Luis Eduardo de Souza

Impacto do agrupamento preferencial de amostras na inferência estatística: aplicações em mineração

Preferential sampling or clustering is frequently found in mining and earth sciences applications. Reliable statistics for a population are obtained when representative samples are available. Such representativeness can be achieved by a proper sample design covering evenly the area. This paper investigates two declustering methods to obtain unbiased statistics where clustered samples are available, namely the polygonal and the cell-declustering method. The impact of clustering is analysed for two different datasets. Polygonal method proved to be simpler as it provides an unique solution easily to be understood by the user. In relation to the cell-declustering method, a methodology to calculate the statistical entropy was implemented to help in determining the most appropriate cell size. The two methods lead to similar declustered statistics. However the final statistics showed a large difference when compared to the statistics obtained for the clustered dataset.

Estimativa de incerteza na classificação de recursos minerais por simulação geoestatística

O sucesso de um novo empreendimento de mineracao depende muito da recuperacao de tonelagens e teores estimados, usando informacoes obtidas durante campanhas de exploracao mineral. Essas estimativas deveriam ser capazes de alertar para possiveis altos riscos na classificacao de recursos, possivelmente construidas usando intervalos de confianca associados com cada estimativa. As categorias de recursos minerais sao definidas de acordo com o espacamento entre amostras e com o grau de confiabilidade em cada classe de recurso, a ser medida, indicada e inferida. Varios sistemas de classificacao estao disponiveis, mas, para esse estudo, o sistema JORC (Joint Organisation Reserves Committee) foi utilizado. Esse artigo propoe uma metodologia para verificar a incerteza associada com volumes e tonelagens relacionados no inventario de um deposito mineral. Para ilustrar a metodologia, um deposito de carvao no sul do Brasil foi utilizado. Nesse deposito, estavam disponiveis 340 furos de sondagem com dados de espessura e 236 com informacoes sobre densidade. Os resultados forneceram ferramentas para medida da incerteza baseadas em um procedimento com embasamento teorico.

Alternativas para classificação de recursos minerais - métodos geoestatísticos tradicionais

The difficulty in quantifying the degree of uncertainty associated with the estimation of mineral resources has led to the creation of a large suite of methodologies, terms, and definitions, with almost every mining company having its own set of standards. It is intuitively known that traditional methods used to evaluate resources do not take into account the spatial continuity of the grades, and even some approaches based on geostatistical methods are unable to provide a measure of the error associated with their estimates. This article aims at developing a methodology for either quantitative or qualitative analysis of mineral resource estimation through uncertainty incorporation and for the correct definition of the associated risk or error. A comprehensive study about each technique was conducted allowing a comparison among the parameters affecting mineral inventory assessment. A case study was conducted with a typical iron ore deposit data set, and the results showed the specific limitations of each classification system and their influence in selecting key parameters. The developed software was used, and the results always demonstrated the empirical nature of the traditional methods based on subjective choices.

Distribuição espacial de concreções piríticas e sua influência na performance de conjuntos mecanizados em mina de carvão

Mine planning in the coal industry is traditionally developed using a geological model built by discretising relevant geological and engineering attributes into small blocks. Production scheduling is planned based on a 3D geological model representing important features, such as coal cumulation, coal recovery at the plant and other geochemical properties relevant for environmental characterisation. In coal operations using continuous mining systems, rock mechanics properties are deemed relevant as these properties directly influence equipment performance. Rock mass resistance and its abrasiveness impact directly the system productivity. Operational difficulties may arise when using continuous coal cutters within zones containing high concentrations of pyrite concretions. In extreme situations, high pyrite concentration makes unpractical the use of continuous systems with severe costs penalties if not predicted in advance. This paper presents a methodology to forecast pyrite spatial distribution based on kriging. The results proved to be appropriate based on reconciliation obtained comparing pyrite percentage versus bit consumption. A case study in major coal deposit illustrates the methodology.