Manifestations of supercritical water in magmatic environments have so far only been accessible from analogue outcrops of fossil systems and by simulating pressure/temperature conditions in the laboratory. In order to assess the unknown properties of such reservoirs, scientific drilling is used when Earth surface sampled rocks cannot sufficiently explain past geological processes and when geophysical imaging does not sufficiently explain observed phenomena. However, our understanding of structural and dynamic characteristics of geothermal systems can be improved through application of advanced and/or innovative exploration technologies. Unlike resistivity imaging, active and passive seismic techniques have rarely been used in volcanic geothermal areas, because processing techniques were not adapted to geothermal conditions. Recent advances in volcano-seismology have introduced new processing techniques for assessing subsurface structures and controls on fluid flow in geothermal systems. We present here preliminary analyses of seismic records around a geothermal reservoir located both on-land and offshore along the Reykjanes Ridge, SW-Iceland. We deployed on-land stations (20 broad-band and 10 short-period seismometers) and 24 Ocean Bottom Seismometers which are recording since April 2014. Together with existing permanent stations, the complete network comprises 66 stations. The network was designed so that several processing techniques can be used with the data set and address scientific questions concerning geothermal systems and the oceanic ridge. We present the network deployment, our approach and preliminary results from the first months.@en

We present tomographic results obtained around geothermal reservoirs using seismic data recorded both on-land Reykjanes, SW-Iceland and offshore along Reykjanes Ridge. We gathered records from a network of 83 seismic stations (including 21 Ocean Bottom Seismometers) deployed between April 2014 and August 2015. We obtain crustal velocity images from several tomography methods. First, we used local earthquakes to perform travel time tomography. The processing includes first arrival picking of P- and S-phases using an automatic detection and picking technique based on Akaike Information Criteria. We locate earthquakes by using a non-linear localization technique, as a priori information for deriving a 1D velocity model. We then computed a 3D velocity model by joint inversion of each earthquake’s location and velocity lateral anomalies with respect to the 1D model. Our results confirms previous models obtained in the area, with enhanced details. Second, we used ambient noise cross-correlation techniques which involve the computation of cross-correlation between seismic records. Empirical Green’s functions are estimated and analyzed to derive an S-wave velocity model by surface wave tomography. Third, noise correlation theory shows that zero-offset P-wave reflectivity at selected station locations can be approximated by auto-correlating and stacking station data. With few assumptions, single-station autocorrelations provide local 1D high-resolution structural acoustic-contrast versus depth information. We show that the application of ambient noise interferometry for reflection retrieval complement well the results from both classical and noise tomography methods. @en