Original scientific paper
https://doi.org/10.17794/rgn.2018.2.5
CHARACTERIZATION OF METAL GRADES IN A STOCKPILE OF AN IRON MINE (CASE STUDY- CHOGHART IRON MINE, IRAN)
Sara Kasmaee
; Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, via Terracini 28, 40131 Bologna, Italy; Research fellow
Francesco Tinti
; Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, via Terracini 28, 40131 Bologna, Italy; Junior Assistant Professor
Roberto Bruno
; Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, via Terracini 28, 40131 Bologna, Italy; Associate Professor
Abstract
In any mining operation due to the cut-off grade (economic criteria), materials classify into the ore and waste. The material with grade equal to or higher than the cut-off grade is considered as ore and the material with grade less than the cut-off grade is transported as wastes to the waste dumps. However, because of increasing metal demand, depleting of in situ ore reserves and so the reduction of cut-off grades for many metals, the mentioned waste dumps were considered as valuable ore reserves named stockpiles. In this paper, multivariate geostatistics was used to estimate the iron grades of two stockpiles following the sequential of piling procedures from the main source - the ore deposit - to the piling field. One stockpile is characterized by phosphorous concentration ((P %) > 0.6 %), while the other by iron concentration ((Fe %)< 50%). Since economic and physical constraints made sampling physically and economically problematic, the grade distribution and variability were estimated on the basis of primary blast-hole data from the main ore body and the mine’s long-term planning policy. A geostatistical model was applied to the excavated part of the iron deposit and the stockpile, by reconstructing ore selection, haulage and piling method. Results were validated through spatial variability of iron and phosphorous concentrations by comparing grade variability (Fe and P) with mining and pilling units. This methodology allows characterizing the iron grades within stockpiles without any extra sampling.
Keywords
Spatial variability; Linear co-regionalisation model (LMC); Co-kriging (CK); Stockpile
Hrčak ID:
194085
URI
Publication date:
23.2.2018.
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