Stress field analysis from induced earthquakes caused by deep fluid injection: the 2013 St. Gallen (Switzerland) seismic sequence.

The city of St. Gallen is located in the Molasse Basin of northeast Switzerland. Mesozoic units of the substratum are affected by a fault system hosting a hydrothermal reservoir. In 2013 a deep geothermal drilling project started in an area close to the city. During a phase of reservoir stimulation, a sequence of more than 340 earthquakes was induced with a maximum magnitude M_L 3.5. Stress inversion of seismological datasets became an essential tool to retrieve the stress field of active tectonics areas. With this aim, a dataset of the best constrained Fault Plane Solutions (FPSs) was processed in order to qualitatively retrieve stress-fields active in the investigated volume. FPSs were obtained by jointly inverting the long-period spectral-level P/S ratios and the P-wave polarities following a Bayesian approach (BISTROP). Data were preliminarily processed by the Multiple Inverse Method to evaluate the possible dataset heterogeneity and separate homogeneous FPS populations. The resulting dataset was then processed using the Bayesian Right Trihedra Method (BRTM). Considering that hypocentral depths range between 4.1 and 4.6 km b.s.l., in order to emphasize depth-related stresses, we performed a first step of raw stress inversion procedure splitting the data into five subsets, grouping events located inside 100-m depth ranges. Once the presence of stress variations with depth has been excluded, the second step of fine stress inversion procedure was performed on the entire dataset. The stress-inversion procedure highlights an active stress field dominated by a well-constrained NE low-plunging σ₃ and a corresponding NW low-plunging σ₁. The corresponding Bishop ratio confirms the stability of the retrieved attitudes. Results are in good accordance with the regional stress field derived from regional natural seismicity. Additionally, the retrieved, dominant, stress field is coherent with the regional tectonic setting.

This research has been supported by PRIN-2017 MATISSE project (No. 20177EPPN2).