Application of Bayesian method for mining-induced tremors: A case study of the Xinjulong coal mine in China

Abstract

Mining-induced tremor is a dynamic phenomenon occurring during the fracturing or slipping of rock and coal mass in coal mines, and the tremor mechanism is one of the key problems in the field of rockburst. The Bayesian inversion method can more accurately analyse the source rupture type under the premise of considering waveform data and model errors. First, we added different noise levels to the waveform and determined filtering parameters based on the spectrum. The rationality of the Bayesian inversion was verified by observing the focal mechanism solution. Finally, a total of fourteen mining-induced tremors were selected, and the parameters of the moment tensor (MT), type of rupture, and fault plane solutions were obtained. The results demonstrate that (1) the tremor events in the roof are mainly tensile/shear failure, and compression failure mainly occurs in the coal seam. (2) Events on the floor are closely related to gob and mining activities. (3) The rupture form of the events near the tectonic region is more complex, and the fault plane solutions (strike, dip, and slip) were obtained by MT conversion. (4) The relation between rockbursts and mining-induced tremors is discussed by analysing events 1# and 14# that occurred in the Xinjulong coal mine. These research findings can provide a reference for the analysis of source parameters and rupture forms of mining-induced tremors.