Optimising sampling protocols via the heterogeneity ...

Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Optimising sampling protocols via the heterogeneity test: challenges in coarse gold mineralisation S. C. Dominy*1,2 and Y. Xie3 1. 2. 3.

Camborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UK Western Australian School of Mines, Curtin University, Bentley, WA 6102, Australia School of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, PRC

*Corresponding author, email [email protected]

Determination of the sampling constant is an important step when applying the Fundamental Sampling Error equation to optimise sampling protocols. The classic method for its determination is based on the heterogeneity test. In coarse gold-dominated mineralisation, the heterogeneity test sometimes provides an evaluation of the fine-gold background grade population heterogeneity, but understates that of the important highgrade coarse-gold component. This is because the total mass of fragments is too small to represent the full gold particle size distribution of the mineralisation. Despite this, single heterogeneity tests are often undertaken on deposits where the presence of coarse gold is ignored, not realised or understated. Resultant sampling and assaying protocols are frequently of poor quality and do not match the mineralisation characteristics. For coarse gold-dominated mineralisation, an empirical approach for sampling constant determination is recommended via direct estimation of the liberation diameter. Keywords: Theory of Sampling, Fundamental Sampling Error, Liberation diameter; Sampling optimisation, Heterogeneity testing, Coarse gold

Introduction The importance of high quality sampling during deposit evaluation and exploitation has been stressed by many authors (Pitard, 1993; Carrasco, Carrasco and Jara, 2004; Minnitt, 2007). Samples should be collected and prepared within the framework of the Theory of Sampling (Gy, 1979,1992; Pitard, 1993). For a sample to be representative it must be unbiased and precise. The precision of sampling protocols relates to the Fundamental Sampling Error (FSE), which can be estimated via the FSE equation (Gy, 1979). Broken rock sample protocol optimisation using the FSE equation, requires determination of the sampling constant (K; Gy, 1979). The most widely applied approach to determining K is the heterogeneity test (HT; Gy, 1979). The standard 50 or 100 piece test is applied across various commodity types including gold (Gy, 1979; Pitard, 1993; Carrasco et al., 2005; Magri, 2007). It is not unusual for a single HT to be used to represent an entire deposit or domain, without consideration of ore characteristics or variability. Mineralisation containing substantive quantities of coarse gold (>15% above 100 µm) is often typified by a high-nugget effect which represents variations in: (1) the in-situ size distribution of gold particles (including effects of gold particle clustering), and (2) gold particle abundance (Dominy, 2014a). Grade is generally correlated to gold particle size, although the relationships are complex (Dominy and Platten, 2007; Dominy et al., 2008). Higher grades often relate to abundant coarse gold and/or clustered gold particles. The sampling of coarse gold mineralisation is generally challenging and discussed further in Dominy et al. (2000) and Dominy (2014a).

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Gold mineralisation frequently displays evidence that fine- and coarse-gold particles may be part of separate paragenetic stages. In general, the fine gold particles are likely to be relatively disseminated through the orebody and responsible for a ‘background’ grade of between 0.5 g/t Au and 5 g/t Au (Dominy et al., 2008). The coarse particles are likely to be dispersed in nature and/or locally clustered, being critical to economic viability in lowgrade deposits. This paper reports on a unique investigation of HT variability in coarse gold-dominated mineralisation. A comparison is made between a number of repeat HT’s across four deposits. It links sample representivity to gold particle distribution, and in particular the critical effect of gold particle clustering. The study demonstrates that the use of the HT is inappropriate in coarse gold mineralisation.

