A New Semi-greedy Approach to Enhance Drillhole Planning

In advanced exploration projects or operating mines, the process of allocating capital for infill drilling programs is a significant and recurrent challenge. Within a large company, the different mine sites and projects compete for the available funds for drilling. To maximize a project's value to its company, a drillhole location optimizer can be used as an objective tool to compare drilling campaigns. The fast semi-greedy optimizer presented here can allow for the obtention of close to optimal solutions to the coverage problem with up to three orders of magnitude less computing time needed than with integer programming. The heuristic approach is flexible as it allows dynamic updating of block values once new drillholes are selected in the solution, as opposed to existing methods based on static block values. The block values used for optimization incorporate kriging estimate and variance, estimate of indicator at cutoff grade and distances to existing or newly selected drillholes. The heuristic approach tends to locate new drillholes within the maximum risk areas, i.e., within less informed zones predicted as being ore zones. Applied to different deposits, it enables, after suitable normalization, comparison of different drilling campaigns and allocation of budgets accordingly.