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<p>The advancement of intelligent mining in open-pit operations has imposed higher demands on geological transparency, aiming to provide a robust foundation for intelligent drilling and charging. In this study, a linear array of 120 nodal seismometers was deployed along the surfaces of the C8 and C9 platforms at Fenghuang Mountain to investigate cavities within the rock mass and prevent improper intelligent charging. The seismometers were 1 m apart along measurement lines, with a 2-m spacing between lines, and the monitoring time for each line was set at 2 h. This deployment was paired with spatial autocorrelation and station autocorrelation to analyze ambient noise seismic data and image the velocity and structure within the rock mass. The results demonstrate that the locations and sizes of cavities or loose structures can be accurately identified at the prepared excavation site. Compared with traditional geological exploration methods for open-pit mines, the approach in this study offers higher accuracy, greater efficiency, reduced labor intensity, and insensitivity to water conditions. Ambient noise seismic imaging for detecting adverse geological conditions in open-pit mines provides critical insights and references for intelligent mining advancements.</p>

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Transparent geological exploration for intelligent and safe open-pit mining based on ambient noise seismic imaging

  • 期刊论文

  • 发表日期：

    2025年2月7日

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  • Ping-Feng Li,
  • Qiang-Qiang Zheng,
  • Ying Xu,
  • Di Wei,
  • Jia-wei Qian,
  • Bao-Ji Yang

摘要

The advancement of intelligent mining in open-pit operations has imposed higher demands on geological transparency, aiming to provide a robust foundation for intelligent drilling and charging. In this study, a linear array of 120 nodal seismometers was deployed along the surfaces of the C8 and C9 platforms at Fenghuang Mountain to investigate cavities within the rock mass and prevent improper intelligent charging. The seismometers were 1 m apart along measurement lines, with a 2-m spacing between lines, and the monitoring time for each line was set at 2 h. This deployment was paired with spatial autocorrelation and station autocorrelation to analyze ambient noise seismic data and image the velocity and structure within the rock mass. The results demonstrate that the locations and sizes of cavities or loose structures can be accurately identified at the prepared excavation site. Compared with traditional geological exploration methods for open-pit mines, the approach in this study offers higher accuracy, greater efficiency, reduced labor intensity, and insensitivity to water conditions. Ambient noise seismic imaging for detecting adverse geological conditions in open-pit mines provides critical insights and references for intelligent mining advancements.