Fundamental Sampling Error In the context of broken rock, the FSE is the smallest residual error that can be achieved even after homogenisation of a sample lot is attempted. When FSE is not optimised for each sub-sampling stage, it often becomes a major component of the sampling nugget variance (Pitard, 2007; Dominy, 2014a). The FSE is dependent upon the Constitution Heterogeneity (CH), which relates to sample weight, mineral fragment size and shape, liberation stage of the gold, gold grade, and gold and gangue density. The FSE can be theoretically estimated before the material is sampled, provided the sampling characteristics (e.g. K) embedded in the FSE equation are determined (Gy, 1979; Pitard, 1993). The FSE equation presented by Gy (1979,1992) is usually modelled as: σ2FSE = f g c λ dN3 (1/MS - 1/ML)

[1]

where σ2FSE = variance of the FSE; f = shape factor; g = granulometric factor; c = mineralogical factor; λ = liberation factor (where λ = {d/dN}0.5); d = liberation diameter; dN = nominal material size; MS = sample mass and ML = lot mass. For a full derivation of equation [1], the reader is referred to Gy (1979,1992) and Pitard (1993). A technical issue with the use of the original FSE formula is the numerical value of the power in the liberation factor, λ [1] (François-Bongarçon, 1998a, 1998b). Gy (1979) originally proposed a value of 0.5, though subsequently reported its limitations (Gy, 2004). This value gives reasonable results for base metal ores (Pitard, 2009); however it generally results in unrealistic values when applied to low-grade ores such as gold. The problem was addressed by François-Bongarçon (1998a, 1998b) who suggested a general model which replaces 0.5 with b, where b = (3 - α). Substituting this into the original equation [1], the following modified equation results: σ2FSE = f g c d3-α dNα ( 1/MS - 1/ML )

[2]

The parameter α can be experimentally determined for specific mineralisation using sampling tree-based methods, though for the HT approach a value must be assumed (François-Bongarçon and Gy, 2002; Minnitt and Assibey-Bonsu, 2010). FrançoisBongarçon (1993) reported values of α around 1.5, and Assibey-Bonsu (1996) listed values between 0.76 and 1.15. Afewu and Lewis (1998) reported values of 1.01 for low grade ores (5 g/t Au) and 1.13 for high grade ores (60 g/t Au), though both ores were characterised by fine gold (5 cm) and fine (10 g/t Au. For the bulk sampling programme, the dAu of 5000 µm was taken (Table 3). This was applied to bulk sample optimisation, where a 100 t primary lot was reduced to an 15 t sub-sample for processing (Johansen and Dominy, 2005). This yielded an FSE of ±10% at the 70% confidence level. If the original SHT results had been applied, a sample cut size of 0.2 t would have been taken. This sample mass would yield an FSE of ±95% at the 70% confidence level. The precision of the 15 t sub-samples was 90% (half absolute relative difference) within ±20%, indicating the split was valid. Essakane open pit, Burkina Faso Essakane is a sediment-hosted sheeted vein system. As part of an RC drilling programme undertaken during the feasibility study, a series of GHTs were undertaken to evaluate likely sampling protocols. RC rejects were chosen by domain and composited to yield a grade of around 2 g/t Au. Composites of 350 kg were selected from spatially distributed primary samples that averaged around 2 g/t Au. Each GHT comprised approximately 100 (N) groups of 30 (p) particles, or nearest number of p to achieve a mass of 50 g (Fig. 1B). Particles were randomly picked from screened primary composites, providing a dN size of 1 cm. Three sets of GHT 100 tests were taken across four lithological-based ore types. The GHTs were collected from intersections across the sheeted vein mineralisation. Individual tests for each lithology showed some variability (Fig. 4 and 5; Table 2). Composite GHT results across the four zones showed relatively minimal variability. However, historical knowledge (artisanal miners extracting gold by simple gravity methods), preliminary metallurgical testing (gravity recoverable gold values to 70%), geological observation (over 500 diamond and RC drill samples showing visible gold to 3 mm in size), screen fire assay results (>20% gold caught on the screen), and strong assay duplicate variability indicated the strong presence of coarse gold and thus the GHT results appeared unrealistic. As a result of the GHT findings, a series of metallurgical tests (including mineralogical work), screen fire assaying and processing of RC reject material via a laboratory Knelson concentrator was undertaken. These combined led to a dAu of 1200 µm being defined as the worst case scenario over the four mineralised domains (Table 3). Gwynfynydd mine, Wales, United Kingdom

