Application of the Multichannel Wiener Filter to Regional Event Detection Using NORSAR Seismic-Array Data

Abstract

Seismic arrays for detection of small earthquakes benefit from reduced noise levels by array processing methods. We present a frequency-dependent multi-channel Wiener fil- tering (MCWF) technique, which employs an adaptive least-squares method to remove coherent noise in seismic array data. The noise records on a number of reference chan- nels are used to predict the noise on a primary channel, which can then be subtracted from the observed data. A sequence of aftershocks caused by a Feb, 21, 2008 main shock in Spitsbergen was recorded in 2008 by the ARCES array in northern Norway. This aftershock sequence was filtered using the multi-channel Wiener filters on both triggered and continuous modes. The Spitsbergen (SPITS) array at a much closer dis- tance to the source region provides reliable reference information on the true number of detectable aftershocks. The triggered procedure detects 631 aftershocks at ARCES in total, where conventional delay-and-sum beamforming combined with a band-pass filter could detect 513 aftershocks with 181 false alarms using a series of constraints, signal-to-noise ratio (SNR), back azimuth and slowness; the multi-channel Wiener fil- tered results found 577 aftershocks with 165 false alarms using the same constraints. A complete automatic multi-channel Wiener procedure is developed for event detec- tion on continuous data. The appropriate SNR threshold for aftershock detection 2.7 is suggested. The MCWF also demonstrates the advantage of reducing false alarms compared to the beamforming method when detecting the same number of aftershocks.