Automatic identification model of micro-earthquakes and blasting events in Laohutai coal mine based on the measurement of source parameter difference

Chen Dong, Paul Martin Mai

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The micro-seismic signal of coal mine is obviously affected by blasting signal, which seriously affects the identification accuracy of micro-seismic signal. For this purpose, automated identification and discrimination methods exist to monitor seismicity occurrence. In this study, seismic source properties of blasting events and micro-earthquakes in the Laohutai coal mine are quantified to more accurately distinguish between these two types of events and to investigate potential physical differences between them. Besides examining the space-time evolution of micro-earthquakes in the Laohutai coal mine, source parameters of blasting events and micro-earthquakes (corner frequency f0; spectral level Ω0; seismic moment M0; moment magnitude Mw; source radius R; stress drop △σ; apparent stress σa, radiated seismic energy E) are determined and scaling relationships between them are investigated. Our results show that the number of micro-earthquakes is closely related to the mining activity. Source-spectral characteristics of blasting events are well described by the Brune omega-square model and follow in general the classical scaling relations (i.e. increasing seismic moment with decreasing corner frequency), like the source-spectral characteristics of micro-earthquakes. Importantly, for events of same magnitude, corner frequency and stress drop of blasting events are larger than for micro-earthquakes. This observation helps to improve automatic identification and discrimination of micro-seismic and blast events, thereby providing important information for (real-time) seismic hazard monitoring and risk management.
Original languageEnglish (US)
Pages (from-to)109883
JournalMeasurement
DOIs
StatePublished - Jul 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-07-29
Acknowledged KAUST grant number(s): BAS/1/1339-01-01
Acknowledgements: The research presented in this article is supported by King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia, by grant BAS/1/1339-01-01, and carried out during C a visiting-student internship of C.D.

ASJC Scopus subject areas

  • Applied Mathematics
  • Condensed Matter Physics

Fingerprint

Dive into the research topics of 'Automatic identification model of micro-earthquakes and blasting events in Laohutai coal mine based on the measurement of source parameter difference'. Together they form a unique fingerprint.

Cite this