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Mineralisation at Gwynfynydd comprises composite quartz-sulphide veins. Five 50 (1.5 kg) piece SHTs were undertaken on Chidlaw lode stope material. The material sampled was low-grade (4 g/t Au) run-of-mine ore. Individual fragments collected were quartz dominated to reflect the nature of the reef (>70% quartz). The low-grade ore was known to contain coarse gold, with up to 90% extractable by gravity (Dominy, 2014b). The tests yielded K values of between 85 to 960 g/cm1.5 (Table 2 and Fig. 6). Backcalculated d values ranged from 5 to 495 µm (Table 2). The composite 250 piece SHT yielded a K value of 3315 g/cm1.5 and d of 440 µm (Fig. 7). The tests show the potential precision issues with SHTs, given that SHT #1, #4 and #5 provide for relatively similar K values and SHT #1 a high d value. Of note is the mean grade of the tests which varies between 0.3 g/t Au and 27 g/t Au. This indicates that SHT #1 picks up more coarse gold compared to SHT #3 for example, as confirmed in screen fire assays. Field observation indicates discrete gold clusters are present. Laboratory gravity processing of grade control samples consistently verified the presence of coarse gold in the low-grade ore (Dominy, 2014b) In addition, two GHTs were collected from a surface stockpile and from the same ore zone as the SHTs. Some 500 kg of 5 cm to 10 cm ore fragments were collected, crushed to P90 -2 cm and screened to produce approximately 190 kg of 1 cm product. Two onehundred lots of 50 to 60 fragments were collected to gain a consistent group mass of 100 g. All samples were screen fire assayed in their entirety. Grade profiles for the two GHTs are given in Fig. 8. The tests yielded K values of 55 and 410 g/cm1.5. The back-calculated d values were 10 to 210 µm respectively. The composite 200 GHT yielded a K value of 685 g/cm1.5 and d of 195 µm. Assays of the entire three fractions are shown in Table 4, which shows grade heterogeneity between fractions. The HTs (SHT and GHT) generally recognised coarse gold, but understated the effect of spatially restricted clustering. Further field and laboratory studies confirmed that in the low-grade ore, gold typically clustered with a dclus of between 3000 µm and 8000 µm (Dominy and Platten, 2007; Dominy, 2014b). X-ray computed tomography confirmed the presence of clustered gold particles in hand specimens. For the low-grade ore domain, a dAu of 3000 µm was used (Table 3). Ballarat East mine, Ballarat, Victoria, Australia Mineralisation at Ballarat comprises composite quartz veins, which locally form complex stockwork-like zones. Two sets of 100 piece DHT tests were available for the Mako lode (Figure 9). These are based on half NQ2 core pieces of average length 35 cm, mass 0.85 kg and comprising >70% quartz. The tests yielded K values of 240 and 270 g/cm1.5 (Table 2). The back-calculated d values were 105 and 150 µm respectively. The composite yielded a K value of 275 g/cm1.5 and d of 135 µm (Table 2). An additional 500 piece DHT was extracted from the Mako database. These were whole NQ2 core pieces of average length 40 cm, mass 2.1 kg and comprising >70% quartz. The composite yielded a K value of 355 g/cm1.5 and d of 155 µm (Table 2). Within both drill core and underground faces, visible gold is common. Batch processing included recording of gold particle size in various fractions recovered from the plant. The dAu equivalent was around 3000 µm for 8 g/t Au ore. HT result implications for the case study sites

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

The sampling protocols applied at each case study are presented in Table 1. Values for dAu and d (back-calculated from HT results and estimated from metallurgical testing) are summarised in Table 3. Across Ballarat and Gwynfynydd, no substantive changes were made as the results reinforced existing approaches. At Ballarat whole core sampling and assaying continues support resource models. At Gwynfynydd, grade control was undertaken using mini-bulk sample processed through a laboratory gravity plant. At Bendigo, the results led to a revision of the feasibility bulk sample plant splitting protocol. This was validated by acceptable duplicate bulk sample precision results. Trial mining bulk lots were fed into a pilot plant with no sample splitting. Whole core sampling and assaying was ultimately used to support resource models produced during 2009 to 2011. The results at Essakane led to a further review and re-assay of RC sample rejects. LeachWELL assay (two by 1-kg) was introduced as part of the feasibility re-assay of RC and drill core rejects, and used for RC grade control drilling.

