Body and surface wave reconstruction from seismic noise correlations between arrays at Piton de la Fournaise volcano

Abstract

AbstractBody wave reconstruction from ambient seismic noise correlations is an important step toward improving volcano imaging and monitoring. Here we extract body and surface waves that propagate in Piton de la Fournaise volcano on La Réunion island using ambient noise cross correlation and array‐processing techniques. Ambient noise was continuously recorded at three dense arrays, each comprising 49 geophones. To identify and enhance the Green's function from the ambient noise correlation, we apply a double beamforming (DBF) technique between the array pairs. The DBF allows us to separate surface and body waves, direct and reflected waves, and multipathing waves. Based on their azimuths and slownesses, we successfully extract body waves between all the combinations of arrays, including the wave that propagates through the active magmatic system of the volcano. Additionally, we identify the effects of uneven noise source distribution and interpret the surface wave reflections.