A seismic network was installed in Helsinki, Finland to monitor the response to an ∼6-kilometer-deep geothermal stimulation experiment in 2018. We present initial results of multiple induced earthquake seismogram and ambient wavefield analyses. The used data are from parts of the borehole network deployed by the operating St1 Deep Heat Company, from surface broadband sensors and 100 geophones installed by the Institute of Seismology, University of Helsinki, and from Finnish National Seismic Network stations. Records collected in the urban environment contain many signals associated with anthropogenic activity. This results in time- and frequency-dependent variations of the signal-to-noise ratio of earthquake records from a 260-meter-deep borehole sensor compared to the combined signals of 24 collocated surface array sensors. Manual relocations of ∼500 events indicate three distinct zones of induced earthquake activity that are consistent with the three clusters of seismicity identified by the company. The fault-plane solutions of 14 selected ML 0.6–1.8 events indicate a dominant reverse-faulting style, and the associated SH radiation patterns appear to control the first-order features of the macroseismic report distribution. Beamforming of earthquake data from six arrays suggests heterogeneous medium properties, in particular between the injection site and two arrays to the west and southwest. Ambient-noise cross-correlation functions reconstruct regional surface-wave propagation and path-dependent body-wave propagation. A 1D inversion of the weakly dispersive surface waves reveals average shear-wave velocities around 3.3  km/s below 20 m depth. Consistent features observed in relative velocity change time series and in temporal variations of a proxy for wavefield partitioning likely reflect the medium response to the stimulation. The resolution properties of the obtained data can inform future monitoring strategies and network designs around natural laboratories.

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We present the deployment of a seismic network in the Helsinki capital area of Finland that was installed to monitor the response to the second stimulation phase of an ∼6-kilometer-deep enhanced geothermal system in 2020. The network consists of a dozen permanent broadband stations and more than 100, predominantly short-period, temporary stations. This 2020 deployment is characterized by a mix of single stations and arrays with diverse configurations. It covers a larger area and exhibits a smaller azimuthal gap compared with the network that monitored the first stimulation in 2018. We surveyed the outcropping rocks at one of the large array sites to study surface expressions of shear or weakness zones that are possibly connected to the stimulated volume at depth. We link the relatively large number of macroseismic reports received during the stimulation to an increased public awareness of the project together with an increased sensitivity because the second stimulation occurred during the local COVID-19 mobility restrictions. The spatial distribution of the reports seems to be controlled by the radiation pattern of the induced earthquakes and hence by the stress state in the reservoir. The continuous records contain strong energy at high frequencies above 50 Hz that is attributed to anthropogenic processes in the densely populated urban area. However, the exceptionally low attenuation of the bedrock yields good signal-to-noise ratio seismograms of the induced small events, the largest of which was magnitude ML 1.2. The signal quality of the obtained noise correlation functions is similarly very good. The data set has been collected to underpin a wide range of seismic analysis techniques for complementary scientific studies of the evolving reservoir processes and the induced event properties. These scientific studies should inform the legislation and educate the public for transparent decision making around geothermal power generation.

This study presents a plan for seismic monitoring of a region around a potential nuclear power plant. Seismic monitoring is needed to evaluate seismic risk. The International Atomic Energy Agency has set guidelines on seismic hazard evaluation and monitoring of such areas. According to these guidelines, we have made a plan for a local network of seismic stations to collect data for seismic source characterization and seismotectonic interpretations, as well as to monitor seismic activity and natural hazards. The detection and location capability of the network were simulated using different station configurations by computing spatial azimuthal coverages and detection threshold magnitudes. Background noise conditions around Pyhäjoki were analyzed by comparing data from different stations. The annual number of microearthquakes that should be detected with a dense local network centered around Pyhäjoki was estimated. The network should be dense enough to fulfill the requirements of azimuthal coverage better than 180° and automatic event location capability down to ML ∼ 0 within a distance of 25 km from the site. A network of 10 stations should be enough to reach these goals. With this setup, the detection threshold magnitudes are estimated to be ML = −0.1 and ML = 0.1 within a radius of 25 and 50 km from Pyhäjoki, respectively. The annual number of earthquakes detected by the network is estimated to be 2 (ML ≥ ∼ −0.1) within 25 km radius and 5 (ML ≥ ∼−0.1 to ∼0.1) within 50 km radius. The location accuracy within 25 km radius is estimated to be 1–2 and 4 km for horizontal coordinates and depth, respectively. Thus, the network is dense enough to map out capable faults with horizontal accuracy of 1–2 km within 25 km radius of the site. The estimation is based on the location accuracies of five existing networks in northern Europe. Local factors, such as seismic noise sources, geology and infrastructure might limit the station configuration and detection and location capability of the network.