A Spectrogram‐Based Method of Rg Detection for Explosion Monitoring

The detection of the high-frequency fundamental-mode Rayleigh-wave Rg is important for explosion monitoring efforts because it indicates a shallow source, which is most often man-made. We developed an automated Rg detector that successfully identifies Rg using the spectrogram of the seismic signal to find peaks in the characteristic Rg frequency band. We tested the detector using a network of over 200 seismometers in Wyoming, which recorded dozens of nearby coal-mining blasts and active-source tamped borehole shots. The detector finds peaks in the summed spectrogram amplitudes from 0.4 to 0.8 Hz for mining blasts and from 0.8 to 1.5 Hz for borehole shots. We achieved successful Rg detection of mining blasts across the entire array for the largest blasts, though smaller blasts had less success at distant stations, due to low signal amplitude. Similarly, Rg detection from borehole shots was successful at distances <50 km but was not common at farther stations. We then developed a method to estimate the probability that a null detection was indicative of a deep source and not an explosion with low signal-to-noise ratio. Finally, we compared our method with an existing Rg detection method based on finding retrograde particle motion, typical of Rg, in signal coming from the known source-receiver back azimuth. In our application, the detector worked well for more distant stations but failed at stations within the same basin as the source, where Rg has prograde particle motion. The two detectors are fundamentally different; the new detector is easier to automate but depends on Rg having larger amplitude than the pre-Rg time window, whereas the existing detector triggers based on the particle motion and the direction of arrival, independent of the amplitude. The new method, perhaps in conjunction with the existing method, can offer increased monitoring capability and higher confidence when detecting Rg.