Undiscovered porphyry copper resources in the Urals—A probabilistic mineral resource assessment
A probabilistic mineral resource assessment of metal resources in undiscovered porphyry copper deposits of the Ural Mountains in Russia and Kazakhstan was done using a quantitative form of mineral resource assessment. Permissive tracts were delineated on the basis of mapped and inferred subsurface distributions of igneous rocks assigned to tectonic zones that include magmatic arcs where the occurrence of porphyry copper deposits within 1 km of the Earth's surface are possible. These permissive tracts outline four north-south trending volcano-plutonic belts in major structural zones of the Urals. From west to east, these include permissive lithologies for porphyry copper deposits associated with Paleozoic subduction-related island-arc complexes preserved in the Tagil and Magnitogorsk arcs, Paleozoic island-arc fragments and associated tonalite-granodiorite intrusions in the East Uralian zone, and Carboniferous continental-margin arcs developed on the Kazakh craton in the Transuralian zone. The tracts range from about 50,000 to 130,000 km2 in area. The Urals host 8 known porphyry copper deposits with total identified resources of about 6.4 million metric tons of copper, at least 20 additional porphyry copper prospect areas, and numerous copper-bearing skarns and copper occurrences.
Probabilistic estimates predict a mean of 22 undiscovered porphyry copper deposits within the four permissive tracts delineated in the Urals. Combining estimates with established grade and tonnage models predicts a mean of 82 million metric tons of undiscovered copper. Application of an economic filter suggests that about half of that amount could be economically recoverable based on assumed depth distributions, availability of infrastructure, recovery rates, current metals prices, and investment environment.
|Undiscovered porphyry copper resources in the Urals—A probabilistic mineral resource assessment
|Ore Geology Reviews
|Eastern Mineral and Environmental Resources Science Center
|Google Analytic Metrics