Abstract

The data-adaptive autoregressive (hereafter DA) method was used to detect local and regional seismic events using digital data from the Vaasa (VAF) station with co-ordinates (62.3°N, 22.2°E) in western Finland.

The seismic signal and the noise were assumed to have been normally distributed stochastic processes with a zero mean. The parameters of these processes were then adapted on the change of the registered signal as a function of time within a predefined detection window.

The accuracy of the method presented is compared with the STA/LTA and visual methods. When the same detection threshold was used with the DA detector and the STA/LTA detector, it was found that the DA detector was more precise in detecting the onsets of seismic events. Bandpass (1.5 to 20 Hz) filtering was used in all the events discussed. This was done to reject the long-period microseismic noise. In one case, the detector was used on nonfiltered as well as filtered data, in order to show coinciding results.

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