Discussion 

The case studies report an investigation into the HT approach applied to coarse gold mineralisation. The examples represent relative extremes in coarse gold mineralisation, and should not be extrapolated across all deposits. In the four cases, if the HT test results had been accepted then based on an understated K value, incorrect sampling protocols would have been applied.



The case study results indicate variability and under-call of K values from repeat tests (Tables 2 and 3). The HT is prone to relatively low precision and high bias, due to the very heterogeneity it aims to quantify. Results often provide an evaluation of the finer grained background gold population, approximating the d sensuo stricto. It does not represent the most influential part of the population (e.g. coarse gold dAu). A large sample mass is required to represent the gold particle size distribution, which may be 1000s kg.



The critical short coming of the HT approach is that it uses only one fragment size and then applies that value to all other fragment sizes. The selected fraction is unlikely to represent the true lot, and this is exacerbated in coarse gold-dominated ores. Comminution of coarse gold-ores liberates gold, which is often seen to concentrate into finer fractions (Table 4).



There remain questions over the definition and application of the liberation diameter. Parameters d and dAu have different meanings and effect on the estimation of FSE. In a fine-gold ore, the two values are more likely to be close and thus have a minimal effect on the optimal sampling approach. In coarse gold dominated ores, the values may be an order of magnitude different (Table 3), leading to different K values and required sampling approaches.



Characterising coarse gold mineralisation is a different problem to fine-grained gold deposits. A direct approach is required that evaluates the in-situ dAu. A crush-screen-concentration method can provide appropriate results (Gonzales and Cossio, 2007; Dominy et al., 2011). Dominy et al. (2010, 2011) suggest a staged approach involving: (1) initial rock and core observations; (2) collection and testing of mini-bulk samples; (3) coarse gold determination based on concentrates from stage (2); and (4) data integration to define gold particle size curves.

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Advanced mineralogical techniques such as QEMSCAN and Mineral Liberation Analyser (Lyman and Schouwstra, 2011), and high-resolution X-ray computer tomography (Dominy et al., 2012) may also be applied. 

Sample protocols should be reviewed on a scenario basis and accounting for the correlation of grade with dAu (or dclus). As a protocol progresses though comminution stages, consideration should be given to the change in dAu. Optimisation around the cut-off grade should be investigated as it may represent a worst case scenario. Where optimisation leads to specialist and potentially costly protocols, then a trade-off study should be undertaken where the FSE can be used as a proxy to financial loss (Pitard, 2009).



The HT approach is not completely disputed, given it can work relatively well for base metal ores (Pitard, 2004; Carrasco et al., 2005; Magri, 2007; Gonzales and Delgadillo, 2011; Dominy, unpublished data). Application must be considered in the light of mineralisation characteristics and likely data quality.

Recommendations 

The precursor to any sampling programme is characterisation via sampling for sampling (Dominy et al., 2010, 2011). The focus of characterisation is the determination of (a) the gold particle size range and (b) the dAu and/or dclus leading to the evaluation of K. Correlations between grade, dAu and/or dclus should be investigated. Careful review of drill core is a good start.



A first step in characterisation is to collect a 300-500 kg sample of run-of-mine ore (e.g. from stockpiles or mill feed belt) and crush to a P90 of -20 mm. The total crushed lot is then screened over two screens, for example 13 mm and 8 mm. The three individual size fractions are then rotary split down to around 8-10 kg (e.g. +13 mm, 8 mm to 13 mm and -8 mm) and pulverised for around six 1.5 kg screen fire assay. Screen fire assay is chosen to evaluate the gold particle size trapped on the screen, thus providing a clear indication of the presence of coarse gold. A large LeachWELL assay could also be applied, though would not yield the coarse gold information and requires fire assay of tails. It is recommended that if the grade difference between the fractions is less than one order of magnitude, then the HT approach may be valid (Table 4).



When dominant coarse gold is identified, actions can be taken to minimise sampling errors. Whole diamond core samples followed by whole core assays are a valid option. In the case of RC drilling, the run length can be reduced to 0.5 m to give a smaller primary sample. Whole core and RC composites can be assayed via screen fire assay (up to 2 kg mass) or LeachWELL (up to 5 kg). An alternative is to use laboratory gravity processing, where samples from 2-3 kg up to 250 kg can be processing in their entirety to effectively yield a zero FSE (Dominy, 2014b). With good laboratory practice, other sampling errors can also be minimised. Further details of coarse gold sampling and assaying approaches are given in Dominy (2014a).



