1887

Abstract

Summary

Identification and detection of the microseismic events is significant issue in source locations and source mechanism analysis. And due to the large amount of microseismic records and need for rapid field analysis and monitoring, the automatic algorithms are more indispensable. In this study, we introduce an effective method for the identification and detecting of the microseismic events by judging if there is a P-wave phase in local segment from single three-component microseismic records. The new judging algorithm mainly contains following key steps: 1), transform the waveform time series into time-varying spectral representations; 2), detect the similarity of the frequency content in the time-frequency domain using the phase-only correlation function; 3), identify the P-phase by the combination analysis of three-component records. The proposed algorithm is compared to the traditional 1D crosscorrelation of the raw waveform, with a synthetic microseismic datasets and a real field-recorded datasets. The results show that the new algorithm is stable to distinguish the similar waveforms and dissimilar waveforms even for low SNR and emergent events, which is meaningful to select the microseismic events out of a large amount of records accurately and rapidly. It can be applied to some other geophysical analyses based on the waveform data.

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/content/papers/10.3997/2214-4609.201600721
2016-05-30
2024-03-29
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References

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