Speaker: Paul Marchal

Date: Thursday 23th of May 2024, 1:15pm.


In mining, assessing uncertainties is an essential step throughout the resource development cycle, from exploration campaigns to remediation and development strategy planning. Indeed, geological data are only partially covering the subsurface and are subject to two main types of uncertainty:  i) sampling and measurement uncertainties, and ii) epistemic or conceptual uncertainties related to data interpretation. This paper focuses on the second ones. It aims to evaluate the diversity of conceptual interpretations that specialists and non-specialists have on data, and the potential impact this can have on the estimation of  uranium deposit geometries. For this purpose, a case study was carried out in the context of an unconformity-associated uranium deposit in the Athabasca basin. Based on a reference section from this area, a cross-section with synthetic drillcores was produced and given to 30 people to correlate and interpret. Our objectives are multiple: defining metrics for comparing data interpretations, assessing the differences in interpretations between expert and non-expert uranium geologists. We defined a set of mathematical criteria (50) based on 4 key characteristics: i) mineralized zones, ii) associated altered zones, iii) associated structural network, and iv) interpretation glyphs and annotations. Individual and group analysis of the defined criteria (t-SNE, MDS) were performed. Digital Leapfrog models are also compared with hand-drawn models. Primary results show that the group of uranium experts is less dispersed overall in terms of property variance. They  tend to propose mineralization zones that are more impacted by the influence of  faults and unconformities. They are finally prone to produce less parsimonious interpretations, incorporating more geological concepts.