Ocean-bottom seismometers (OBSs) are equipped with seismic sensors that record acoustic and seismic events at the seafloor, which makes them suitable for investigating tectonic structures capable of generating earthquakes offshore. One critical parameter to obtain accurate earthquake locations is the absolute time of the incoming seismic signals recorded by the OBSs. It is, however, not possible to synchronize the internal clocks of the OBSs with a known reference time, given that GNSS signals are unable to reach the instrument at the sea bottom. To address this issue, here we introduce a new method to synchronize the clocks of large-scale OBS deployments. Our approach relies on the theoretical time-symmetry of time-lapse (averaged) crosscorrelations of ambient seismic noise. Deviations from symmetry are attributed to clock errors. This implies that the recovered clock errors will be obscured by lapse crosscorrelations' deviations from symmetry that are not due to clock errors. Non-uniform surface wave illumination patterns are arguably the most notable source which breaks the time symmetry. Using field data, we demonstrate that the adverse effects of non-uniform illumination patterns on the recovered clock errors can be mitigated by means of a weighted least-squares inversion that is based on station-station distances. In addition, our methodology permits the recovery of timing errors at the time of deployment of the OBSs. This error can be attributed to either: i) a wrong initial time synchronization of the OBS or ii) a timing error induced by changing temperature and pressure conditions while the OBS is sunk to the ocean floor. The methodology is implemented in an open-source Python package named OCloC, and we applied it to the OBS recordings acquired in the context of the IMAGE project in and around Reykjanes, Iceland. As expected, most OBSs suffered from clock drift. Surprisingly, we found incurred timing errors at the time of deployment for most of the OBSs.@en

The timing of the recordings of ocean-bottom seismometers (OBSs) is critical for accurate earthquake location and Earth model studies. GNSS signals, however, cannot reach OBSs deployed at the ocean bottom. This prevents their clocks from being synchronized with a known reference time. To overcome this, we developed OCloC, a Python package that uses time-lapse cross-correlations of ambient seismic noise to synchronize the recordings of large-scale OBS deployments. By simultaneously quantifying deviations from symmetry of a set of lapse cross-correlations, OCloC recovers the incurred clock errors by means of a least-squares inversion. In fact, because non-uniform noise illumination patterns also break the symmetry of (lapse) cross-correlations, we introduce a distance-based weighted least-squares inversion. This mitigates the adverse effect of the noise illumination on the recovered clock errors. Using noise recordings from the IMAGE project in Reykjanes, Iceland, we demonstrate that OCloC significantly reduces the time and effort needed to detect and correct timing errors in large-scale OBS deployments. In addition, our methodology allows one to evaluate potential timing errors at the time of OBS deployment. These might be caused by incorrect initial synchronization, or by rapidly changing temperature conditions while the OBS is sunk to the sea bottom. Our work advances the use of OBSs for earthquake studies and other applications.@en

In autumn 2017 a network of 14 broadband seismic stations was deployed at the Theistareykir high temperature geothermal field (NE Iceland). This experiment was conducted as part of the current efforts to characterize the field's main structures, and possible short and long term stress variations due to the ongoing fluid injection and extraction operations which started in autumn 2017. In this work, we use two years of continuous seismic records (October 2017–October 2019) to compute a 3D shear wave velocity model of the geothermal field and to detect possible crustal stress changes related to the injection and production activities. From phase cross-correlations of the vertical component recordings, we measure the Rayleigh wave group velocity dispersion curves to obtain 2D group velocity maps between 1 and 5 s. Subsequently, we use a neighborhood algorithm to retrieve the 3D shear wave velocity model of Theistareykir. Mainly, two sets of elongated high and low velocity anomalies can be observed oriented in a NW/WNW direction, parallel to the lineaments of the active Tjörnes fracture zone. Velocity reductions west of Ketilfjall and at Baerjafjall could indicate the location of upflow zones of the magmatic reservoir or hydrothermal system. We analyzed the temporal evolution of phase and amplitude of phase auto-correlations using the stretching technique and discuss their behavior in relation to the geothermal field operations. We notice a slightly stronger long-term velocity decrease in the reservoir region compared to outer regions. This could be related to the mass depletion in that area (higher fluid extraction compared to the water reinjection). In summary, our findings show how a monitoring network can be set up to enable a detailed imaging and monitoring of reservoir behavior in general.

