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 report on the results obtained from a dense seismic deployment over a geothermal reservoir located on the tip of the Reykjanes peninsula, SW Iceland. The available seismic stations have continuously recorded the ambient-seismic wave field between April 2014 and August 2015. Using seismic interferometry (SI), seismic responses were generated between these receivers. SI allows one to turn one receiver of a receiver pair into a so-called ‘virtual source’, whose response is then retrieved by the other receiver. The retrieved virtual-source response approximates the medium’s Green’s function between the two receiver locations. For the ambientseismic recordings used in this study, virtual-source retrieval involves simple time-averaging of the crosscorrelations between these recordings. The virtual-source responses were retrieved in a time-lapse manner. The temporal variation of the ‘coda’ of these virtual-source responses has been evaluated, where the term coda refers to the later arriving, multiply scattered waves. The multiple scattering implies that these waves have sampled the subsurface very densely and hence have become highly sensitive to tiny mechanical and structural changes in that subsurface. We did not find a clear relation between the temporal variation of the coda waves and the injection/ extraction rates of the geothermal reservoir. @en

We report on the results obtained from a dense seismic deployment over a geothermal reservoir. The reservoir has been producing continuously for almost a decade and is located on the tip of the Reykjanes peninsula, SW Iceland. The seismic stations on top of the reservoir have continuously recorded the ambient seismic wavefield between April 2014 and September 2015. The density of the seismic network makes the data well suited for time-lapse seismic imaging of the reservoir. To that end we compute time-lapse responses through the application of seismic interferometry. These interferometric lapse responses are obtained by simple crosscorrelation of the seismic noise recorded by the different seismic stations. We subsequently evaluate the temporal variation of the coda of these crosscorrelations. The term coda refers to the later arriving, multiple scattered waves. The multiple scattering implies that these waves have sampled the subsurface very densely and hence become highly sensitive to tiny mechanical and structural changes in that subsurface. This sensitivity allows one, in principle at least, to monitor the geothermal reservoir. Preliminary results indeed suggest a relation between the temporal variation of the coda waves and the reservoir. Ultimately, this method may lead to a means to monitor a geothermal reservoir in both space and time. @en

We report on a Bayesian (i.e., probabilistic) inversion for the shear-wave velocity structure of the Reykjanes peninsula, SW Iceland. Travel times of Rayleigh waves traversing the peninsula served as input to the probabilistic algorithm. These Rayleigh waves were retrieved through the application of seismic interferometry to yearlong recordings of ambient seismic noise. The Reykjanes peninsula is well placed for this technique because it is surrounded by ocean, which implies a relatively uniform seismic noise illumination; the latter being a condition for accurate interferometric surface wave retrieval. The Bayesian algorithm uses a variable model parametrization by employing Voronoi cells in conjunction with a reversible jump Markov chain Monte Carlo sampler. The algorithm is entirely data-driven, meaning that, contrary to conventional deterministic tomographic inversions, the user does not need to define any regularization or parameterization parameters to solve the inverse problem. The geology in the area of interest is characterized by four NE-SW trending volcanic systems, orientated oblique to the divergent plate boundary cutting across the Reykjanes Peninsula. These are from west to east; Reykjanes, Svartsengi, Fagradalsfjall and Krýsuvík, of which all except Fagradalsfjall host a known high-temperature geothermal field. We observe relatively high shear wave velocity patches close to the Earth’s surface (top two kilometers) at the location of these known high-temperature fields. These high velocity anomalies invert to relatively low shear wave velocities (in comparison to shear wave velocities in the same horizontal plane) at depths greater than 3 km. The latter low-velocity anomalies are relatively small below Reykjanes and Svartsengi. At depths of 5 to 8 km, a low-velocity anomaly extends horizontally below Reykjanes and Svartsengi, correlating relatively well with the inferred brittle-ductile transition below the high-temperature fields at 4-5 km depth. The low-velocity anomaly below Krýsuvík is much larger and coincides with a deep-seated low electrical resistivity anomaly. Horizontally, it coincides with the center of an inflation source at 4–5 km depth. For example, in 2010 this resulted in an uplift exceeding 50 mm/year, but several periods of alternating uplift and subsidence associated with increased seismicity have been observed in Krýsuvík since 2009. Our results both confirm and add details to previous models obtained in the area. Our study demonstrates the potential of Bayesian surface wave inversion as a complementary geophysical tool for geothermal exploration. @en