MAKING THE MOST OF THE RECORDINGS FROM SHORT-PERIOD SEISMOMETER ARRAYS

Several methods have been developed for computing optimum multichannel filters for use with short-period arrays, but these methods are not w idely used. The most commonly used method is delay and sum (DS) follow ed by high-pass filtering. This, however, fails to exploit fully the s patial-filtering properties of arrays, which if used should reduce the need for frequency filtering. To compute spatial filters requires the auto- and cross-correlation of functions of the noise. Here the corre lation functions are specified using noise models rather than the obse rved noise in an interval (the fitting interval) preceding signal onse t. With noise models, it is found that problems of signal distortion a nd ''supergain'' are avoided, supergain being excessive noise reductio n in the fitting interval, with little reduction or even amplification of the noise outside the interval. Using minimum power (MP) filters, which minimize the noise at the output yet pass signals undistorted, i t is shown using data from the 20-element array at Eskdalemuir, Scotla nd, that signal-to-noise improvements of up to 7 can be obtained durin g periods when noise levels are above average, the improvement with si mple delay-and-sum processing for the same noise sample being only 1.7 . The use of noise models allows stable and effective wavenumber filte rs to be rapidly estimated and applied. For those seismograms for whic h the signal and noise after MP processing have obvious differences in predominant frequency, it is shown that optimum frequency filters can sometimes be used to further improve signal-to-noise ratio (S/N) with out significant loss of bandwidth.