Research on microseismic event imaging based on waveform clustering analysis

Li Dewei; Yang Ruizhao; Meng Lingbin

doi:10.19606/j.cnki.jmst.2022.01.003

Volume 7 Issue 1

Feb. 2022

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Li Dewei, Yang Ruizhao, Meng Lingbin. Research on microseismic event imaging based on waveform clustering analysis[J]. Journal of Mining Science and Technology, 2022, 7(1): 26-33. doi: 10.19606/j.cnki.jmst.2022.01.003

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Research on microseismic event imaging based on waveform clustering analysis

doi: 10.19606/j.cnki.jmst.2022.01.003

College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China

Received Date: 2021-07-21
Rev Recd Date: 2021-10-12
Publish Date: 2022-02-01

Abstract

Abstract

The quality of microseismic data greatly affects the accuracy of the source location results, especially in surface microseismic data where the first arrivals of P waves and S waves are not obvious or the low signal-to-noise ratio signals are difficult to identify.Secondly, due to the different focal mechanisms that induce microseismic, the signal characteristics received by different geophones are not the same.All of these factors have a certain impact on the accurate location of microseismic events.This paper proposes a method for selecting microseismic data based on cluster analysis to improve the imaging quality of microseismic event amplitude superposition locating.First, the Euclidean distance between the trace channels is calculated by cluster analysis, and the trace channels with larger and smaller distances are removed through the clustering graph, that is, trace channels with insignificant signal characteristics or severe noise interference are removed.Second, the cross-correlation calculation is performed on the signals of each channel, the trace channels with strong signal characteristic correlation being extracted, and those with unobvious P wave characteristics removed.Finally, the screened trace channels are superimposed and located with amplitude superposition.The comparison of the locating results with the original trace channels shows that the locating effect of the microseismic cluster analysis is more focused, the location of the focal point is clearer, and the locating results are significantly improved.
- microseismic,
- cluster analysis,
- waveform classification,
- data denoising,
- events location

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Research on microseismic event imaging based on waveform clustering analysis

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