A New Semi-greedy Approach to Enhance Drillhole Planning
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Original Paper
A New Semi-greedy Approach to Enhance Drillhole Planning Raphae¨l Dutaut1,2 and Denis Marcotte1 Received 20 January 2020; accepted 28 March 2020
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 projectÕs 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. KEY WORDS: Geostatistics, Infill drilling, Risk control, Semi-greedy optimization, Heuristic.
INTRODUCTION During exploration and mining phases, the costs of infill drilling represent a significant portion of total project costs. Deposit definition is usually the result of a staged process with confidence in mineral resource estimates being gradually upgraded from inferred to indicated and measured categories (Canadian National Instrument 43-101). Uncertainty on a deposit can represent a high risk for the company in terms of investment (e.g., construction of a new mine or extensions) or actual production. Par1
Civil, Geological and Mining Department, Polytechnique Montre´al, C.P. 6079, Succ. Centre-Ville, Montreal, QC H3C 3A7, Canada. 2 To whom correspondence should be addressed; e-mail: [email protected]
ker (2012) indicates that changes in the net present value (NPV) can be six times the variations on grade, so that a 10% error in grade estimation can result in a 60% variation in NPV. In order to decrease the risks associated with resource estimation, obtaining more information through further drilling is the standard practice. Face with limited budget, optimization of drillhole localization becomes of strategic importance for mining companies. Infill drillhole planning is generally performed manually by an experienced geologist. The drilling plan is then submitted for approval. To reduce subjectivity inherent to the exercise, drillhole location optimization has been studied since the late 1970s (Kim et al. 1977; Scheck and Chou 1983). These attempts focused mainly on
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