Ambient seismic noise processing to monitor sea dikes: the case of Noirmoutier, France

The use of ambient noise for passive seismic imaging has evolved into a cutting-edge, low-cost, and environmentally acceptable method of exploring the subsurface. This technique dispenses with active seismic sources, alternatively uses ambient seismic noise. Theoretical investigations have approved that an estimate of the empirical Green’s function between receivers could be obtained from the cross-correlation of ambient noise and/or dispersed coda waves. This Green’s function is mostly made up of fundamental Rayleigh waves, propagating between two receivers as if they would be caused at one of them. The applications of ambient noise surface wave tomography, from engineering and urban developments to regional and continental scales, have led to the mapping of the area's velocity model, which chiefly corresponds to the structural/geological units.

Because of numerous devastating catastrophes in recent years, several countries have made flood protection a priority. However, sea-dikes are considered remarkably heterogeneous and may fail due to their construction and/or reinforcing structures; they are potentially subject to stress by sea waves during the tidal cycle and seasonal heat variations, resulting in the water infiltration. Internal abnormalities cannot be recognised in the early stages of erosion, although visual assessments may often be relied on. In this study, we outline a passive seismic survey that was carried out to investigate technical and methodological aspects of passive seismic methods along with their application in a sea dike monitoring perspective. 

The SEEWALL project is a collaborative project, seeking to create innovative methodology to monitor the temporal evolution of sea dikes and detect early deterioration. We deployed 160 permanent 3-component MEMS accelerometers spaced 2 meters apart on top of a dike on the island of Noirmoutier (France), which was exhibiting moderate water infiltrations at its base. Despite the inhomogeneous distribution of the ambient noise sources, exploitable empirical Green's functions can be retrieved mostly from the cross-correlation of vertical component data. We estimate the surface wave phase velocity dispersion curves  using a time-frequency analysis; strictly speaking, after preconditioning the data, the cross-correlation is carried out in the frequency domain by carefully windowing data, from which each  empirical Green's functions is derived; their cross-correlations are stacked linearly by hours. The arrival times of the causal and anti-causal parts are often not fully symmetrical, indicating the diversity of major noise sources. The phase velocities measured on both positive and negative lag-times, as a function of the frequency, are computed using the phase-shift method. Interpretation of the phase velocity dispersion curves is challenging due to the geometry of the dike at the scale of the intended wavelength (a few tens to hundreds meters). But the pattern of the dispersion data appears to be relatively stable over time. It is also consistent with the dispersion curves we have obtained using active seismic hammer-shots, performed along the structure. For monitoring, we suggest using F-K spectra to highlight the variety of energy density over time, in order to advance a deeper understanding of data analysis; this enables us to discover any changes that might not be otherwise obvious.