Eikonal tomography using Coherent surface Wavefronts extracted from Ambient seismic Noise with a Matched-Filtering Approach

Recent advances in tomographic methods, such as Helmholtz/Eikonal tomography, leverage seismic wavefields recorded by dense regional seismic networks to produce finely resolved images of the subsurface. This approach directly uses phase and amplitude measurements of coherent wavefronts generated by large earthquakes, bypassing the need to solve large tomographic inverse problem or compute synthetic seismograms. However, since these earthquakes are mainly located at plate boundaries, the azimuthal distribution of the sources is often limited. In addition, obtaining robust phase velocity maps typically requires years of continuous seismic data. In contrast, oceanic microseisms - responsible for ambient seismic noise - are more evenly distributed and generate coherent wavefronts continuously. In this study, we apply a matched filtering technique to iteratively extract these coherent surface wavefronts. Within a 4-hour time window, we typically extract 10 to 20 coherent wavefronts, from which we can measure arrival time and amplitude at each station. After removing outliers, phase measurements are interpolated using smoothing splines on either a Cartesian or a spherical grid, depending on the size of the domain under study. The gradient of the interpolated phase velocity surfaces is then used in the eikonal equation to generate phase velocity maps. These maps are stacked to produce average isotropic phase velocity maps for periods ranging from 6 to 25 s. We will present applications of this method in California and Western Europe.