Sampling across the Mine Value Chain

Dear Colleagues,

Sampling is a critical component throughout the Mine Value Chain; it includes the sampling of both in situ and broken material for exploration, resource and grade control, geoenvironmental, metallurgical and geometallurgical purposes. The data produced must be fit-for-purpose to contribute to Mineral Resources/Ore Reserves reported in accordance with The 2012 JORC Code 2012 or other international reporting codes. Quality assurance/quality control is critical to maintain data integrity through documented procedures, sample security, and monitoring of precision, accuracy and contamination. Samples are their associated assays are key inputs into important decisions throughout the Mine Value Chain.

The Theory of Sampling (TOS) was developed in the 1950s by the late Dr. Pierre Gy to improve sampling within the mining industry (though it has far wider applications). It defines and provides guidelines for the reduction of sampling errors, which may lead to uncertainty and create an overall measurement error. TOS attempts to break down this error into a series of contributions along the sampling value chain (e.g., the planning to assay-measurement process). Errors are additive throughout the sampling process and generate both monetary and intangible losses. The aim is to collect representative samples to accurately describe the material in question.

Despite the wealth of knowledge available on correct sampling principles, it is surprising how little attention and resources are often dedicated to collecting representative samples. Often, practitioners appear to be satisfied as long as some material is collected and delivered to the laboratory for analysis. Yet, unless the samples are representative, the whole measurement process is flawed at the outset and no amount of re-analysis can fix the problem. Consequently, companies stand to lose millions of dollars in terms of poor investment decisions, wasted resources, poor plant performance, poor product quality and income from product sales. Sampling, therefore, needs to be given the attention it deserves to ensure that the samples extracted are representative so that meaningful decisions can be made based on their analyses.

Dr. Simon Dominy
Prof. Hylke Glass
Prof. Kim Esbensen
Guest Editors

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