24-MMP-A4 Mine Valuation and Mineral Resource Estimation · December 2013
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
EGBC National Exam — Mining and Mineral Processing Engineering, 09-Mmp-A4 Mine Valuation and Mineral Resource Estimation, 2013-Dec. 3 hours duration; one handwritten 8.5×11 in reference sheet permitted (not an open-book exam); only approved Sharp or Casio calculators allowed. Question 1 is compulsory (40 marks, parts 1.1–1.7); candidates then select FOUR of the six optional Questions 2–7 (15 marks each) to complete the paper.
Reference texts: Isaaks & Srivastava, An Introduction to Applied Geostatistics (variogram modelling, kriging estimators, compositing and support); Hustrulid, Kuchta & Martin, Open Pit Mine Planning and Design (NPV/cut-off grade methodology, cost estimating, financing structures); Torries, Evaluating Mineral Projects: Applications and Misconceptions (SME) (mine valuation, cost of capital, inflation treatment); Gentry & O'Neil, Mine Investment Analysis (net smelter return, smelter/refining contract terms); SME Mining Engineering Handbook, 3rd ed. (mineral economics, capital and operating cost estimating).
Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.
4.1 Comment on the claims. This power-law form, Cost/day = K·Tx, is a standard parametric (factored) mining cost-estimating relationship, fitted by regressing ln(cost) on ln(T) across a population of operating mines of different scale – exactly the same statistical philosophy as Taylor's Rule in Q1.1. Dividing by T gives cost/tonne = K·T(x−1) = K/T(1−x), confirming the algebra in the claim. Because most such components exhibit economies of scale, the fitted exponent x is normally less than 1 (cost grows sub-linearly with throughput, reflecting fixed-cost components, bulk purchasing and mechanization efficiencies spread over more tonnes); since (x−1) is then negative, cost/tonne decreases as T increases, which is the physically sensible behaviour the claim implies. Two cautions are warranted: (i) K and x are only valid within the range of mine sizes actually used to calibrate them – extrapolating far outside that range risks missing real diseconomies (haul-distance/pit-geometry limits, logistics bottlenecks) that a pure power law cannot capture; and (ii) different cost components legitimately have different exponents, because they scale with different physical drivers – here Haulage correctly carries a shallower exponent (0.6) than Drilling/Blasting/Loading/General (0.7), consistent with haul fleet requirements scaling somewhat differently with throughput than drill-and-blast pattern intensity.
Given.
| Component | Cost/day formula |
|---|---|
| Drilling | 1.90 T0.7 |
| Blasting | 3.17 T0.7 |
| Loading | 2.67 T0.7 |
| Haulage | 18.07 T0.6 |
| General | 6.65 T0.7 |
| Throughput, T | 50,000 t/day (ore + waste) |
Find. Individual component and total costs, in $/day and $/tonne.
Approach. Evaluate T0.7 and T0.6 once, then substitute into each component's own K and x; cost/tonne is cost/day divided by T (equivalently K·Tx−1).
| Component | Cost/day | Cost/tonne |
|---|---|---|
| Drilling | $\$3,698.56$ | $\$0.0740$ |
| Blasting | $\$6,170.75$ | $\$0.1234$ |
| Loading | $\$5,197.45$ | $\$0.1039$ |
| Haulage | $\$11,921.75$ | $\$0.2384$ |
| General | $\$12,944.96$ | $\$0.2589$ |
| Total | $\$39,933.48$ | $\$0.7987$ |