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An automatic means to discriminate between earthquakes and quarry blasts

INSTITUTE OF GEOPHYSICS AND PLANETARY PHYSICS SCRIPPS INSTITUTION OF OCEANOGRAPHY, LA JOLLA, CALIFORNIA 92093

Abstract

In this article we discuss our efforts to use the NORESS array to discriminate between regional earthquakes and ripple-fired quarry blasts (events that involve a number of subexplosions closely grouped in space and time). The method we describe is an extension of the time versus frequency "pattern-based" discriminant proposed by Hedlin et al. (1989b). At the heart of the discriminant is the observation that ripple-fired events tend to give rise to coda dominated by prominent spectral features that are independent of time and periodic in frequency. This spectral character is generally absent from the coda produced by earthquakes and "single-event" explosions. The discriminant originally proposed by Hedlin et al. (1989b) used data collected at 250 sec^–1 by single sensors in the 1987 NRDC network in Kazakhstan, U.S.S.R. We have found that despite the relatively low digitization rate provide by the NORESS array (40 sec^–1) we have had good success in our efforts to discriminate between earthquakes and quarry blasts by stacking all vertical array channels to improve signal-to-noise ratios.

We describe our efforts to automate the method, so that visual pattern recognition is not required, and to make it less susceptible to spurious time-independent spectral features not originating at the source. In essence, we compute a Fourier transform of the time-frequency matrix and examine the power levels representing energy that is periodic in frequency and independent of time. Since a double Fourier transform is involved, our method can be considered as an extension of "cepstral" analysis (Tribolet, 1979). We have found, however, that our approach is superior since it is cognizant of the time independence of the spectral features of interest. We use earthquakes to define what cepstral power is to be expected in the absence of ripple firing and search for events that violate this limit. The assessment of the likelihood that ripple firing occurred at the source is made automatically by the computer and is based on the extent to which the limit is violated.