Obtaining representative samples is of the uttermost importance for modelling mineral deposits. On one hand, Gy’s formula makes it possible to compute relative error variance for a specified target grade on the stringent assumption of perfect homogenization. On the other hand, duplicates (field, rejects and pulp) are now routinely used in QA/QC. No direct links have been established between Gy’s relative variance and the main duplicates statistics used in QA/QC. This paper presents a simple multiplicative error model that makes it possible to predict from Gy’s formula the standard deviation of duplicates differences and duplicates correlation for any distribution. Assuming lognormality, a test is derived to predict whether the sample preparation procedure is likely to meet the target proportion of duplicates with half absolute relative difference (HARD) of less than 10%. The test and the predicted statistics can be used to predict duplicates’ QA/QC results and make necessary adjustments early, before any QA/QC data is acquired. The relationships are tested and validated by simulations and a series of deposit data extracted from NI43-101 published reports.

获得具有代表性的样品对于模拟矿床至关重要。一方面，Gy公式可以在严格均质化的严格假设下计算指定目标等级的相对误差方差。另一方面，现在在质量检查/质量控制中通常使用重复项（田地，废品和纸浆）。Gy的相对方差与QA / QC中使用的主要重复统计之间没有直接联系。本文提出了一个简单的乘法误差模型，该模型使得可以根据Gy公式预测任何分布的重复差和重复相关的标准偏差。假设对数正态性，则得出一个测试来预测样品制备程序是否可能满足绝对相对差异为一半的重复样品的目标比例（HARD）的小于10％。在获取任何QA / QC数据之前，该测试和预测的统计信息可用于预测重复项的QA / QC结果并尽早进行必要的调整。通过模拟以及从NI43-101发布的报告中提取的一系列沉积数据来测试和验证这种关系。