Sampling programmes should always be tempered with an understanding of geological and gold particle size variability to maintain reality. The value proposition for good sampling is compelling. Coarse gold mineralisation will always have a higher inherent risk than other gold deposits and require a specialised approach.

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores



For coarse gold mineralisation, pilot testing (>1 t samples) and/or trial mining (>500 t) as part of the feasibility study are recommended to verify grade and metallurgical properties (Dominy and Petersen, 2005; Johansen and Dominy, 2005; Cintro et al., 2007).



This study highlights avenues for further reseach including: the relationship between α, ore type and its determination; clustering effects and its determination; the relationship between background grade/gold and high-grade coarse gold; the ratio at which coarse/fine gold becomes material; and alternate approaches to characterising coarse gold ores with respect of K.

Acknowledgements This work has benefited from the support of various exploration and mining companies, including: Bendigo Mining Ltd, Castlemaine Goldfields Ltd, Gold Fields Ltd and Welsh Gold PLC. Professor Richard Minnitt (University of Witwatersrand, RSA), the late Dr Allen Royle (University of Leeds, UK) and Professor Kim Esbensen (GEUS) are thanked for their advice. Journal reviewers are acknowledged for their constructive comments on the manuscript.

References Afewu, K. I. and Lewis, G. O. 1998. Sampling a run-of-mine mill feed – a practical approach, Journ. S. Afr. Inst. Min. Metall., 98, 299-304. Assibey-Bonsu, W. 1996. Summary of present knowledge on the representative sampling of ore in the mining industry, Journ. S. Afr. Inst. Min. Metall., 96, 289-293. Bazin, C., Hodouin, D. and Blondin, R. M. 2013. Estimation of the variance of the fundamental error associated to the sampling of low grade ores, Int. Journ. Min. Process., 124, 117-123. Carrasco, P. C., Carrasco, P. and Jara, E. 2004. The economic impact of incorrect sampling and analysis practices in the copper mining industry, Chemometrics Intell. Lab. Sys., 74, 209-214. Carrasco, P., Carrasco, P., Campos, M., Tapia, J. and Menichetti, E. 2005. Heterogeneity and Ingamell's tests of some Chilean porphyry ores, Proc. World Conf. Sampling and Blending, 139-150, Melbourne, Australasian Institute of Mining and Metallurgy. Cintra, E. C., Scabora, J. A., Viegas, E. P., Barata, R. and Maia, G. F., 2007. Coarse gold sampling at Sao Francisco mine, Brazil, Proc. World Conf. Sampling and Bending, 187198, Porto Alegre, Fundacao Luiz Englert. Dominy, S. C. 2014a. Predicting the unpredictable – evaluating high-nugget effect gold deposits, Mineral Resource and Ore Reserve Estimation, Monograph 30, 659-678, Melbourne, Australasian Institute of Mining and Metallurgy. Dominy, S. C. 2014b. Effects of sample mass on gravity recoverable gold test results in low-grade ores, Appl. Earth Sci. (Trans IMM B), 123, 234-242. Dominy, S. C., Annels, A. E., Johansen, G. F. and Cuffley, B. W. 2000. General considerations of sampling and assaying in a coarse gold environment, Appl. Earth Sci. (Trans IMM B), 109, 145-167.

