Automatic seismic wave detection and autoregressive model method

Abstract

The problem of automatic detection of seismic waves by large telemetered seismic networks such as the Mexican Continental Aperture Seismic Network (RESMAC), is extended here to include determination of seismic first-arrival and S-phase-arrival times. A short general outline of the detection problem background and a small introduction to the autoregressive model (AR) concept are presented. Several automatic detection algorithms were implemented and compared with a newly developed autoregressive algorithm. Careful consideration of the advantages and disadvantages of each method determined that a mixed detection scheme is optimal and suitable for RESMAC. A few examples are shown that illustrate the relative performances of the methods tried here. The proposed detection scheme has the following characteristics: (a) First-arrival detection, based on a simple (average of squared input) characteristic function, and a trigger criterion that uses as a distortion measure the long-average-to-short-average ratio of the characteristic function, checked using a duration criterion; (b) use of two threshold values, one for triggering, and another for beginning the backward search for the phase arrival time; (c) use of the autoregressive model (AR) method, with the Itakura-Saito distortion measure, for S-phase detection, checked using both duration and amplitude criteria; and (d) characterization of the reliability of the determinations for their subsequent use in automatic location programs, alarms, etc. The automatic detection scheme has proved effective.