GEOPHYSICAL RESEARCH, 2019, vol. 20, no. 1, pp. 38-51.

UDC 550.34+005

Abstract  References   Full text (in Russian)


R.Yu. Zamaraev, S.E. Popov

Institute of Computational Technologies SB RAS, Novosibirsk, Russia

Abstract. The seismic event classification algorithm based on the preliminary transformations of signals into the entropy model is presented. It allows summarizing the information about the waveform features from three directions of measurements, averaging and comparing these features. The events’ characteristic functions based on entropy model are calculated for estimating the similarity of the seismic field in the calculation window to templates of explosions, earthquakes and abstract templates with given properties. Templates for explosions and earthquakes are obtained by averaging characteristic functions of the sets of corresponding events for a given station in a given region. Abstract templates are calculated using the envelope function of the seismic field’s entropy model, which is a sum of entropy models of signals in three dimensions. The similarity of the sample characteristic function to premade templates is estimated using a set of distance measures between one-dimensional vectors such as correlation distance, etc. Conclusion is issued on the basis of the rating voting system according to the amount of minimum distances, which is used in. An example of a seismic events classification in the Kemerovo region territory is given. The algorithm is oriented to regional networks and seismic monitoring systems and provides a fully automated and fast process for detecting and classifying the declared regional seismic events.

Keywords: regional seismic events, industrial blasts, event detection, rapid automatic classification, entropy models, events' templates, similarity estimations.


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