Stochastic simulation applied to zinc mineral resources classification at vazante mine

• Grant number: 18/17022-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2018
• End date: October 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Marcelo Monteiro da Rocha
• Grantee: Laíza Maietto Lauriano
• Host Institution: Instituto de Geociências (IGC). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The evaluation and classification of mineral resources and reserves are important steps in the development of any mining enterprise. These steps associated with the declaration of mineral resources and reserves should be based on the principles of transparency, materiality and competence. In Brazil and in the world these concepts find definitions in guides linked to committees and committees such as the CBRR (Brazilian Commission of Resources and Reserves) and CRISCO (Committe for Mineral Reserves International Reporting Standard). In relation to the classification of resources and mineral reserves, the classes should be defined based on the degree of confidence that the reporting company has in the information used in the evaluation and classification. This degree of confidence relates to the quantity and quality of the available information and is often quantified through the indices and uncertainty associated with the evaluation. In this sense, it is intended to classify the zinc mineral resources of the Vazante Mine linked to the Nexa Resouces Company by quantifying the uncertainties calculated by the mean confidence interval derived from the Gaussian sequential simulation results, a geostatistical stochastic simulation technique.