Discussion - Optimization of Mining Engineering Design in Mineral Valuation – Wells, Howard M. – Technical Papers, MINING ENGINEERING, Vol. 30, No. 12, December 1978, pp. 1676-1684

Dear Editor: It is with great pleasure that I read Mr. Howard M. Wells article in the December 1978 issue of MINING ENGINEERING entitled: "Optimization of Mining Engineering Design in Mineral Valuation." Mr. Wells very adequately presents the case and point that there are a great number of variables which must be analyzed during an economic evaluation of an FUND RESOURCE, such as copper or uranium. I wish to take this opportunity to suggest that, given today's economic climate, decision making takes place under conditions of uncertainty and that this uncertainty justifies our need to examine each one of the parameters entered into the evaluation model. It is my contention that the influence of the tonnages and grades as well as their distributions, have the most profound effect upon the results of an evaluation. Everyone concerned with the evaluation of FUND RESOURCES realizes that as metal prices decline or stagnate with sharply rising direct operating costs, cutoff grades (Gc) must increase according to the equation below which Mr. Wells uses: Gc = Total Operating Cost/(Market Price X 20 X Recovery) However, historically, we have seen cutoffs move dramatically lower in both the copper and uranium industries for the past decade. Henceforth, this established the metals industry most important argument for processing greater tonnages of lower grade materials from disseminated deposits (refer to paper by Kirkman, Roy C.). These disseminated deposits, created by either concentration processes (uranium) or dispersion processes (copper, gold, molybdenum), have log-normal grade distributions (Fig 1). Gross profits are rising, but unit profits are falling. The industry has created longevity through economy of scale, i.e., mining vast tonnages of low grade. In order to develop the great tonnages necessary to prove economic viability, we must examine alternatives at the low-end of the tonnage grade relationship. Notice from [Fig. 2] that as we move further to the right away from line A-B drawn tangential to the average grade curve at 45°, total profits will increase (given fixed annual production capacity) and unit profits decrease. The theoretical optimum operating point is where: [ ] At this point my observation is that slight shifts in production capacity bring about greater changes in profitability due to greater grade changes. Therefore, the best financial risk evaluation is obtained by totally revising the mining engineers methods and fixing the financial parameters such as discount and interest rates. A 10% shift in either of these two parameters will not cause near the same variance in economic viability as will a change on the GRADE-TONNAGE curve [(Fig. 2)].