Optimizing event detection and location in low-seismicity zones: Case study from Western Switzerland

Obtaining robust event catalogs in regions of low seismicity can be time-consuming, because quality events are less frequent and sensor coverage is generally sparse. Optimizing event detection and location in such regions is all the more crucial because these areas tend to host a higher density of sensitive infrastructures. The methodology proposed consists of reprocessing existing data recorded by a permanent network and boosting the final catalog resolution by temporarily deploying portable sparse mini-arrays in the target area. Sonogram analysis is applied on both existing and new datasets to detect waveforms barely emerging from the background noise. A visual interactive event analysis module is used to test for phase picking, event association, waveform cross correlation, and location ambiguities. It also estimates back azimuth and slowness when sparse array data are available. The method is applied to a low-seismicity region in the western Swiss Molasse basin where two sparse mini-arrays were temporarily deployed. The detection of earthquakes is improved by a factor of 9 when reprocessing four yrs (2009–2013) of available data recorded by two accelerometers and one broadband station in a 2500 km² target area. Magnitude estimations are empirically calibrated over four magnitude units, down to −1:7 M_L, lowering the existing catalog completeness by close to one magnitude unit. After validating picking and location accuracies with a standard residual-based scheme, 174 newly detected events are relocated, illuminating zones of previously undetected microseismic activity.