Navoi State University of Mining and Technologies, Navoi, Uzbekistan

Sh. T. Tadzhiev, PhD, Associate Professor, sh_tadjiev@mail.ru

Navoi Mining and Metallurgical Company, Navoi, Uzbekistan

Sh. M. Sadinov, Chief Surveyor

Deep open pit mining involves high geomechanical risks due to deformation of open pit slopes, which poses a serious threat to mine personnel, equipment and operational stability. The Muruntau Open Pit Mine, being one of the largest gold deposits in the world, operates in difficult geological, tectonic and geodynamic conditions which drastically affect rock mass stability. The aim of this research is to substantiate efficiency of automated slope deformation monitoring at the Muruntau Mine using the up-to-date robotic surveying tools. The integrated analysis of the nature, scale and dynamics of deformation processes in time and space within the limits of the open pit field is performed. Using the data on geological structure, physical and mechanical properties of rocks, hydrogeological conditions and earlier recorded deformations, the zoning of the open pit wall slope was carried out with the identification of stable, nominally stable and unstable sites. It is found that deformations develop most intensively nearby influence zones of regional faults and complex structural components of rock mass. The instrumental observations were carried out using electronic tachometer Leica TS06 and robotic tachometer Leica TM50i included in automated monitoring system GeoMoS. The Automatic Target Recognition technology, with a range to 3 km and a land corner of 0.5", ensured continuous and high-precision recording of displacements at checkpoints in three dimensions. The obtained quantitative characteristics of horizontal and vertical displacement velocities can help detect stages of active deformations and assess their hazard. It is shown that introduction of automated geodynamic monitoring improves the operational efficiency and reliability of observations, reduces the human factor impact and the operating cost, and allows generating a firm informational foundation for the slope stability prediction and preventive decision-making toward enhanced safety and sustainability of mining operations.

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