Cut-Off Grade Calculator Guide

The standard economic cut-off grade (COG) for open-pit operations is calculated as: COG (%) = [(Mining Cost + Processing Cost) / (Metal Price × Recovery Rate × Conversion Factor)] × 100. Here, the conversion factor adjusts for unit consistency—e.g., 2204.62 lb/ton when metal price is in $/lb and ore mass is in short tons. Recovery rate must be expressed as a decimal (e.g., 0.85 for 85%). This formula derives from the break-even principle in SME’s Guidelines for Resource and Reserve Estimation (2022) and aligns with CIM Definition Standards (2019), which require explicit linkage of grade to economic viability. It assumes linear cost behavior and constant metallurgical response—a simplification requiring validation via testwork and mine planning software.

Unit consistency is critical: 1 metric tonne = 1000 kg, so no conversion factor is needed when both metal price ($/kg) and ore mass (tonnes) are metric. The formula becomes COG (%) = [(Mining Cost + Processing Cost) / (Metal Price × Recovery Rate × 10)] × 100 — because 1% grade = 10 kg metal per tonne ore. For example, at $3.5/kg metal price, 85% recovery, and $15/tonne total cost: COG = 15 / (3.5 × 0.85 × 10) × 100 ≈ 0.50%. Always verify units against your geological model and reporting standards (e.g., JORC Code Table 1 requires explicit statement of grade units). Automated calculators like ours perform this unit-aware arithmetic internally but demand correct input labeling.

Discrepancies commonly arise from unmodeled factors: general and administrative (G&A) costs, royalties, smelting/refining charges, transportation, or cut-off grade optimization for NPV maximization (not just break-even). Feasibility studies often use Lerchs-Grossmann pit optimization with nested pits, where COG is iteratively adjusted to maximize discounted cash flow—not static breakeven. Also, recovery may be grade-dependent (e.g., lower recovery at low grades), violating the constant-recovery assumption. Per CIM Best Practices (2023), feasibility-level COG should integrate stochastic geology, operational dilution, and schedule-driven cost escalation. Always reconcile calculator outputs with pit shell modeling results and sensitivity analysis per ISO 14040 (LCA framework for sustainability-informed grading).

Not directly—this calculator assumes uniform metallurgical response, but copper porphyries often require separate oxide/sulfide processing streams with distinct recoveries (e.g., 75% for oxide vs. 92% for sulfide leach/concentrate) and costs. Using a single average recovery misrepresents economics. Best practice (per SME Copper Porphyry Handbook, 2021) is to calculate domain-specific COGs and apply block-model conditional simulation. Additionally, acid consumption in oxide zones or arsenic penalties in sulfides introduce non-linear cost terms. Our tool serves as an initial screening value only; definitive COG for such deposits requires integration with process mineralogy data (e.g., QEMSCAN®-derived liberation models) and flowsheet costing in tools like METSIM® or HSC Chemistry.

Accuracy is limited in exploration—typically ±30–50% error due to sparse data on actual mining dilution, geotechnical constraints, and recovery variability. The calculator assumes deterministic inputs, whereas exploration-grade estimates have high uncertainty (e.g., recovery ±15% at 90% confidence per CRIRSCO guidelines). For scoping studies, use probabilistic COG: run Monte Carlo simulations over input distributions (e.g., metal price lognormal, recovery beta-distributed). As recommended in the 2022 AusIMM Resource Estimation Handbook, always report COG as a range (e.g., 0.25–0.42%) with P10/P50/P90 values. Field validation via bulk sampling and pilot plant testing remains essential before advancing to pre-feasibility.

No—this calculator includes only direct mining and processing costs. Environmental compliance costs (e.g., TSF closure bonding, long-term water treatment, carbon taxes) must be added to the total cost term to reflect true economic viability. Per IFC Performance Standard 2 and GISTM (Global Industry Standard on Tailings Management), these can add $0.50–$3.00/tonne depending on jurisdiction and deposit type. Omitting them risks material underestimation of COG—especially for low-grade, high-tonnage deposits. Best practice (CIM Environmental & Social Guidance, 2022) is to embed lifecycle environmental liabilities into the cost structure. We recommend augmenting the calculator’s ‘processing_cost’ input with a line-item for ‘ESG-adjusted cost’ derived from site-specific EIA cost models.

This calculator is calibrated for open-pit economics—its assumptions (e.g., low stripping ratio, high production rates, truck-and-shovel fleet costs) do not hold for underground operations. Underground COG requires fundamentally different cost drivers: development cost per meter, stope access, ground support, ventilation, and lower throughput. A typical underground COG is 2–5× higher than open-pit for the same commodity. Per SME Underground Mining Methods (3rd ed.), underground COG should use: COG = (Development Cost + Mining Cost + Milling Cost) / (Metal Price × Recovery × 10). Always apply mine method–specific cost databases (e.g., MineCost™ or industry benchmarks from AMECO) and confirm with empirical data from analogous operations—never extrapolate open-pit COG downward.

Update the cut-off grade quarterly at minimum—and immediately following material changes: >10% metal price shift (e.g., LME copper spike), >5% cost variance (fuel, labor, energy), recovery degradation (>3% drop in plant performance), or new regulatory requirements (e.g., updated emissions pricing). Per CIM Mining Guidelines (2023), formal COG reviews must accompany each mine plan update (annual for operating mines) and integrate new geostatistical models, reconciliation data, and market forecasts. Use rolling 12-month average metal prices (not spot) to dampen volatility, aligned with SEC Industry Guide 7 and ASX Listing Rule 5.12. Document all assumptions and sensitivities in the Technical Report (NI 43-101 or JORC-compliant) to ensure auditability and stakeholder transparency.