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Abstract

Induced earthquakes have peculiar characteristics such as relatively shallow depths, small-to-moderate magnitude, correlation with field operations, non-GR recurrence law, and eventually non-homogenous Poisson recurrence time. Thus, when dealing with induced seismicity, the standard Probabilistic Seismic Hazard Analysis (PSHA) has to be modified.This work aims at exploiting the information carried by the ongoing induced seismic sequence in quasi-real time to provide spatio-temporal predictions of ground shaking in a prescribed forecasting interval (in the order of days). First, the workflow adaptively updates the seismicity forecasts based on the incoming information as it becomes available. The clustering of seismic events in volume (3D seismicity) and time is modelled based on an Epidemic Type Aftershock Sequence (ETAS) model. The proposed 3D ETAS model encompasses a decoupled depth-area volumetric probabilistic kernel. The ETAS parameters will be re-calibrated to take into account non-GR long-term temporal boundary conditions in case of induced seismicity.Second, the PSHA is performed using proper ground motion prediction models (GMPE). By combining the time-dependent seismicity rates provided by ETAS model and the mentioned GMPE, PSHA in a prescribed forecasting interval is adopted for calculating the mean rates of exceeding certain ground-shaking levels. The procedure is demonstrated through retrospective hazard forecasting of induced seismicity recorded at the Geysers geothermal field in northern California in the time period of 2011-2015 during fluid injection in the vicinity of Prati 9 and Prati 29 injection wells. This work has been supported by PRIN-2017 MATISSE project No 20177EPPN2, funded by Italian Ministry of Education and Research.