Choosing Between Two Kind of Sampling Patterns Using Geostatistical Simulation: Regularly Spaced or at High Uncertainty Locations?

Data from a mineral deposit are commonly obtained by core drilling. This kind of sampling involves high costs, limiting the number of drill holes. Additional holes should be located to bring the maximum benefit. The benefit can be evaluated by various ways and must take into account the goals of sampling. This article presents a case study where the deposit has been sampled and the new drillings must be added to reduce the uncertainty about a transfer function, Net Present Value (NPV) of the mining project. There are basically two ways to choose locations where new drillings should be placed for cases where the aim of sampling is to reduce uncertainty about a global function: the addition of new drillings outlining a quasi regular grid with previously collected drillings or the addition of new drillings on the locations of high uncertainty about the attribute of interest (or the attribute that is considered most influential in the transfer function). The performances of these patterns on reducing the uncertainty measured by the function selected are compared. The results point out that the most efficient pattern relates to the distribution (histogram) of the uncertainty about the attribute of interest. Thus, the choice of which sampling pattern should be adopted varies depending on data distribution and its influence on the transfer function.