Real time seismic event detection and discrimination using multi-channel data

The authors present an approach to the detection and discrimination of seismic events using multi-channel data. The seismic detection algorithm consists of an adaptive correlation enhancer and a sliding window detector that make the detector insensitive to changes in the background noise level. This algorithm is capable of detecting extremely weak signals of signal-to-noise ratios (SNRs) as low as -10 dB while keeping false alarms down to a minimum. The discrimination algorithm uses the adaptive correlation enhancer´s weights as input discriminants to a neural net. Preliminary test results indicate that this algorithm can successfully discriminate between nuclear test events and earthquakes. The results presented here were obtained by exercising the algorithm on field-acquired data supplied by Sandia National Laboratories