From Drill Holes to Dollars
The block model is the fundamental bridge between geological data and mining economics. Every open pit and underground mine in the world relies on a block model — a three-dimensional grid where each block carries an estimated grade, tonnage, and classification. Drill hole samples, typically spaced tens to hundreds of meters apart, are the sparse input. Geostatistical estimation (kriging) fills the gaps, producing the best possible grade estimate for every block in the deposit along with its uncertainty.
Cutoff Grade Optimization
The economic cutoff grade determines which blocks are ore (worth mining and processing) and which are waste (removed but not processed). In this simulation, you can adjust the cutoff and immediately see how it reshapes the ore body — raising the cutoff shrinks the ore envelope and increases the average ore grade, while lowering it expands the envelope but dilutes the grade. The optimal cutoff depends on metal price, mining cost, processing cost, and recovery — Lane's algorithm formalizes this optimization.
Understanding the Visualization
The simulation displays a 2D cross-section of a block model. Each block is colored by its estimated grade — hot colors (red/yellow) indicate high grades, cool colors (blue) indicate low grades. The cutoff grade is shown as a contour line separating ore (opaque) from waste (translucent). Drill hole locations are marked as white dots. Notice how blocks near drill holes have sharp color contrasts (confident estimates) while blocks far from data trend toward the mean grade (regression to mean — a kriging property).
Resource Classification and Risk
Block models support the formal resource classification system used worldwide. Blocks estimated from dense, closely-spaced drilling are classified as Measured resources — the highest confidence category. Blocks estimated from moderate drill spacing are Indicated. Blocks estimated from sparse data or extrapolated are Inferred — too uncertain for economic evaluation. The transition from Inferred to Measured represents a journey from geological speculation to bankable reserves, with each step requiring more drilling, better variogram models, and lower kriging variance.