Discrimination of induced seismicity by full moment tensor inversion and decomposition

Human activities, including operations related to mining and reservoir exploitation, may induce seismicity and pose a risk for population and infrastructures. While different observations are commonly used to assess the origin of earthquakes, there is a lack of rules and methods for the discrimination between natural and induced seismicity. The inversion and decomposition of the full moment tensor and the observation of relevant deviation from a pure double couple (DC) model may be an indicator for induced seismicity. We establish here a common procedure to analyse a set of natural and induced events of similar magnitude, which occurred in Germany and neighbouring regions. The procedure is based on an inversion method and on a consistent velocity model and recording network. Induced seismicity is recorded during different mining and/or reservoir exploitations. Moment tensors are inverted using a multi-step inversion approach. This method, which was successfully applied in previous studies at regional and teleseismic distances, is further developed here to account for full moment tensor analysis. We first find a best DC solution and then perform a full moment tensor inversion, fitting full waveforms amplitude spectra at regional distances. The moment tensor solution is decomposed into DC, compensated linear vector dipole and isotropic terms. The discrimination problem is then investigated through the evaluation of distributions of non-DC source components for natural and induced data sets. Results illustrate the potential of the inversion and discrimination approach. Additional detailed analyses are carried out for the two most significant induced earthquakes, and rupture models are compared with the full moment tensor solutions.