TOS forum, Issue 5, p. 19 (2015)

Good sampling is good business: reconciling economic drivers of productivity and quality using fundamentals of sampling theory

O. Domingueza and K. Smithb
a[email protected]
b [email protected]

Iron Ore supply is outpacing global demand, reinforcing the importance of product quality and reliability as critical factors that distinguish Iron Ore producers in a competitive market. This expectation calls for a shift in industry attitudes toward sampling in bulk commodities, beginning with a greater emphasis on optimisation of sampling processes from Exploration to Port. Business initiatives aimed at optimising processes often call upon technological innovation, such as mobile sampling and analysis modules at the drill rig. Such technologies indeed represent an exciting frontier in the business of minerals exploration; however their merits must be critically compared to existing sampling protocols before implementation if sample quality is to be maintained. Quantifying the Fundamental Sampling Error (FSE) of the sampling protocol is a minimum requirement to achieve this and should be preceded by experimental calibration of the sampling constant K and the exponent alpha. Here, we present a case study in which the Segregation Free Analysis (SFA) calibration methodology proposed by Minnitt et al. was used to determine K and alpha for a Channel Iron Deposit (CID) and a Brockman Iron Formation-hosted Bedded Iron Deposit (BID) from the Pilbara region of Western Australia. Following three experimental calibrations of K and alpha, liberation size was calculated for iron oxides and deleterious minerals using Gy’s formula. Validation of liberation size is critical if the resulting FSE calculation is to inform business decisions. Electron beam instruments such as QEMSCAN have been proposed as a relatively quick and low cost way to estimate liberation size. An “off-the-shelf” QEMSCAN analysis was trialled as a validation method against the SFA calibration results. Good agreement was achieved between liberation sizes determined by the SFA calibration method and the QEMSCAN analysis. Furthermore, the QEMSCAN results proved to be a beneficial source of supplementary information, in the form of particle size analysis, which indicates the degree of aggregation that persisted in the calibration material despite best efforts to eliminate it, as well as mineral abundance analyses, which either confirmed or highlighted uncertainty around critical mineralogical assumptions made in the calibrations. These observations emphasise the importance of validation when assessing FSE. The case study presents an industry perspective on the applications of sampling theory in response to an increasingly competitive Iron Ore market.

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