Conference paper Open Access
Soubestre, Jean; D'Auria, Luca; Barrancos, José; Padilla, German D.; Perez, Nemesio
We develop an automatic network-based method for detecting and locating all kind of seismo-volcanic signals. Seismic data of the island of Tenerife continuously recorded by the Red Sı́smica Canaria, a permanent monitoring network composed of 16 broadband stations operated by the Instituto Volcanológico de Canarias (INVOLCAN), are analysed. The method is based on the analysis of eigenvalues and eigenvectors of the seismic network covariance matrix, the equivalent in the frequency domain of the cross-correlation matrix. First, the width of the network covariance matrix eigenvalues distribution is used to detect events. Then, the first eigenvector of the covariance matrix corresponding to each event is used to locate it. Our main hypothesis is that, by representing the principal component of the recorded wavefield, this first eigenvector characterizes the dominant event excluding the information related to the noise. Obtained locations are successfully compared with locations from a standard approach based on manual phase picking. Conversely to this latter traditional approach, the developed method has the advantage of not requiring a priori knowledge, to be fully automatic and to be able to analyse large amounts of data.