Abstract. The rapid increase in energy demand in the city of Reykjavik has posed the need for an additional supply of hot water from deep geothermal energy. The deep hydraulic (re-)stimulation of well RV-43 on the peninsula of Geldinganes (north of Reykjavik) is an essential component of the plan implemented by Reykjavik Energy to meet this energy target. Hydraulic stimulation is often associated with fluid-induced seismicity, most of which is not felt on the surface, but which, in rare cases, can cause nuisance to the population and even damage to the nearby building stock. This study presents a first of its kind pre-drilling probabilistic induced-seismic hazard and risk analysis for the site of interest. Specifically, we provide probabilistic estimates of peak ground acceleration, European microseismicity intensity, probability of light damage (damage risk), and individual risk. The results of the risk assessment indicate that the individual risk within a radius of 2 km around the injection point is below 0.1 micromorts, and damage risk is below 10−2, for the total duration of the project. However, these results are affected by several orders of magnitude of variability due to the deep uncertainties present at all levels of the analysis, indicating a critical need in updating this a-priory risk assessment with in-situ data collected during the stimulation.

Induced seismicity is one of the main factors that reduces societal acceptance of deep geothermal energy exploitation activities, and felt earthquakes are the main reason for closure of geothermal projects. Implementing innovative tools for real-time monitoring and forecasting of induced seismicity was one of the aims of the recently completed COSEISMIQ project. Within this project, a temporary seismic network was deployed in the Hengill geothermal region in Iceland, the location of the nation's two largest geothermal power plants. In this paper, we release raw continuous seismic waveforms and seismicity catalogues collected and prepared during this project. This dataset is particularly valuable since a very dense network was deployed in a seismically active region where thousand of earthquakes occur every year. For this reason, the collected dataset can be used across a broad range of research topics in seismology ranging from the development and testing of new data analysis methods to induced seismicity and seismotectonics studies.