Algorithmic Optimization of an Underground Witwatersrand-Type Gold Mine Plan
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Original Paper
Algorithmic Optimization of an Underground Witwatersrand-Type Gold Mine Plan G. T. Nwaila ,1,6 S. E. Zhang,2 L. C. K. Tolmay,3 and H. E. Frimmel4,5 Received 24 June 2020; accepted 24 October 2020
In the mining environment, mine planning is complicated by the presence of unfavorable environmental conditions, limited knowledge of the shape and size of the deposit, ore body characteristics, and volatile market conditions. In this paper, we propose a top-down algorithmic approach to strategically optimize the cutoff grade and net present value (NPV), and implement its solutions at the operation level, while simultaneously mitigating operation risks, to maximize the life of an ultra-deep gold mine from the Witwatersrand Basin, South Africa. To date, the Witwatersrand Basin has contributed about 28% of the worlds total gold supply from a series of Mesoarchaean quartz pebble conglomerate units (referred to as reefs). Through a quantitative analysis using algebraic and stochastic methods, we ranked mining variables in terms of their margin sensitivity and impact/adjustability efficacy. The results of this study showed the following. By using our proposed approach, an underground mine plan can be optimized by focusing on few key variables. Strategic mining of combinations of high-grade panels with low-grade panels and counter-balancing their risk profiles can yield optimal executable mine plan results (i.e., higher NPV, ideal profit margin, and lower risk) without sterilizing a given mineral resource for underground mining operations. KEY WORDS: Gold, Cutoff grade, Mine planning, Monte Carlo simulation, Optimization, Underground mine.
INTRODUCTION
1
School of Geosciences, University of the Witwatersrand, Private Bag 3, Wits 2050, South Africa. 2 PG Techno Wox, 43 Patrys Avenue, Helikon Park, Randfontein 1759, South Africa. 3 Tolmay Enterprises, 150 Galena Avenue, Kloofendal 1703, South Africa. 4 Bavarian Georesources Centre, Department of Geodynamics and Geomaterials Research, Institute of Geography and Geology, University of Wu¨rzburg, Am Hubland, 97074 Wu¨rzburg, Germany. 5 Department of Geological Sciences, University of Cape Town, Rondebosch 7700, South Africa. 6 To whom correspondence should be addressed; e-mail: [email protected]
In South Africa, the unit production cost of mining ore deposits has escalated by > 20% over a decade while production and ore grade in certain deposits have declined by similar proportions (Tholana et al. 2013; Neingo and Tholana 2016). These on-going changes highlight the operational and financial challenges faced by the mining industry, such as depletion of desirable and highly profitable ore bodies, increases in labor and operational costs, resulting in continuous decline in profit. In response to these trends, mining companies, specifically those with underground mining operations, have restructured their operations through voluntary retrenchments, termination of capital projects, cost reduction, non-core asset divestment and geo-
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