Optimizing Cut-Off Grade to Maximize NPV

Cut-off grade is one of the most influential parameters in the economics of a mining project. It determines what is considered minable ore and what is treated as waste — and therefore, directly, the size of reserves, the mine life, and the project's net present value (NPV). Yet it is often set in a simplistic way, without rigorous optimization.

What is cut-off grade?

Cut-off grade is the minimum concentration of a metal or mineral below which extraction is not economically justified under current or anticipated market conditions. It is generally expressed in g/t (gold, silver), % (copper, zinc), or specific units depending on the metal considered.

A cut-off grade that is too high reduces the minable tonnage and shortens mine life, but raises the average grade and unit revenue. A grade that is too low inflates the reserves but dilutes grades, increases processing costs and can reduce overall NPV.

The Lane Method: dynamically optimizing cut-off grade

Kenneth Lane’s theory (1988) remains the reference for cut-off grade optimisation. It considers three limiting constraints in a mine:

• The mining capacity (tonnes mined per period)
• Processing capacity (tonnes processed per period)
• Sales/refining capacity (metal sold per period)

Depending on which constraint is active in each period, the optimal cut-off grade will differ. The goal is to maximise NPV over the entire mine life, not just short-term profit.

Factors that influence cut-off grade

Metal prices: a rise in the gold price, for example, can justify lowering the cut-off grade to bring more marginal ore into the reserves.

Operating costs (OPEX): any reduction in mining, processing or G&A costs allows the cut-off grade to be lowered profitably.

Discount rate: a high rate favours a higher cut-off grade early in the project (mining the richest ore first) to maximise early cash flow.

Metallurgical recovery: better plant recovery is effectively equivalent to lowering the economic cut-off grade.

Geological and geotechnical constraints: certain areas can only be mined at specific costs, which influences the local cut-off grade.

Practical optimization strategies

Block optimization: use software such as Whittle, Deswik, or GEOVIA to optimize pits and sequences by integrating variable cut-off grades by phase and period.

Sensitivity analysis: test the impact of ±10–20% variations in prices, costs, and recovery to assess the robustness of the selected cut-off grade.

Periodic review: cut-off grade is not fixed — it must be revisited with every update of economic parameters or during feasibility studies.

Integration into the financial model: cut-off grade must be directly linked to the DCF model to measure its real impact on NPV and IRR.

Quantified impact: a simplified example

For a gold mine with 10 Mt of resources at an average grade of 1.5 g/t:

• Cut-off at 0.8 g/t → 8 Mt of reserves, average grade 1.8 g/t, NPV = $120M
• Cut-off at 0.5 g/t → 9.5 Mt of reserves, average grade 1.55 g/t, NPV = $105M
• Cut-off at 1.2 g/t → 5 Mt of reserves, average grade 2.1 g/t, NPV = $95M

In this example, 0.8 g/t maximizes NPV — neither too high, nor too low.

Conclusion

Cut-off grade optimization is an iterative, multidisciplinary, and strategic exercise. It requires close collaboration between geologists, mining engineers, metallurgists, and financial analysts. At CCE Mining, we systematically integrate this optimization into our planning and reserve estimation studies, to ensure every project reaches its full economic potential.