Conference Proceedings
Mineral Resource Estimation Conference Proceedings 2023
Conference Proceedings
Mineral Resource Estimation Conference Proceedings 2023
Comparison of two quantitative mineral resource classification methods – a case study from a large copper porphyry-skarn deposit
Two quantitative methods for Mineral Resource classification have been applied to a copper skarn deposit beneath a large open pit that is mining a world-class porphyry complex. A drill hole spacing study (DHSS) using the single block kriging method (SBK) and a conditional simulation method (CS) were applied to the skarn deposit and the results compared. Inputs to both processes included the proposed mining rate and stope designs to estimate the likelihood of achieving grade and metal production targets.
Mineral Resource classification of the deposit considers the relative precision of tons, grade and metal predictions over quarterly and annual production periods. These relative precision estimates are calculated at 90 per cent confidence interval (CI).
The SBK method represented the production period as a single large block. Kriging estimates were performed in the large block for various synthetic drill hole grids, and the estimation errors derived. The error was assumed to be normally distributed due to the large block size and quantity of samples, allowing CIs to be deduced.
The CS method followed a conventional sequential Gaussian simulation workflow where grades were simulated with a 5 ft × 5 ft × 5 ft grid node spacing inside mineralisation domains. Each realisation was then averaged up to monthly production volumes represented by a combination of designed stopes, and the coefficient of variation (CV) for the averaged grade was calculated. CI on the relative precision of grade predictions were then deduced from the CVs.
The two methods produced similar results; despite being calculated independently. CS results were used to report uncertainty in the proposed life-of-mine plan and highlight areas for additional drilling. SBK results were used as the basis for Mineral Resource classification as this method has been previously applied to the skarn deposit.
Mineral Resource classification of the deposit considers the relative precision of tons, grade and metal predictions over quarterly and annual production periods. These relative precision estimates are calculated at 90 per cent confidence interval (CI).
The SBK method represented the production period as a single large block. Kriging estimates were performed in the large block for various synthetic drill hole grids, and the estimation errors derived. The error was assumed to be normally distributed due to the large block size and quantity of samples, allowing CIs to be deduced.
The CS method followed a conventional sequential Gaussian simulation workflow where grades were simulated with a 5 ft × 5 ft × 5 ft grid node spacing inside mineralisation domains. Each realisation was then averaged up to monthly production volumes represented by a combination of designed stopes, and the coefficient of variation (CV) for the averaged grade was calculated. CI on the relative precision of grade predictions were then deduced from the CVs.
The two methods produced similar results; despite being calculated independently. CS results were used to report uncertainty in the proposed life-of-mine plan and highlight areas for additional drilling. SBK results were used as the basis for Mineral Resource classification as this method has been previously applied to the skarn deposit.
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- Published: 2023
- PDF Size: 1.303 Mb.
- Unique ID: P-03188-X3F3C8