LI Xiaobin, YANG Zhenwei, YUN Meihou, et al. Four-line staggered grid survey layout of mine micro-seismic and surface wave velocity structure imaging[J]. Journal of China Coal Society, 2019, 44(S2): 643-649. DOI: 10.13225/j.cnki.jccs.2019.1132
Citation: LI Xiaobin, YANG Zhenwei, YUN Meihou, et al. Four-line staggered grid survey layout of mine micro-seismic and surface wave velocity structure imaging[J]. Journal of China Coal Society, 2019, 44(S2): 643-649. DOI: 10.13225/j.cnki.jccs.2019.1132

Four-line staggered grid survey layout of mine micro-seismic and surface wave velocity structure imaging

  • Micro-seismic monitoring technique is an important mean for the safety of coal mine.Both mining activity and mechanical vibration are regarded as sources which take plenty geological information of coal and rock medium through seismic waves traveling time and space.During the seismic wave propagation, surface wave signals have the characteristics of strong energy, low frequency, slow attenuation and easy to collect.Because of the time and space randomness of mine micro-seismic events and mining activities, the spatial autocorrelation method is suitable for extracting surface wave information from complex ambient noise.This paper introduces a four-wire staggered grid survey layout for the mine micro-seismic monitoring based on the theory of spatial autocorrelation method.Firstly, the theoretical methods includes extracting the circular observation data set, narrowband filtering, calculating the spatial autocorrelation coefficient, calculating the phase velocity, fitting the phase velocity dispersion curve and calculating the velocity structure of coal seam etc.Secondly, some field data are collected from the scattered signals of interference such as micro-seismic events and mining activities, and each data segment is processed by narrowband filtering with different center frequencies to acquire each frequency component respectively.Thirdly, the spatial autocorrelation coefficients between the central observation point and the circular observation point were calculated for each frequency component.Finally, the dispersion curve of surface wave phase velocity is obtained by spatial autocorrelation function and Bessel function.The experimental results showed that the surface wave velocity imaging has a good consistency with the thickness distribution of coal seam, which can better reflect the velocity structure of coal mine working surface.Since the surface wave is not affected by the shielding effect of the high-speed layer, it has a strong resolution ability to the low-speed layer such as coal seam, which can identify the low-speed layer and determine the boundary of the velocity anomaly, such as coal seam broken belt, goaf, and collapse column.By means of real-time record micro-seismic signals of mining rock fracture and ambient noise with mine micro-seismic four-wire staggered grid survey layout, it can extract effective information and invert the velocity geophysical characteristics of surrounding rock carried by micro-seismic propagation which is of significance to ensuring the safety of mining operations.
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