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Dominy S. C. and Petersen J. S. 2005. Sampling coarse gold-bearing mineralisation developing effective protocols and a case study from the Nalunaq mine, southern Greenland, Proc. World Conf. Sampling and Blending, 151-165, Melbourne, The Australasian Institute of Mining and Metallurgy. Dominy, S. C. and Platten, I. M. 2007. Gold particle clustering - a new consideration in sampling applications, Appl. Earth Sci. (Trans IMM B), 116, 130-142. Dominy, S. C., Xie, Y. and Platten, I. M. 2008. Gold particle characteristics in narrow vein deposits: implications for evaluation and metallurgy, Proc. Narrow Vein Mining Conf., 91104, Melbourne, Australasian Institute of Mining and Metallurgy. Dominy, S. C., Platten, I. M. and Xie, Y. 2010. Determining gold particle size in gravity ores for sampling and metallurgical characterisation – discussion and test protocol, Proc. Gravity Gold Conf., 83-95, Melbourne, Australasian Institute of Mining and Metallurgy. Dominy, S. C., Platten, I. M., Xie, Y. and Minnitt, R. C. A., 2011. Underground grade control protocol design: case study from the Liphichi gold project, Larecaja, Bolivia, Appl. Earth Sci. (Trans IMM B), 119, 205-219. Dominy, S. C., Platten, I. M., Howard, L. E., Bell, R-M., Xie Y. and Minnitt, R. C. A. 2012. Determination of the sampling liberation diameter in a high-grade coarse gold ore by high-resolution X-ray computed tomography, Proc. Sampling Conf., 161-169, Melbourne, Australasian Institute of Mining and Metallurgy. François-Bongarçon, D. M. 1993. The practice of sampling theory of broken ores, CIM Bull., 86, 75-81. François-Bongarçon, D. M. 1998a. Gy’s formula: conclusion of a new phase of research, Austr. Inst. Geosci. Bull., 22, 1-10. François-Bongarçon, D. M. 1998b. Extensions to the demonstration of Gy’s formula, Explor. Min. Geol., 7, 149-154. François-Bongarçon, D. M. and Gy, P. M. 2002. The most common error in applying Gy’s formula in the theory of mineral sampling and the history of the Liberation factor, Journ. S. Afr. Inst. Min. Metall., 102, 475-479. Geelhoed, B. 2011. Is Gy’s formula for the fundamental sampling error accurate? Experimental evidence, Mins Eng., 24, 169-173. Gonzales, P. and Cossio, S., 2007. A review of sampling protocol for a gold ore based on liberation study, Proc. World Conf. Sampling and Blending, 163-174, Porto Alegre, Fundacao Luiz Englert. Gonzales, P. and Delgadillo, J. A. 2011. Sampling protocols from heterogeneity tests on gold, copper, and polymetallic ores of Mexico, Proc. World Conf. Sampling and Blending, 113-122, Santiago, Gecamin. Gy, P. M. 1979. Sampling of Particulate Materials, Amsterdam, Elsevier. Gy, P. M. 1992. Sampling of Heterogeneous and Dynamic Material Systems, Amsterdam, Elsevier.

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Gy, P. M. 2004. Sampling of discrete minerals – a new introduction to the theory of sampling I: Qualitative approach, Chemometrics Intell. Lab. Sys., 74, 7-24. Johansen, G. F. and Dominy, S. C. 2005. Development of sampling protocols at the Bendigo gold project, Australia, Proc. World Conf. Sampling and Blending, 175-183, Melbourne, Australasian Institute of Mining and Metallurgy. Lyman, G. J. and Schouwstra, R. 2011. Use of scanning electron microscope to determine the sampling constant and liberation factor for fine materials, Proc. World Conf. Sampling and Blending, 89-103, Santiago, Gecamin. Magri, E. J. 2007. Some experiences in heterogeneity tests and mine sampling, Proc. World Conf. Sampling and Blending, 329-348, Porto Alegre, Fundacao Luiz Englert. Minnitt, R. C. A., 2007. Sampling: the impact on costs and decision making, Journ S. Afr. Inst. Min. Metall., 107, 451-462. Minnitt, R. C. A., Rice, P. M. and Spangenberg, C., 2007. Part 2: Experimental calibration of sampling parameters K and alpha for Gy’s formula by the sampling tree method, Journ. S. Afr. Inst. Min. Metall., 107, 513-518. Minnitt, R. C. A., 2014. A comparison of two methods for calculating the constants K and α in a broken ore, Proc. Sampling Conf., 165-178, Melbourne, Australasian Institute of Mining and Metallurgy. Minnitt, R. C. A. and Assibey-Bonsu, W. 2010. A comparison between the duplicate series method and the heterogeneity test as methods for calculating the sampling constants, Journ. S. Afr. Inst. Min. Metall., 110, 251-268. Minnitt, R. C. A., Francois-Bongarcon, D. F. and Pitard, F. F. 2011. Segregation free analysis for calibrating the constants K and α for use in Gy’s formula, Proc. World Conf. Sampling and Blending, 133-150, Santiago, Gecamin. Pitard, F. F. 1993. Pierre Gy’s Sampling Theory and Sampling Practice, Boca Raton, CRC Press. Pitard, F. F. 2004. Effects of residual variances on the estimation of the variance of the fundamental error, Chemometrics Intell. Lab. Sys., 74, 149-164. Pitard, F. F. 2007. The in-situ nugget effect: a major component of the random term of a variogram, Proc. World Conf. Sampling and Blending, 91-110, Porto Alegre, Fundacao Luiz Englert. Pitard, F. F. 2009. Pierre Gy’s Theory of Sampling and C. O. Ingamells Poisson Process Approach: Pathways to Representative Sampling and Appropriate Industry Standards. PhD Thesis, Aalborg University, Esberg, Denmark. Royle, A. G. 1989. Splitting gold assay pulps containing coarse gold, J. Leeds Univ. Mining Assoc., 89, 63-68. Royle, A. G. 1991. Safe sampling formulae for gold deposits, Min. Tech. (Trans IMM A), 100, 84-86.

