Abstract

Currently, the transmitting channel wave technique mainly uses the attenuation coefficient of the channel wave total energy to explore the geological structure of the coal seam face. In the case of weak geophone coupling and intense geological anomaly, the channel wave energy will be attenuated severely, which significantly affects the stability and accuracy of the result. The Q value of the coal channel is a critical parameter to evaluate the energy attenuation characteristics of the channel wave. The Q value is typically estimated by using the attenuation coefficient of the body wave, but the special coal channel model hinders the estimation of the Q value of the coal seam. According to the linear attenuation characteristics of the centroid frequency of the transmitting channel wave, a new method was proposed to assess the quality factor (Q) of the coal channel by using the centroid frequency change of the channel wave signal. The expected frequency was calculated as its centroid frequency according to the energy ratio of each frequency point through the spectral analysis of the channel wave signal. Combined with the transmission tomography technology, the imaging of the coal seam face based on the transmitting channel wave Q value was established. According to the sudden change of the Q value of the coal channel near the geological structure of the coal seam face, a geological interpretation method based on the abnormal Q value was proposed. The two-dimensional numerical simulation demonstrated that the centroid frequency of the transmitting channel wave signal decayed linearly with the propagation distance and the geological structure increased the frequency shift. Furthermore, three-dimensional numerical simulation validated the feasibility and effectiveness of the Q value inversion method. Field Experimental results showed that the algorithm exhibited improved stability and accuracy. This work proposed a novel frequency-domain inversion method of the transmitting channel wave that directly uses the frequency shift characteristics of the channel wave to estimate the Q value of the coal channel, which offers a new strategy in the data processing of channel wave.

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