Forecasting Magnitude Frequencies and Magnitude Occurrence Probabilities Using the Seismogenic Index Model

We test the performance of the seismogenic index model for forecasting magnitude frequencies and their occurrence probabilities of induced earthquakes. The seismogenic index model incorporates several parameters: injected fluid volume, b value of the Gutenberg-Richter magnitude scaling, seismogenic index, and p value of a modified Omori law to capture seismicity induced after shut-in. We apply this forecast model to compute retrospectively magnitude frequencies of seismicity induced by injections in hydrocarbeon and geothermal reservoirs. We include time dependency in our forecast tests and we account for times after shut-in of the operations. Furthermore, we compute cumulative seismic moment release for 34 injections using the seismogenic index model. Both, computed magnitude frequencies and seismic moment well agree with the observed magnitude distributions. Hence, the seismogenic index model performs well and the obtained results prove its reliability for forecasting induced event magnitudes. We combine this forecast model with the homogeneous Poisson process (HPP) which enables to compute occurrence probabilities of given magnitude events. Analyzing the waiting times statistics of induced earthquakes confirm the use of the HPP model. We find that the maximum magnitudes observed in the considered case studies of injections had probabilities of occurrence of up to 95 per cent.