A Bayesian probabilistic approach to estimate the focal mechanism of micro-earthquakes occurring at the Irpinia fault system, southern Italy.

We developed a Bayesian technique to infer the double-couple, focal mechanism parameters (strike, dip and slip angles) of an earthquake source. The method uses 3 independent datasets: P-wave peak amplitude and polarity and S-to-P amplitude ratio wherever it is available.

The Bayesian technique works even in absence of one dataset and easily integrates any prior information about the region of study. The parameter space is explored thanks to an octree strategy. The method estimates the Posterior pdf, where the maximum likelihood parameter values (MAP model) both for the principal and auxiliary plane are chosen as the final fault mechanism solution. Furtherly, the uncertainties as the projections of the semi-axis of the 68% confidence ellipsoid centred on the MAP model are provided.

The joint use of the three datasets allows to determine a solution even in the case of a limited number of stations that have recorded the event, which is the case for example for small magnitude earthquakes (M<3).

We applied and tested the methodology to a microearthquake sequence (M_L 0.4-3.0) occurred in the Irpinia region, South Italy, using an uninformative prior distribution for the parameters. In this area, the background seismicity occurs in a volume delimited by the faults activated during the 1980 Irpinia M 6.9 earthquake. This faults system is complex and composed of northwest–southeast striking normal faults along the Apennines chain. A network of 3-component accelerometers and velocimeters is currently monitoring the area (Irpinia Seismic NETwork).

We inferred the focal mechanism of the earthquakes of the sequence. Our results show fault mechanism solutions which are consistent with previous studies, well reflecting the regional stress field. The focus on micro-seismicity can reveal characteristics useful to highlight behaviours of larger scale seismicity.