Using geochemical proxies to model nuggety gold deposits: An example from Sunrise Dam, Western Australia

Abstract

Gold distribution in vein-hosted hydrothermal ore deposits is commonly nuggety (i.e. occurs as very localised concentrations of gold). In these cases samples for gold assay from diamond drill core may be too small to model the underlying heterogeneity of gold distribution and result in poorly constrained ore body models and underestimated gold resources. Hence, it is common practice to use more spatially continuous proxies for mineralisation to help define the boundaries of mineralised regions. We present a method for automating the use of geochemical proxies for nuggety gold ore bodies.Sunrise Dam Gold Mine, in Western Australia, is a world-class gold deposit with a very high nugget effect. Multi-element geochemical data has been collected at this site in order to improve prediction of mineralised regions. Suitable proxy elements have been selected from this data set, in particular, those that are spatially related to gold mineralisation but do not display nuggety distribution, such as Sb, Rb and Cr.We applied a probabilistic approach to the problem of quantifying the relationship between gold assay values and geochemical elements. It is shown that a kernel density estimator and Bayes conditional probability can provide an effective method for calculating the probability of a sample having elevated gold content and that this measure will be more spatially continuous than gold assay values if the appropriate geochemical proxies are selected. Using conditional probability and suitable cut-off values, we reclassified approximately 27% of samples as mineralised which returned low Au assay results. When plotted on drill holes conditional probability values provided a much more spatially continuous guide to mineralised regions than Au assay values alone.