Creation of a Production and Feed Simulator from the Phosphate and Niobium Plants in Catal?o Using Geometallurgical Information

摘要

The companies Copebrás and Niobrás of the CMOC International group operate in phosphates and niobium orebodies and they are located in a carbonatitic complex. Currently, geological mapping and mine sampling is used for metallurgical support plus ore type classification as a function of the recovery potential of the apatite and pyrochlore. Different ore types are mixed and piles are formed based on a target composition considering different types of lithologies. For each pile formed, a table is presented that indicates the content of the main elements, the characterization data and percentage of each lithology that forms part of the blend. Even with this information, it was not possible to estimate the plants feed capability and to estimate the plants production. A characterization of the ore types, differently classified mainly by mineralogical contents and lithological description, present in the mine was made to determine the main characteristics of each type and their specific impact on the industrial process. Each type collected the ore types were defined based on the geological map and for each ore type, a mount of 30 samples for chemical analysis, X-ray diffraction and SEM analysis to recognize the chemical and mineralogical composition. Then, these same geological samples were submitted to metallurgical tests to check the individual process behaviour and categorize the best ore types to feed the plants. A mathematical equation was created, based on the geology and the metallurgical characteristic of the stockpile, to estimate the feed and the production of the plants. The result was a correlation of 93 to 95 % through the estimated feed and production simulation with the real plants feed and production for the phosphates plants considering the first 2018 twenty stockpiles. This information enabled a better blend configuration and greater visibility of the feed and production potential for the plants. As consequence, there were improvements in information and predictability the process.