PART I PROJECT DEVELOPMENT
9. CONCLUSIONS
Accurate sampling methods are critical to obtaining meaningful analytical data in the gold industry. The basic rule for correct sampling and sample processing is that all parts of the ore, concentrate or slurry being sampled must have an equal probability of being collected and becoming part of the final sample for analysis. If this is not the case, bias is easily introduced that cannot be eliminated by simply averaging replicate measurements. Special
R.J. Holmes 18
care must also be taken to ensure that sample masses are adequate at each stage of sampling and sample preparation to achieve the required precision.
REFERENCES
Australian Standard AS 4433.1, 1997. Guide to the Sampling of Particulate Materials - Part 1:
Sampling Procedures. Standards Australia, Sydney.
Bartlett, H.E., 2002. Design of primary samplers for slurries in concentrators and statistical methods for measuring components of variance in sampling. J. South Afr. Inst. Min.
Metall., November/December 2002, 102(8), 485–490.
Franc-ois-Bongarc-on, D., Gy, P., 2002. Critical aspects of sampling in mills and plants: a guide to understanding sampling audits. J. South Afr. Inst. Min. Metall. 102(8), 481–484.
Gy, P.M., 1982a. Sampling of Particulate Materials – Theory and Practice, Second ed.
Elsevier, Amsterdam.
Gy, P.M., 1982b. Sampling from high capacity streams. In: Proceedings of the First Australian International Bulk Materials Conference. The Institution of Engineers Australia, Brookfield, Victoria, pp. 407–423.
Gy, P.M., Marin, L., 1978. Unbiased sampling from a falling stream of particulate material.
Int. J. Miner. Process. 5, 297–315.
Holmes, R.J., 1997. Sampling of iron ore process streams. In: Proceedings of the Iron Making Resources and Reserves Estimation Conference, 25–26 September 1997, Australasian Institute of Mining and Metallurgy, Melbourne, pp. 171–175.
Holmes, R.J., 2002. Sampling and measurement – the foundation of accurate metallurgical accounting, In: Proceedings of the Value Tracking Symposium, 7–8 October 2002, Brisbane, Australia, Australasian Institute of Mining and Metallurgy, Melbourne, pp. 101–107.
Holmes, R.J., 2004. Correct sampling and measurement – the foundation of metallurgical accounting. Chemometr. Intell. Lab. Syst. 74, 71–83.
ISO 12743, 1998. Copper, lead and zinc sulfide concentrates – sampling procedures for determination of metal and moisture content. International Organization for Standard- ization, Geneva.
Pitard, F.F., 1993. Pierre Gy’s Sampling Theory and Sampling Practice, Second ed. CRC Press Inc, FL.
Sampling procedures 19
Ralph J. Holmesobtained a BSc in Physics in 1967 and subsequently a PhD in 1972 from the University of Melbourne in mineral characterization. He joined the CSIRO Division of Mineral Physics in November 1971 to work on the application of nuclear techniques to the on-stream analysis and sampling of iron ore and other mineral commodities.
He currently manages the CSIRO Minerals Brisbane Laboratory and the Division’s Iron Ore Processing group, which conducts research in ore characterization, comminu- tion, beneficiation, agglomeration and quality control for the mining industry.
Dr Holmes has developed a range of nuclear techniques for on-stream and bulk anal- ysis of crushed ores and coal, includingIronscan, for which he received the inaugural AusIMM Mineral Industry Operating Technique Award in 1987. He received an inau- gural Standards Award from Standards Australia in 1993 and an Australian Clunies Ross National Science and Technology Award in 1998. Dr Holmes is a Fellow of the Australasian Institute of Mining and Metallurgy and the Australian Institute of Physics.
R.J. Holmes 20
Developments in Mineral Processing, Vol. 15 Mike D. Adams (Editor)
r2005 Elsevier B.V. All rights reserved.
21
Chapter 2
Mineralogical investigation of gold ores
S.L. Chryssoulisaand J. McMullenb
aAmtel, London, Canada
bBarrick Gold Corporation, Toronto, Canada
Mineralogical investigation is a critical and integral aspect of any pre- feasibility study as well as one of the quality control measures in the process optimization step (Gasparrini, 1993; Marsden and House, 1993). Minera- logical information must be considered in conjunction with the metallurgical testwork program results to ensure that appropriate processing methods are evaluated and that the optimum processing technology and flowsheet meth- ods are selected and incorporated into the final plant design. A table of mineral formulae is provided at the front of this book.
Mineralogical investigation of tailings and other streams from operational plants has two specific objectives. The first is to determine reasons why design efficiencies are not being achieved and the second is to provide insight for continued process optimization by identifying opportunities and the means to augment recovery (Chryssoulis, 2001). Gold deportment analyses also assist in setting realistic targets for tailings grade, which is the absolute measure of metallurgical performance.
A gold deportment study consists of two parts, the first involves a complete gold mineralogical distribution in which all forms and carriers of gold (for definitions see Section 1) are identified and quantified, while in the second the focus is on determining and ranking the causes for the gold losses. As each form and carrier of gold is independently assessed, the completeness of the gold mineralogical distribution is measured by the relative deviation of the mineralogical gold tally from the assayed value. A 10% deviation is considered acceptable for gold concentration in the range 0.02–1 g/t. This approach is considered more accurate and comprehensive than the diagnostic
DOI: 10.1016/S0167-4528(05)15002-9
leaching method (Tumily,et al., 1987), which is used more routinely as a first line of control and enables the relatively rapid turnaround of process-based leachability information.
The process mineralogy of gold is not limited to the gold minerals, submi- croscopic gold and their carriers, but also includes the study of gangue min- erals and other species that may affect gold processing, such as cyanicides.
1. GOLD MINERALOGY