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

FIGURES 1 (A) single fragment for a 0.5 kg 50 piece SHT; and (B) 30 fragments for a 100 group GHT

(C) SHT fragments can be collected one-by-one from stockpiles or the composite crushed for the GHT method; and (D) consistently sized drill core lengths can be used for the DHT approach or a composite crushed for the GHT.

(C)

(D)

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

2 Three 50-piece 2.5 kg SHT grade profiles for the Bendigo St Anthony's reef

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

3 Composite 150-piece 2.5 kg SHT grade profile for the Bendigo St Anthony's reef. Displays a typical HT curve where many (in this case 93%) show grades more consistent with the low-grade background mineralisation (see individual curves in Fig. 2)

4 Three 100 group (30 particle) GHT grade profiles for Essakane oxide zone mineralisation

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

5 Three 100 group (30 particle) GHT grade profiles for Essakane fresh zone mineralisation

6 Five 50-piece 1.5 kg SHT grade profiles for the Gwynfynydd Chidlaw lode

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

7 Composite (five 50-piece 1.5 kg SHTs from Fig. 6) SHT grade profile for the Gwynfynydd Chidlaw lode

8 Two 100 group (60 particle) GHT grade profile for the Gwynfynydd Chidlaw lode. The highest grade on GHT2 (red curve) is 1456 g/t Au

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

9 Two 100-piece 0.85 kg DHT grade profiles from half NQ2 core for the Ballarat mine 450 400

Grade (g/t Au)

350 300 250 200 150 100 50 0 1

7

13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 Consecutive HT sample

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Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

TABLES Table 2 HT test results summary for case studies Kangaroo Flat Test #

Ore type

N

Grade

Fragment mass

Total mass

K

d

SHT1

ROM

50

73

2.5

125

325

460

SHT2

ROM

50

1

2.5

125

105

15

SHT3

ROM

50

34

2.5

125

1255

685

Composite SHT

ROM

150

36

2.5

375

630

450

Ballarat East Test #

Ore type

N

Grade

Fragment mass

Total mass

K

d

DHT1A

ROM

100

10

0.85

85

240

105

DHT1B

ROM

100

16

0.85

85

270

150

DHT2 Composite DHT(1A+B)

ROM

500

13

2.1

1050

355

155

ROM

200

13

0.85

170

275

135

Essakane Test Group # Composite GHT1 Composite GHT2 Composite GHT3 Composite GHT4

