Pseudo-Prospective Forecasting of Induced and Natural Seismicity in the Hengill Geothermal Field

The Hengill geothermal field, located in southwest Iceland, is host to the Hellisheioi power plant, with its 40+ production wells and 17 reinjection wells. Located in a tectonically active area, the field experiences both natural and induced seismicity linked to the power plant operations. To better manage the risk posed by this seismicity, the development of robust and informative forecasting models is paramount. In this study, we compare the forecasting performance of a model developed for fluid-induced seismicity (the Seismogenic Index model) and a class of well-established statistical models (Epidemic-Type Aftershock Sequence). The pseudo-prospective experiment is set up with 14 months of initial calibration and daily forecasts for a year. In the timeframe of this experiment, a dense broadband network was in place in Hengill, allowing us to rely on a high quality relocated seismic catalog. The seismicity in the geothermal field is characterized by four main clusters, associated with the two reinjection areas, one production area, and an area with surface geothermal manifestations but where no operations are taking place. We show that the models are generally well suited to forecast induced seismicity, despite some limitations, and that a hybrid ETAS model accounting for fluid forcing has some potential in complex regions with natural and fluid-induced seismicity. In the southwest of Iceland, the Hengill volcanic region is the seat of a geothermal field exploited with two power plants. The power plants provide district heating and electricity to the capital region. The area continuously experiences small to moderate earthquakes, associated to the volcanic nature of the region and to the power plant operations (injection and withdrawal of fluids from the underground). To better manage the risk posed by these earthquakes, we use statistics-based computer simulations to forecast the rate of earthquakes during a year-long experiment. The simulations are trained on 14 months of data. One of the models (the Seismogenic Index) is designed to relate rate of earthquakes to the volumes of fluids injected and withdrawn; while the other relies on statistical characteristics of earthquake sequences. We show that these computer simulations are well suited to forecast earthquake rates in the Hengill geothermal field, even though they have their respective limitations. The combination of the statistical seismicity simulations with a term accounting for the volumes does show promising results in an area with complex earthquake sequences. Statistical models are used in a pseudo-prospective experiment to forecast daily seismicity rates in the Hengill geothermal field Epidemic-Type Aftershock Sequence (ETAS)-type models are able to adapt quickly to sudden changes in the seismicity rate The Seismogenic Index-type model performs at least as well as ETAS-type models outside periods of high-intensity seismic activity