Integrating the Theory of Sampling into Underground Mine Grade Control Strategies: Case Studies from Gold Operations

Abstract

Grade control aims to deliver adequately defined tonnes of ore to the process plant. The foundation of any grade control programme is collecting high-quality samples within a geological context. The requirement for quality samples has long been recognised, in that these should be representative and fit-for-purpose. Correct application of the Theory of Sampling reduces sampling errors across the grade control process, in which errors can propagate from sample collection through sample preparation to assay results. This contribution presents three case studies which are based on coarse gold-dominated orebodies. These illustrate the challenges and potential solutions to achieve representative sampling and build on the content of a previous publication. Solutions ranging from bulk samples processed through a plant to whole-core sampling and assaying using bulk leaching, are discussed. These approaches account for the nature of the mineralisation, where extreme gold particle-clustering effects render the analysis of small-scale samples highly unrepresentative. Furthermore, the analysis of chip samples, which generally yield a positive bias due to over-sampling of quartz vein material, is discussed.

Establishing a sub-sampling plan for waste-derived solid recovered fuels (SRF): Effects of shredding on representative sample preparation based on theory of sampling (ToS)

“…This formula could, also, be used in sub-sampling either for the calculation of minimum subsampling uncertainty (FE) for a given sample size or for the calculation of the required sample mass to obtain a specified FE (Dominy et al, 2019). At each stage of sub-sampling, Ms is the mass of the sub-sample at this stage and ML is the mass of sample or higher level of sub-sample (Gerlach and Nocerino, 2003).…”

“…Every stage of mass splitting introduces FE, the summation of which gives the overall FE of the subsampling process. An overall FE ≤ 15% is a recommended acceptable reference limit (Dominy et al, 2019;Dominy et al, 2018b;Gerlach and Nocerino, 2003), although the limit value depends on the fitness for purpose requirements that are different for each application (Ramsey and Thompson, 2007).…”

“…The establishment of a sampling and sub-sampling plan able to meet end-users requirements (fitness for purpose) is a critical quality assurance measure (Dominy et al, 2019;Dominy et al, 2018b). For example, waste-to-energy plants need accurately determined quality of the waste-derived material, such as solid recovered fuel (SRF), to ascertain efficient utilization (Flamme and Ceiping, 2014).…”

Importance of representative metallurgical sampling and testwork programmes to reduce project risk – a gold case study

“…Sampling is a vital component during all stages of the Mine Value Chain. It includes the sampling of in-situ material and broken rock for geological, metallurgical and geoenvironmental purposes (Carrasco et al 2004;Minnitt 2007;Ehrig and Pitard 2017;Rendu 2017;Dominy et al 2018aDominy et al , 2018bDominy et al , 2018cDominy et al 2019;Pitard 2019). Sampling errors are defined in the context of the Theory of Sampling (TOS), where incorrect actions may lead to uncertainty and create an overall measurement error (Gy 1982(Gy , 2004Pitard 2019).…”

“…2018a, 2018b, 2018c; Dominy et al. 2019; Pitard 2019). Sampling errors are defined in the context of the Theory of Sampling (TOS), where incorrect actions may lead to uncertainty and create an overall measurement error (Gy 1982, 2004; Pitard 2019).…”