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In volcanic and hydrothermal geosystems, monitoring of mass and stress changes provide information for both volcanic hazardassessment and estimation of geothermal resources. The combined continuous recording of the gravity field and ground motionwith sufficient accuracy in an active volcano-tectonic setting allows a better understanding of the mass and stress transfermechanisms that produce short term gravity changes and local seismic activity. The aim is to gain a better understanding ofgeothermal system processes by addressing short-term mass changes within geothermal reservoirs in relation to external influencessuch as anthropogenic (reservoir exploitation) and natural forcing (local and regional earthquake activity and earth tides). Thiscontributes to knowing the reservoir properties, structure and long-term behaviour.Þheistareykir (Northeast Iceland), where the geothermal power production started in autumn 2017 (2x45 MWe) is the site chosenfor this unique experiment. The overall goal of the project is to use a network of continuously measuring gravity meters to detectsmall variations in gravity associated with managing a geothermal field (injection and extraction). The gravity changes are expectedto be small: ~5 µgal/6 months (1 µgal=10-8 ms-2). Therefore, high performance and up-to-date instrumentation such assuperconducting gravity meters (SG), spring gravity meters and broadband seismometers are used. To achieve these goals, inautumn 2017 a network of 5 relative gravity meters (3 iGravs and 2 gPhones) and 14 seismic stations were deployed. Three gravitymonitoring sites are in close vicinity to the production and injection area, and one iGrav is set up outside the geothermal field forreference. Presented in this report are the details of the infrastructure and instruments deployed and the first results of more than 18months of continuous gravity and seismicity monitoring.@en

Accurate timing of seismic records is essential for almost all applications in seismology. Wrong timing of the waveforms may result in incorrect Earth models and/or inaccurate earthquake locations. As such, it may render interpretations of underground processes incorrect. Ocean bottom seismometers (OBSs) experience clock drifts due to their inability to synchronize with a GNSS signal (with the correct reference time), since electromagnetic signals are unable to propagate efficiently in water. As OBSs generally operate in relatively stable ambient temperature, the timing deviation is usually assumed to be linear. Therefore, the time corrections can be estimated through GPS synchronization before deployment and after recovery of the instrument. However, if the instrument has run out of power prior to recovery (i.e., due to the battery being dead at the time of recovery), the timing error at the end of the deployment cannot be determined. In addition, the drift may not be linear, e.g., due to rapid temperature drop while the OBS sinks to the seabed. Here we present an algorithm that recovers the linear clock drift, as well as a potential timing error at the onset. The algorithm presented in this study exploits seismic interferometry (SI). Specifically, time-lapse (averaged) cross-correlations of ambient seismic noise are computed. As such, virtual-source responses, which are generally dominated by the recorded surface waves, are retrieved. These interferometric responses generate two virtual sources: a causal wave (arriving at a positive time) and an acausal wave (arriving at a negative time). Under favorable conditions, both interferometric responses approach the surface-wave part of the medium's Green's function. Therefore, it is possible to calculate the clock drift for each station by exploiting the time-symmetry between the causal and acausal waves. For this purpose, the clock drift is calculated by measuring the differential arrival times of the causal and acausal waves for a large number of receiver-receiver pairs and computing the drift by carrying-out a least-squares inversion. The methodology described is applied to time-lapse cross-correlations of ambient seismic noise recorded on and around the Reykjanes peninsula, SW Iceland. The stations used for the analysis were deployed in the context of IMAGE (Integrated Methods for Advanced Geothermal Exploration) and consisted of 30 on-land stations and 24 ocean bottom seismometers (OBSs). The seismic activity was recorded from spring 2014 until August 2015 on an area of around 100 km in diameter (from the tip of the Reykjanes peninsula).@en

Tomographic imaging based on ambient seismic noise measurements has shown to be a powerful tool, especially in areas like Iceland, where the microseism illumination is excellent. In this paper, we produce a 3D S-wave tomographic image over the western Reykjanes Peninsula high-enthalpy geothermal fields and evaluate the reliability of the tomographic results for different resolutions through simulated and real data. We use 30 broadband stations operating for approximately one-and-a-half year and apply ambient noise seismic interferometry for each station-pair. This results in empirical Green's functions in which especially the ballistic surface waves (BSW) are well resolved. The retrieved BSW exhibit a high signal-to-noise ratio between 0.1 and 0.5 Hz, and the beamforming analysis indicates an apparent surface-wave velocity of 3 km/s over a broad azimuthal range. For the tomographic inversion, we invert the estimated phase velocities between all station pairs to frequency-dependent phase velocity maps in four different resolutions (1, 2, 3, and 4 km) using a Tikhonov regularisation. With the estimated regularisation parameter per frequency per resolution, we invert simulated data for checkerboard sensitivity tests per frequency for different combinations of velocity anomaly sizes and resolutions.

