1 research outputs found
MINERAL RESOURCE ASSESSMENT OF BATTERY CRITICAL ELEMENTS IN A COPPER PORPHYRY DEPOSIT
Elements for the construction of batteries are currently experiencing growing demand due to the need to create lithium-ion batteries in electronics, electric car engines and other vehicles as well as energy distribution and storage systems against the background of the green development of the economies of countries. The increased interest for these elements causes a risk of supply in recent years, which calls these elements critical. The combined use of continuous and categorical variables will reveal some patterns of the distribution of elements, as well as to improve the allocation of hidden geological domains. Therefore, the mineral resource assessment and modeling of orebody is containing these elements, with the introduction of categorical variables such as rock type, alteration and mineralization zone into the algorithm is important research not only for the mining industry, but also for the development of global green technologies. This paper is devoted to the identification of an algorithm based on machine learning and geostatistics for assessing mineral resources of the abovementioned critical battery elements (i.e., Co, Cu, Li, Mo, Ni) over real copper-porphyry deposit, where their local and spatial distributions are being adjusted by geological properties such as mineralization, rock types, and alterations. The results of this study can show whether copper-porphyry deposits are suitable as the main source of critical elements. Moreover, the outcome of comparing several techniques for domaining and simulation steps of the algorithm will make it possible to identify the most suitable one, which will be also the criterion for results analysis