Study on transmitted channel wave-based, horizontal multilayer 3-D velocity model inversion and quantitative coalbed thi
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RESEARCH ARTICLE - APPLIED GEOPHYSICS
Study on transmitted channel wave‑based, horizontal multilayer 3‑D velocity model inversion and quantitative coalbed thickness detection method Zean Hu1,2 · Pingsong Zhang1,2 · Guangzhong Ji1,2 · Xiaoyun Su3 Received: 19 November 2019 / Accepted: 8 October 2020 © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2020
Abstract Most methods using transmitted channel wave (TCW) prospecting to quantitatively detect the thickness of coal seams based on the statistic relationship of group velocity in certain wave bands to the thickness of coal seams cannot be applied universally. To establish a universal applicable method, we first obtained the theoretical dispersion curve of TCW using the generalized reflection–transmission coefficient method and the 1-D horizontal multilayer velocity model, performed iteratively match calculation using the inversion model and the genetic algorithm and analyzed the distributive characteristics of shear wave velocity of coal and rock formations at a certain depth. We then obtained the 3-D velocity images of the coal seam working face based on TCW data using the 3-D back-projection technology. According to the changes of shear wave velocity at the coal–rock interface and the rate of inversion velocity change, we further proposed the quantitative discriminant model for coalbed thickness. Based on the model, we quantitatively interpreted the thickness of the coal seam by computing the depths corresponding to the extremes of the positive and negative rate of the shear wave velocity change and obtained the distribution characteristics of the coal thickness in the working surface. To verify the feasibility and validity of the proposed model for coalbed thickness, we conducted a 3-D physical similarity model experiment and subjected the collected two-component TCW data to inversion calculation and compared the obtained coal seam thickness with the known model parameters. Overall, our study achieved the universal 3-D quantitative detection of coalbed thickness and provided technical supports for intelligentized coalbed mining. Keywords Channel wave dispersion curve · Genetic algorithm · 3-D velocity inversion · Quantitative coalbed thickness detection
Introduction With the rapid development of science and technology, the intelligentized or unmanned coal mining technology has become the main developmental trend of coal mining toward the dual guarantee for coal production and personnel safety * Pingsong Zhang [email protected] 1
State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan, China
2
School of Earth and Environment, Anhui University of Science and Technology, Huainan, China
3
Xi’an Research Institute of China Coal Technology & Engineering Group Corp, Xi’an 710077, China
(Yuan 2017; Peng et al. 2019). The accurate and efficient detection of the thickness of coal seams in the coal mining face can directly guar
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