Mineral Resource Estimation

High grade drill intersects are often a welcome occurrence for a mining company, its shareholders and/or potential investors. They represent the potential for even greater metal content in the deposit. However, from a resource evaluation perspective, they may present complications in generating a realistic resource estimate, by overestimating or underestimating...

Most recent developments in resource estimation have taken place in the following fields: Geological modelling: 3D modelling has become much faster and more accurate, by implementing fast interpolation algorithms within specialised software like Leapfrog, GOCAD, Geomodeller. More traditional mining packages have added implicit modelling to their capabilities (Minesight, Micromine, etc.)...

Classifying coal deposits in recently explored basins to internationally recognised reporting codes requires close attention to data quality and a comprehensive understanding of the geology. The coal basins and sub-basins of the Zambezi coalfield are structurally complex, affected in varying degrees by intrusive bodies, with centimetre scale inter-bedded coal and...

In early 2015, India introduced a set of new mining rules, using the terminologies defined in the UNFC 1997 guideline and the CRIRSCO Template. Since then, mapping the Indian Resource Classification system against the CRIRSCO Template has become extremely important to the Indian and foreign investors. In the recent past,...

After discovering a mineral deposit, delineating the drilling, and developing a geological framework, the next step is usually estimating metal content by quantifying the grade and tonnage of the mineral occurrence. To support mine design and the economic analysis of the project, a geometallurgical model can also be generated by...

Mineral resources are reported in tonnage and grades. While great care is placed on generating a reliable estimate of grade, determining bulk density for resource estimation is often overlooked. Instead, a simple average value of bulk density is used. While this estimate can work for some deposit types, an overly...

Grade domains are often considered, following the modelling of geologic domains, to further control the distribution of grades during resource estimation. This is usually achieved by wireframe modelling on sections displaying grade assays or composites, indicator kriging, and/or implicit modelling using radial basis functions. The latter approach is often facilitated...

Despite the intention to include geological controls during the wireframing phase of the mineral resource estimation process, modelling methodology is sometimes reduced to connecting grade data along trends judged to be geologically valid. This is specifically the case for precious metal vein deposits where the grade distribution is controlled by...

International professional organisations in Australia, Canada, South Africa, USA, UK, Ireland, and many countries in Europe have adopted comparable codes, guidelines, and standards for mineral resource reporting. The definition of a mineral resource usually includes the requirement that “reasonable prospects for economic extraction” exist. This requirement implies a judgment by...