Ore reserve estimation is the technical process of calculating the tonnage and grade of mineable material within a deposit, building upon resource estimation by applying modifying factors that reflect realistic mining and economic constraints. The process typically begins with a three-dimensional geological model constructed from drill hole and sampling data, followed by statistical or geostatistical interpolation methods, such as kriging or inverse distance weighting, to estimate grade values across the modeled volume. Modifying factors are then applied, including an appropriate cut-off grade below which material is uneconomic to mine, expected mining dilution and ore loss, metallurgical recovery rates, and assumed commodity prices and operating costs. In iron ore and bauxite estimation, particular attention is paid to product quality blending requirements across the mine life. In gold estimation, nugget effect and sample variability often necessitate careful geostatistical treatment to avoid overestimating high-grade zones. In diamond reserve estimation, the process is distinctive because grade cannot be reliably estimated from small drill core samples alone; instead, large-diameter bulk sampling, sometimes involving the processing of thousands of tonnes of kimberlite, is required to obtain statistically meaningful diamond grade and value estimates.
