Probabilistic centroid moment tensor inversions using geologically constrained priors: Application to induced earthquakes in the Groningen gas field, the Netherlands

We use the Hamiltonian Monte Carlo (HMC) algorithm to estimate the posterior probability distribution of a number of earthquake source parameters. This distribution describes the probability of these parameters attaining a specific set of values. The efficiency of the HMC algorithm, however, can be improved through the formulation of a geologically constrained prior probability distribution. The primary objective of the presented study is, therefore, to assess the role of the prior probability in the application of the HMC algorithm to recordings of induced seismic events in the Groningen gas field.