Classification of Seismic Events Accompanying Mine Blasting

SEISMIC INSTRUMENTS(2023)

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摘要
The article presents a new method of classifying acoustic and microseismic emission (KLASI-k), which analyzes waveform parameters (the rise time amplitude RA , average frequency AF , and the waveform index WI ). The method is based on k -means clustering, which makes it possible to separate subsets of events differing in scaled seismic energy (the ratio of emitted seismic energy to released seismic moment) and source duration. In classifying seismic events, there is the fundamental possibility of using the source parameters (seismic energy E s , seismic moment M 0 , and corner frequency f 0 ) as the features of the KLASI-k algorithm. Good correspondence is observed between the classified subsets of events in the transition from waveform parameters { RA , AF , WI } to source parameters { E s , M 0 , f 0 }. The KLASI-k method was applied to the data on mining seismicity induced by two ripple-fired blasts in the Gubkin Mine of the KMAruda Mining Enterprise at the Korobkovskoe iron ore deposit. The analyzed catalogs include 77 microevents recorded after the blast on July 6, 2019 and 259 microevents after the blast on October 24, 2020. Applying the KLASI-k method has made it possible to separate two subsets in the seismic catalogs. The events in the first subset show a scaled seismic energy ( E s / M 0 ) higher than 10 –7 J/(N m), while those in the second subset, lower than 10 –7 J/(N m). The first type of events have a smaller source duration than those of the second type; the released seismic moment is the same.
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关键词
induced seismicity,source parameters,algorithm k-means,scaling
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