Finally, after the inversion to depth, we detect S-wave velocity anomalies with variations between −15% and 15% with reference to an estimated average velocity using 1 km and 3 km of lateral resolutions and 1 km of vertical resolution. This study shows the potential of ambient noise tomography as complementary seismological tool for reservoir characterization.@en

The Reykjanes Geothermal System (RGS) is a high-temperature geothermal system located on the Reykjanes peninsula, a transtensional plate-boundary zone located on the southwestern tip of Iceland. The area is characterized by high seismicity, recent volcanism, and high-temperature geothermal fields. We use seismic noise records from April 2014 to August 2015 to study stress changes and potential deformation of the subsurface caused by injection and production operations at RGS through seismic interferometry. We retrieve continuous time series of waveform similarity values and seismic velocity changes during this period. The S-transform of the similarity values allows us to clearly identify three variations in the mechanical properties of the Reykjanes peninsula related to rapid changes of RGS production. In addition, we observe a slow seismic velocity decrease of 0.36%/year in the reservoir due to the water deficit and seasonal variations associated with the energy production demand.

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Integration of results from active seismic, passive seismic and well data reduces the uncertainties of several subsurface parameters that are of interest for cost-effective geothermal production operations in Los Humeros. In this study, we present results from the application of ambient noise seismic interferometry (ANSI) to retrieve zero-offset reflected P-waves from continuous seismic data recorded at the Los Humeros geothermal field, Mexico. This study is inspired by encouraging results from the application of ANSI for body wave reflection retrieval that was reported in 2016 for a geothermal field located at Reykjanes peninsula, Iceland (Verdel et al., 2016). Continuous broadband and short-period seismic recordings provided insightful reflection information that corresponded well, in relevant depth intervals, with reflectivity retrieved from the correlation of coda waves from a distant but very strong earthquake. That work was carried out within the context of EU’s Seventh Framework research and innovation program IMAGE. Encouraged by these findings, it was decided to conduct a new study following a similar approach within the context of the GEMex project, a European-Mexican collaboration. The purpose of GEMex is to gain an improved understanding of the geological structure and geothermal reservoir behaviour for two geothermal fields: Los Humeros and Acoculco. In the following, we address data selection and processing aspects related to the retrieval of reflected P-waves from Los Humeros seismic noise recordings. The retrieved reflections are compared with modelled reflectivities at two station locations at a close distance from the location where the seismic interval velocities that are used in the modelling were available from the literature. The reflected P-wave information provides structural detail about the field at locations directly underneath the employed seismic stations.@en

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.@en

Timing errors are a notorious problem in seismic data acquisition and processing. A technique is presented that allows such time shifts to be detected and corrected in a systematic fashion. The methodology relies on virtualsource responses retrieved through the application of seismic interferometry (SI). In application to recordings of ambient seismic noise, SI involves temporal averaging of time-windowed crosscorrelation measurements. Because surface waves dominate the ambient seismic field, the retrieved interferometric responses are typically also dominated by surface waves. Under favorable conditions, these interferometric responses therefore approach the surface-wave part of the medium's Green's function. Additionally, however, its time-reverse is also retrieved under those conditions. This implies time-symmetry of the time-averaged receiver-receiver crosscorrelations. It is this time-symmetry that is exploited in this study. By comparing the arrival time of the interferometric surface waves at positive time to the arrival time of the interferometric surface waves at negative time for a large a number of receiverreceiver pairs, relative timing errors are determined in a least-squared sense. The proposed methodology is validated using both synthetic data and field data. The results hold particular promise for time-lapse (4D) seismic surveys.@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 present results from the application of ambient noise seismic interferometry (ANSI) to data that were recorded continuously in 2014 and 2015 at Iceland’s peninsula Reykjanes. The objective of this study is the retrieval of reflected body waves (P-waves) that provide high-resolution velocity-versus-depth as well as subsurface structural information. We show, for a subset of the onshore seismometers, that reflection information is present in the frequency bandwidth 3-8 Hz. We have observed both time-lapse variations where we expect them and time-invariant results where we do not expect to see changes. As we lacked availability of active seismic reflection and well-sonic data that could serve as reference, we discovered, in our search to find a truly independent means for checking the reflection information quality of our ANSI results, that the coda of a global seismic P-wave, that is created by scattering in the crust, contains very high frequent (3-8 Hz) reflectivity information as it shows quite good correspondence with the 40-days ANSI results, whereas random noise correlation results, using the same amount of data as the coda response, shows less resemblance. We conclude that these results justify a more detailed investigation of the merits of the ANSI method for this data set. But then, the ANSI-derived reflectivity estimates in turn clearly suggest that indeed P-wave crustal scattering information from global seismic waves is present in the frequency-range of 3–8 Hz, which is extremely high for global seismic waves. The latter aspect may open up a large range of opportunities for detailed crustal research at any location on the globe where broadband, and even shortperiod, seismometers are installed. @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 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

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