m DAS cable placed at the bottom of an infiltration basin. Using ambient noise interferometry, we derived time-lapse phase velocity variations (dc(f)/c(f)) of Rayleigh waves and inverted them for depth-dependent shear wave velocity variations (dVs(z)/Vs(z)) in the first 50 m of the subsurface. The obtained seismic velocity changes appear to be associated with variations in water saturation and effective pore pressure for different compartments of the aquifer. Our results suggest that DAS combined with noise-based passive monitoring provides a solution to track the dynamics of an alluvial aquifer and estimate hydrological parameters relevant for effective groundwater resource management.
Bâ et al. (Fri,) studied this question.