Geostatistical modelling of geometallurgical classes

The Australasian Institute of Mining and Metallurgy
W Patton U Mueller H Talebi I Minniakhmetov
Organization:
The Australasian Institute of Mining and Metallurgy
Pages:
23
File Size:
2824 KB
Publication Date:
Mar 22, 2022

Abstract

The sustainability of mining projects is linked to informed investment decisions based on public reporting of exploration and mineral resource estimation results. In Australia, public reporting guidelines are established by the Joint Ore Reserves Committee reporting code through the JORC Code (2012). Although the assessment of uncertainty in the results reported is a requirement, this is often communicated qualitatively and evaluated subjectively. This can become a liability particularly in the early stages of mining projects when spatial domains of geological interpretation and mineralisation envelopes inform resource estimations’ reliability. A recent review of JORC reports found no reports used quantitative assessments of the geological interpretation or mineral resource estimation envelopes, and 27 per cent of reports did not address the question of quality of geological interpretation. Reports that did address the quality used 19 different terms to communicate quality. This work presents methodologies for quantitative uncertainty assessment and communication and explores how they could be applied in public reporting practice. Quantitative uncertainty reporting would benefit mine planning and financial modelling as they normally assume the geology is 100 per cent right (since no error is reported or only a single deterministic model is provided). The complexity, cost, and additional work of doing a quantitative assessment could hinder a straightforward implementation. This could be overcome if mining companies budget for quantitative uncertainty assessment and associated professional development. A compulsory requirement for the inclusion of uncertainty assessments in public reporting or adopting standardised subjective language would improve industry practice.
Citation

APA: W Patton U Mueller H Talebi I Minniakhmetov  (2022)  Geostatistical modelling of geometallurgical classes

MLA: W Patton U Mueller H Talebi I Minniakhmetov Geostatistical modelling of geometallurgical classes. The Australasian Institute of Mining and Metallurgy, 2022.

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