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Optimally locating additional boreholes in the boundaries of ore deposits is an important problem in mining projects. To solve this problem, combined variance has been proposed as a cost function to be minimized. An issue about combined variance is its dependence on the value of variable at unknown location. This value is achieved through a round-based algorithm that estimates the probability of occurrence of ore and rounds it to the nearest integer without considering all scenarios. This study aims to consider all scenarios using a Monte Carlo simulation-based algorithm. This approach uses ordinary cokriging to estimate the probability of occurrence of ore at unknown locations. Then, the estimated probabilities are entered into a Monte Carlo simulation procedure to generate various realizations. The method was applied in the Chadormalu ore deposit to propose ten additional boreholes. The round-based algorithm proposed additional drill holes in the middle of ore-intersected and non-intersected initial drill holes. However, the Monte Carlo-based algorithm is sensitive to the thickness such that in boundaries with thicker ore, the additional boreholes are suggested farther away from the ore-intersected drill holes and closer to the non-intersected ones and vice versa.

A Monte Carlo Simulation-based algorithm for updating Combined Variance cost function in optimally locating additional drillholes