Inversion of multi-mode Rayleigh wave dispersion curves for regional imaging: Application to the Basque-Cantabrian Zone (N Spain)

Surface waves in seismic noise correlation functions are routinely exploited to image structures at a broad range of scales and resolutions. In most applications, the correlation functions are considered (1) to be estimates of the Green's function between pairs of receivers and (2) to be composed mainly of fundamental-mode surface waves. This approach requires at least an inter-station distance of 3 wavelengths to produce reliable phase/group velocity measurements, which can be a limiting factor when working at local or regional scales. Additionally, as shown by many previous studies, the presence of superficial low-velocity layers may cause a dominance of higher modes over certain frequency ranges, which means that only considering the fundamental mode may not be enough to accurately model the observed dispersion curves.

In this work, we overcome the limitations by measuring Rayleigh wave phase velocities directly from the cross-correlation spectra. This approach does not depend on the far-field approximation and is, therefore, not subject to the three-wavelength rule. We use these measurements to produce a set of phase velocity maps using a standard tomographic algorithm. Finally, for a set of regularly spaced nodes, dispersion curves are compiled from the phase velocity maps and used in a non-linear inversion to obtain the 1D shear-wave velocity structure. Previous geological and geophysical studies are used to place constraints on the non-linear inversion.

We apply this methodology to seismic data acquired in the Basque-Cantabrian region (N Spain) between 2014 and 2018 (by the SISCAN-MISTERIOS network, with inter-station distances ranging from 7 to 400 km) and obtain a 3D model of this structurally complex area (a thick Mesozoic basin inverted and incorporated into the Pyrenean-Cantabrian mountain belt in the Cenozoic) which agrees with the existing geological knowledge but significantly extends the area for which high-resolution information is available.