24-MMP-A4 Mine Valuation and Mineral Resource Estimation · December 2014
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, 2014-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, volume–variance relations); Hustrulid, Kuchta & Martin, Open Pit Mine Planning and Design (mine valuation, NPV and cut-off grade methodology, mineable reserves); Gentry & O'Neil, Mine Investment Analysis (Canadian mining taxation, smelter/refining contract terms, net smelter return); SME Mining Engineering Handbook, 3rd ed. (mineral exploration/evaluation stages, ore reserve classification); CIM Best Practice Guidelines and NI 43-101 (Canadian Securities Administrators).
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.
A block model discretizes the deposit into a regular 3-D grid of small blocks (typically sized near the intended SMU), each carrying an interpolated grade, density, rock-type and geometallurgical code. It is used because it converts scattered, irregularly located drill-hole assays into a uniform digital representation that can be queried, summed and re-cut by any pit outline, stope design or cut-off grade instantly — supporting resource estimation, mine planning, scheduling, and reserve reporting from one consistent dataset rather than re-interpreting raw drill data for every study.
Porphyry copper application. Because the mineralization is broadly continuous, a standard orthogonal block model (e.g. 10×10×10 m or 15×15×15 m blocks) works well: grades are interpolated by ordinary kriging or inverse-distance weighting using the fitted variogram, honouring the smoothly varying nature of the deposit. Blocks are classified measured/indicated/inferred by kriging variance or data density, and the same model directly supports pit optimization (e.g. Lerchs–Grossmann/floating-cone pit outlines run on the block grades and costs).
Irregular vein application. A single rectilinear grid poorly represents a thin, dipping, sinuous vein because most blocks would straddle the vein/wallrock contact and dilute the true grade. Vein deposits therefore commonly use a sub-blocked, wireframed, or "vein-following" block model: the vein is first digitized as a 3-D wireframe honouring true structural geometry (strike, dip, pinch-and-swell), and grade is then estimated only within that wireframe — often with the block grid locally rotated or sub-celled to follow the vein orientation, or with polygonal/sectional estimation used instead of a full 3-D grid where the vein is too narrow and irregular for reliable block-scale kriging. The intent throughout is the same: prevent waste dilution from being averaged into ore blocks that a rigid, un-rotated grid would otherwise create.
