Drillhole placement subject to constraints for improved resource classification

CIM Journal Preprints, 2017

D. S. Silva
Centre for Computational Geostatistics, University of Alberta
Edmonton, Alberta, Canada

A. Jewbali
Newmont USA Limited
Denver, Colorado, USA

J. B. Boisvert and C. V. Deutsch
Centre for Computational Geostatistics, University of Alberta
Edmonton, Alberta, Canada

https://doi.org/10.15834/cimj.2018.3

Drillhole placement involves benefits, costs, and constraints. Benefits are related to the drilling campaign value, which includes maximizing ―indicated‖ and ―measured‖ resources. Costs include drilling, rig movement, and access construction. Constraints include infeasible areas, maximum and minimum angles of drilling, maximum depth of drilling, and budget. Manually planning drillholes that meet these constraints is suboptimal. A framework for straight drillhole optimization that accounts for benefits, costs, and constraints is presented. The method aims to maximize the value of resources converted from ―inferred‖ to indicated and measured. The framework is demonstrated for a Nevada gold deposit and outperforms manually selected drillholes.

Keywords: Diamond drilling, Infill drilling, Mineral exploration, Mining, Optimization
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