Assessment of interpretation and spatial uncertainty of spatial domains

In the mining industry, code compliant reporting standards for public announcements have been developed setting minimum standards for public reporting of Exploration Results and Mineral Resources. These include an assessment of the quality and confidence in the data and work carried out since public reporting aims to provide information that is Material, Transparent and Competent to investors. There are four phases required to estimate a Mineral Resource (Preparation, Investigation, Model Creation and Validation), and estimation is highly dependent on the accuracy of the Preparation stage which is a result of the quality of the geological interpretation given for the mineralisation process and current spatial location. This interpretation seeks to spatially define geologically homogenous areas in the resource (spatial domains), corresponding to a single statistical population with a single orientation, where possible. In the estimation workflow, the creation of the spatial domain presents a challenge in terms of assessing the uncertainty in the geological interpretation often due to the manual and subjective interpretation used to guide its creation as well as in spatial domains with several mineralisation overprint events. The proposed work investigates a hybrid Bayesian method using multivariate quantitative data combined with qualitative data to predict and assess the interpretation uncertainty in the classification of drill hole intervals to a spatial domain and present methods available in current mining software to assess the spatial uncertainty of the 3D ‘wireframe’ or ‘rock type’ model interpretation.