Beyond the pit: Why laboratory integrity now shapes mining viability

With commodity prices rising across the mining sector, from gold to strategically critical rare earth elements, more material has moved back into economic consideration. That has increased the importance of reliable, 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 assumptions were recalculated.

That recalibration narrows the margin for analytical uncertainty. As projects operate closer to economic thresholds, small differences in assay results carry greater weight across exploration, 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 tonne. This is true in gold projects adjusting cutoff grades and in rare earth deposits managing complex elemental distributions. At that scale, analytical data does more than confirm grade. It shapes classification, recovery modelling, and resource estimates.

No reserve is declared without defensible analytical data supporting the resource model. In projects operating near cutoff, laboratory results directly influence economic classification decisions.

“The difference between a viable project and a marginal one can come down to analytical precision,” says William R. Sattlegger, P. Geo., CEO of i2iVestcom Advisors Corporation. “Those numbers drive metallurgy, recovery, and valuation. If you lose confidence in the data, you lose confidence in the project.”

Consider a deposit processing 20 million tpy 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.

Sampling risk: The first point of failure

Before instrumentation or calibration is evaluated, a more fundamental question must be answered: is the sample representative?

“In mining, it’s really the sampling,” Sattlegger explains. “A poor sample can lead to swings of over 50% in reported values.”

Such variability can distort block models, misclassify material, and undermine reconciliation between predicted and actual production. Even advanced ICP-MS systems cannot compensate for a non-representative sample.

For that reason, serious operations build layered QA/QC systems around sampling integrity. Blanks monitor contamination. Duplicates assess precision. Certified reference materials verify accuracy. In exploration programmes, these controls support resource estimates. In producing mines, they safeguard grade control and metal accounting.

As projects move closer to economic thresholds, QA/QC shifts from procedural discipline to active risk management. Investors and stakeholders increasingly expect sampling and verification protocols to be repeatable, documented, and defensible.

Calibration in complex mining matrices

Even when sampling is disciplined, analytical chemistry must still withstand challenging matrices.

Gold operations frequently involve cyanide leach solutions and high-total-dissolved-solids digests that can interfere with signal stability. Rare earth deposits present a different challenge: chemically similar elements across the lanthanide series, often at low concentrations, where small analytical bias can distort modelled distribution and downstream processing assumptions.

Accurate results depend not only on instrument performance but on calibration alignment. In high-TDS systems, mismatches between sample matrices and calibration standards can introduce systematic bias. Dilution steps intended to protect instrumentation create additional exposure to contamination, signal suppression, or drift. In rare earth analysis, interference correction and method validation are central to defensible reporting.

As projects advance toward feasibility studies or reserve disclosures, calibration is no longer just a laboratory detail. It becomes part of the project’s economic foundation. Analytical Supply Chains Adapting to Mining’s Demands These pressures are also reshaping expectations across the analytical supply chain. “As grades decline and deposits become more complex, the margin for analytical error narrows,” says Brian Alexander, Ph.D., Chief Technical Officer of Inorganic Ventures. “In mining, you’re often working at trace levels in difficult matrices. If calibration doesn’t reflect the chemistry you’re measuring, small biases can compound.”

In one gold operation working near its cutoff threshold, reconciliation differences emerged between process samples and laboratory assays. Instrumentation performed as expected, but the issue traced back to calibration alignment within a cyanide matrix. After shifting to matrix-matched standards and strengthening documentation, variability decreased and confidence improved.

“What we’re seeing is that mining labs need standards that behave like the samples they’re actually running,” Alexander says. “That’s where matrix matching and documentation become so important.”

That kind of adjustment reflects a broader shift. As more analytical work moves closer to the mine site and decision cycles compress, laboratories rely more heavily on stable calibration, traceable standards, and support that can help resolve bias before it affects reporting.

Heavy equipment may move the rock. But in modern mining, it is the integrity of the assay, and the systems that support it, that ultimately determine whether that rock creates value.

Read the article online at: https://www.globalminingreview.com/special-reports/12052026/beyond-the-pit-why-laboratory-integrity-now-shapes-mining-viability/