Beyond the pit: Why laboratory integrity now shapes mining viability - ME Feature Article

With commodity prices rising across the mining sector, from gold to strategically critical rare earth elements, more material has moved back into economic consideration. This has placed greater emphasis on reliable and defensible analytical results. When gold reached record levels earlier this year, material long considered marginal was suddenly worth another look. Stockpiles were revisited, lower-grade zones returned to the model, and economic assumptions were recalculated in light of a new price reality. That recalibration narrows the margin for analytical uncertainty. As projects operate closer to economic thresholds, small differences in assay results begin to carry greater weight across exploration programs, grade control and processing decisions. In many operations, the line between sending material to the mill or to the dump hinges on fractions of a gram per ton. This is true in gold projects adjusting cutoff grades or in rare earth deposits managing complex elemental distributions. At that scale, analytical data do more than confirm grade; they shape classification, recovery modeling and longterm resource estimates. No reserve is declared without defensible analytical data supporting the underlying resource model. In projects operating near cutoff, those laboratory results directly influence economic classification decisions. “The difference between a viable project and a marginal one can come down to analytical precision,” said William R. Sattlegger, P. Geo., chief executive officer of i2iVestcom Advisors Corp. and executive director of the Critical Minerals Conference. “Those numbers drive metallurgy, recovery and valuation models. If you lose confidence in the data, you lose confidence in the project.” Consider a deposit processing 20 Mt (22 million st) annually at a cutoff near 0.5 g/t. A shift of just 0.05 g/t in reported grade, whether from sampling variability or calibration bias, can alter how large volumes of material are classified. Across that scale, even small analytical differences can translate into meaningful economic consequences.