4-D monitoring of the Solfatara crater (Italy) by ambient noise tomography

Thursday, 18 December 2014
Marco Pilz1, Heiko Woith1, Stefano Parolai1 and Gaetano Festa2, (1)Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany, (2)The University of Naples Federico II, Naples, Italy
Imaging shallow subsurface structures and monitoring related temporal variations are two of the main tasks for modern seismology. Although many observations have reported temporal velocity changes, e.g., in volcanic areas and on landslides, new methods based on passive sources like ambient seismic noise can provide accurate spatially and temporally resolved information on the velocity structure and on velocity changes. The success of these passive applications is explained by the fact that these methods are based on surface waves which are always present in the ambient seismic noise wave field because they are excited preferentially by superficial sources. Such surface waves can easily be extracted because they dominate the Green´s function between receivers located at the surface.

For real-time monitoring of the shallow velocity structure of the Solfatara crater, one the forty volcanoes in the Campi Flegrei area characterized by an intense hydrothermal activity due to the interaction of deep convection and meteoric water, we have installed a dense network of 50 seismological sensing units covering the whole surface area in the framework of the European project MED-SUV. Continuous recordings of the ambient seismic noise over several days as well as signals of an active vibroseis source have been used. Based on a weighted inversion procedure for 3D-passive imaging using ambient noise cross-correlations of both Rayleigh and Love waves, we will present a high-resolution velocity model of the structure beneath the Solfatara crater. We discuss why and how it is possible to perform high precision and real-time monitoring of temporal changes in the properties of the propagation medium at small scales. In particular, we will focus on the depth resolution of the presented approach and further discuss the perspectives of noise-based real-time 4-D tomography.