Most earthquake location methods require phase identification and arrival-time measurements. These methods are generally fast and efficient but not always applicable to microearthquake data with low signal-to-noise ratios because the phase identification might be very difficult. The migration-based source location methods, which do not require an explicit phase identification, are often more suitable for such noisy data. Whereas some existing migration-based methods are computationally intensive, others are limited to a certain type of data or make use of only a particular phase of the signal. We have developed a migration-based source location method especially applicable to data with relatively low signal-to-noise ratios. We projected seismograms onto the ray coordinate system for each potential source-receiver configuration and subsequently computed their envelopes. The envelopes were time shifted according to synthetic P- and S-wavearrival times (computed using an eikonal solver) and stacked for a predefined time window centered on the arrival time of the corresponding phase. This was done for each component and phase individually, and the squared sum of the stacks was defined as the objective function. We applied a robust global optimization routine called differential evolution to maximize the objective function and thereby locate the seismic event. Our source location method provides a complete algorithm with only a few control parameters, making it suitable for automatic processing. We applied this method to single and multicomponent data using P and/or S phases. We conducted controlled tests using synthetic seismograms contaminated with a minimum of 30% white noise. The synthetic data were computed for a complex and heterogeneous model of the Pyhäsalmi ore mine in Finland. We also successfully applied the method to real seismic data recorded with the in-mine seismic network of the Pyhäsalmi mine.

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SUMMARY Microearthquakes with magnitude down to 0.3 were detected by the Taiwan Chelungpu‐fault Drilling Project Borehole Seismometers (TCDPBHS). Despite the large coseismic slip of 12 m at the drill site during the 1999 Chi–Chi earthquake, our studies show very little seismicity near the TCDPBHS drill site 6 yr after the Chi–Chi main shock. The microearthquakes clustered at a depth of 9–12 km, where the Chelungpu thrust fault turns from a 30° dipping into the horizontal decollement of the Taiwan fold‐and‐thrust tectonic structure. Continuous GPS surveys did not observe post‐slip deformation at the larger slip region and no seismicity was observed near the drill site. Therefore we suggest that the thrust belt above the decollement is locked during this interseismic period. We further investigated source parameters of 242 microearthquakes by fitting ω−2‐shaped Brune source spectra to our observation data using a frequency‐independent Q model. We find that the static stress drop increases significantly with increasing seismic moment. However, due to the intense debate on this topic of scaling‐relations and the related self‐similarity of earthquakes, we further improve the data analysis and correct for path and site effects using the Projected Landweber Deconvolution (PLD) method for events within some clusters. The PLD method analyses the source time functions of the larger and the smaller event by an iterative technique. As a result we received source dimensions and stress drops of larger events including path and site effect corrections. The results from the PLD method are less scattered and also show a positive relation between static stress drop and seismic moment. We find a similar positive trend for the apparent stress scaling with seismic moment.

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