IMPROVING ORE QUALITY MANAGEMENT IN DEEP POLYMETALLIC DEPOSITS
DOI:
https://doi.org/10.17605/Keywords:
Deep mine, polymetallic ore, ore quality, grade control, geometallurgy, liquefaction, sampling, mine-to-mill, logistics, block model, ore mixing, underground miningAbstract
The article analyzes the problem of ore quality management in underground mining of deep polymetallic deposits from a geological, technological, geomechanical and geometallurgical point of view. The analysis focuses on the fact that ore quality is a complex indicator determined not only by the metal content, but also by the mineralogical composition of the ore, textural properties, harmful impurities, degree of dilution, the state of mixing in logistics processes and technological response to enrichment. In the process of mining in deep layers, high rock pressure, instability of stope walls, excessive destruction after blasting, mixing of ore with waste rock, reduced representativeness of samples and time delays in the mine-factory chain complicate ore quality management. The article argues that the need to improve ore quality management requires geological domaining, customized sampling protocols, QA/QC system, geotechnical control of liquefaction, near-real-time monitoring, identification of ore flow along logistics, geometallurgical model, and the introduction of a continuously updated grade-control model.
References
[1] Dominy S.C., Glass H.J., O’Connor L., Lam C.K., Purevgerel S., Minnitt R.C.A. Integrating the Theory of Sampling into Underground Mine Grade Control Strategies // Minerals. – 2018. – Vol. 8, No. 6. – Art. 232. – DOI: 10.3390/min8060232.
[2] Dominy S.C., Platten I.M., Xie Y., Minnitt R.C.A. Underground grade control protocol design: case study from the Liphichi gold project, Larecaja, Bolivia // Applied Earth Science (Transactions of the Institutions of Mining and Metallurgy, Section B). – 2010. – Vol. 119, No. 4. – P. 205–219. – DOI: 10.1179/1743275811Y.0000000016.
[3] Villaescusa E. Geotechnical design for dilution control in underground mining // Proceedings of the Seventh International Symposium on Mine Planning and Equipment Selection. – Calgary: Balkema, 1998. – P. 141–149.
[4] Xingwana L. Monitoring ore loss and dilution for mine-to-mill integration in deep gold mines: A survey-based investigation // Journal of the Southern African Institute of Mining and Metallurgy. – 2016. – Vol. 116, No. 2. – P. 149–160. – DOI: 10.17159/2411-9717/2016/v116n2a6.
[5] Bardzinski P., Jurdziak L., Kawalec W., Krol R. Copper Ore Quality Tracking in a Belt Conveyor System Using Simulation Tools // Natural Resources Research. – 2020. – Vol. 29. – P. 1031–1040. – DOI: 10.1007/s11053-019-09493-6.
[6] Prior-Arce A., Benndorf J. Resource Model Updating for Underground Mining Production Settings // REAL TIME MINING – Conference on Innovation on Raw Material Extraction. – Amsterdam, 2017. – P. 130–140.
[7] Tiu G., Ghorbani Y., Jansson N., Wanhainen C., Bolin N.-J. Quantifying the variability of a complex ore using geometallurgical domains // Minerals Engineering. – 2023. – Vol. 203. – Art. 108323. – DOI: 10.1016/j.mineng.2023.108323.
