Characterisation and 3D modelling of a nuggety, vein-hosted gold ore body, Sunrise Dam, Western Australia

Abstract

In high-nugget gold ore bodies, samples taken from drill core for gold assay are typically too small to allow for the extreme spatial variability in grade and are a poor representation of the underlying distribution of mineralisation. The GQ North lode at the Sunrise Dam Gold Mine in Western Australia is a good example of an orebody which has a very strong nugget effect (coefficient of variation >20) and that has proved very problematic to model. Gold is hosted in vein stockworks and shear zones and although there is a clear spatial relationship between mineralisation and alteration, high vein density and well-developed foliations, the relationship is best defined statistically because the association between high gold grades and various combinations of these features is non-trivial. We present a method for automating the inclusion of geological data (proxies for gold mineralisation) into the prediction of mineralised rocks, using conditional probability. The method uses the gold assays and the logged geological data to calculate the probability that rocks with particular geological features will be mineralised. The ore body can then be modelled automatically using interpolation software with isosurfaces indicating the regions with highest probability of gold mineralisation. A good understanding of the geological features associated with mineralisation and consistent geological logging are important prerequisites for successful conditional probability modelling of drill hole data.