Mine Fracturing Monitoring Analysis Based on High-Precision Distributed Wireless Microseismic Acquisition Station
A large number of shallow fossil fuel energy sources have been exhausted, including coal, oil, natural gas, and other non-renewable energy sources with rapid industrial development. The mining of fossil fuel energy has gradually shifted to the deep layers of the stratum, where safety is more difficu...
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Veröffentlicht in: | IEEE access 2019, Vol.7, p.147215-147223 |
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Sprache: | eng |
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Zusammenfassung: | A large number of shallow fossil fuel energy sources have been exhausted, including coal, oil, natural gas, and other non-renewable energy sources with rapid industrial development. The mining of fossil fuel energy has gradually shifted to the deep layers of the stratum, where safety is more difficult to guarantee. As a result, the development of a data acquisition system that can be used for microseismic monitoring and disaster prediction is imminent. In this study, in order to complete the design of a high-precision acquisition circuit, main control circuit, and other hardware circuits, the authors developed a set of high-precision distributed wireless microseismic acquisition stations, which was combined with three-component geophones to complete a microseismic monitoring system. This monitoring system was then verified through on-site work during the construction of a coal mine in China. This paper focuses on a detailed analysis of the data collected by the acquisition stations. Firstly, twelve sets of acquisition stations were used to conduct fixed-location blasting tests of the mine, which yielded good test results. Secondly, an analysis of microseismic monitoring data obtained during deep-well fracturing was carried out, and pre-fracturing static monitoring, carbon dioxide monitoring, fracturing monitoring, and post-fracturing static monitoring were also completed. This paper provides a detailed introduction to fracturing monitoring data of mines, combining discussions on the other three types of mine monitoring to reach relevant conclusions. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2019.2946443 |