Linking Gy’s Formula to QA/QC Duplicates Statistics

Marcotte, Denis; Dutaut, Raphaël

doi:10.1007/s11004-020-09894-x

Cited by 2 publications

(1 citation statement)

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“…Assuming the following model (Marcotte and Dutaut, 2020) is valid: [1] where Z o is the observed value at the x position, Z v is the true value, and t is the multiplicative error of the analysis (in this study both Z v and t are assumed to be lognormal, a reasonable assumption for most precious and base metal deposits). Equation [1] can be written:…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A new grade-capping approach based on coarse duplicate data correlation

Dutaut

Marcotte

2021

J. S. Afr. Inst. Min. Metall.

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SYNOPSIS In most exploration or mining grade data-sets, the presence of outliers or extreme values represents a significant challenge to mineral resource estimators. The most common practice is to cap the extreme values at a predefined level. A new capping approach is presented that uses QA/QC coarse duplicate data correlation to predict the real data coefficient of variation (i.e., error-free CV). The cap grade is determined such that the capped data has a CV equal to the predicted CV. The robustness of the approach with regard to original core assay length decisions, departure from lognormality, and capping before or after compositing is assessed using simulated data-sets. Real case studies of gold and nickel deposits are used to compare the proposed approach to the methods most widely used in industry. The new approach is simple and objective. It provides a cap grade that is determined automatically, based on predicted CV, and takes into account the quality of the assay procedure as determined by coarse duplicates correlation. Keywords: geostatistics, outliers, capping, duplicates, QA/QC, lognormal distribution.

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Section: Theoretical Backgroundmentioning

confidence: 99%