Recoverable Resource Estimation Using Bivariate Uniform Conditioning at the Lihir Gold Mine

Bivariate recoverable resource estimation aims at predicting the recovered metal for a secondary variable when a cut-off is applied to a primary variable. The choice of a consistent geostatistical model is advisable to allow a robust estimation from exploration data of the primary and secondary metal recovery functions on a generic selection block (selective mining unit û SMU) within large panels. Ore processing decisions at Lihir Gold LimitedÆs Lihir Gold Mine are based on the gold and sulfur estimates of SMUs from production (grade control) data. The predictive model from exploration data at Lihir is based on the estimation of a recoverable resource for gold by Uniform Conditioning (UC), with an estimate of the sulfur grade being provided by Ordinary Kriging of panels. While univariate UC is adapted to the diffusive nature of the gold mineralisation (Ladolam orebody) at Lihir, the independent estimation of sulfur, through ordinary kriging, fails to capture the potential spatial correlation that exists between gold and sulfur mineralisation. This paper presents a practical implementation of bivariate UC, which better represents in the resource model the spatial correlation between gold and sulfur. Incremental economic gains through improved definition of material categories and scheduling are investigated, and the particular impact on the process of geological interpretation and domaining is emphasised.