Ore type

N

Grade

Fragment group mass

Total composite mass

K

d

Oxide

300

8.9

50 g

15

40

16

Transition

300

5.3

50 g

15

24

14

Fresh

300

1.7

50 g

15

104

12

Fresh

300

1.3

50 g

15

38

5

Gwynfynydd Test #

Ore type

N

Grade

Fragment mass

Total mass

K

d

SHT1

LROM

50

27

1.5

75

960

495

SHT2

LROM

50

1

1.5

75

85

10

SHT3

LROM

50

4

1.5

75

240

60

SHT4

LROM

50

0.5

1.5

75

100

5

SHT5

LROM

50

0.3

1.5

75

110

5

Composite GHT

LROM

200

9.5

100 g

20

685

195

Composite SHT LROM 250 6.6 1.5 375 3315 440 Key: Ore type - ROM, run of mine ore or LROM, low-grade run of mine ore; Grade (g/t Au), this is the grade of the HT sample set; Fragment mass (kg); Total mass (kg); K (g/cm1.5) and d (µm); Composite results are composite of all individual tests for that case study.

19

Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Table 3 Comparison between HT and test work results Kangaroo Flat (1)

K

Composite SHT

36

630

450

-

-

Pilot plant

8(ROM)

240 000

-

10 000

-

Test work

8(ROM)

68 000

-

5000

350

(6)

dAu

(3)

Grade

(5,8)

HT d

(2)

Test

Est. d

Ballarat East (1)

K

DHT (highest case K)

13

355

155

-

-

8(ROM)

40 000

-

3000

100

Process plant

dAu

(3)

Grade

(5)

HT d

(2)

Test

Est. d

Essakane (1)

K

GHT (highest case K)

1.7

104

12

-

-

2.5(ROM)

40 000

-

1200

125

Test work

dAu

(3)

Grade

(7)

HT d

(2)

Test

Est. d

Gwynfynydd (1)

HT d

(2)

dAu

(3)

Test

Grade

K

Est. d

Composite SHT

6.6

3315

440

-

-

Composite GHT

9.5

685

195

-

-

(5)

Test work 4(LROM) 107 000 3000 250 Key: Ore type - ROM, run of mine ore or LROM, low-grade run of mine ore; Grade (g/t Au); K (g/cm1.5); All d and dAu values in microns; Composite results are composite of all individual tests for that case study. (1)HT d back-calculated from HT results; (2)dAu determined from experimental studies; (3)Est. d sensuo stricto liberation diameter determined from experimental studies; (5)based on extensive bulk sampling and trial mining across different grades; (6)conservative estimate of dAu based on field observation and gold particle yields from processing ROM grade batches; (7)dAu via gravity test work; (8) high dAu based on variable grade batches through the pilot plant, including high-grade lots with very coarse gold.

20

Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

Table 4 Screen analysis of Gwynfynydd and Bendigo ores Fraction >13 mm 8-13 mm 100 mm 25-100 mm 8-25mm 100 µm >1000 µm >2500 µm 80

60

10

ROM grade (g/t Au) 8

Sampling approach 



Ballarat East, Australia [underground, operating]

60

30

10

8





Essakane, Burkina Faso [open pit, operating]

40

10

2

1.5





Gwynfynydd, Wales, UK [underground, defunct]

60

20

5

4



Feasibility: o 100 t development bulk samples processed in 1.5 tph gravity plant o 100 kg grab mini-bulk samples processed in laboratory gravity unit o Chip-channel face sampling of faces and fire assay o Diamond drilling with half core samples and whole-sample screen fire assay Production: o Diamond drilling with whole core samples and whole-sample screen fire assay (used in resource model) o Chip-channel face sampling of faces and fire assay (not used in resource model) o Proxy-based indicator evaluation of grade Feasibility: o Various approaches trialled ranging from half core fire assay, through to half and whole core LeachWELL o Testing of core and face whole-sample analysis by laboratory gravity unit Production: o Diamond drilling with whole core samples and whole sample LeachWELL assay (used in resource model) o Face chip samples with whole sample LeachWELL assay (not used in resource model) Feasibility: o RC reject processing in laboratory gravity plant o Large sub-samples from RC via LeachWELL o Drilling with whole core samples and LeachWELL assay Production: o Resource and grade control sampling utilising 1 m RC composites with LeachWELL assays Production: o Up to 25 t development/stope bulk samples batch processed in 34 tph gravity plant o 50-100 kg face panel samples processed in laboratory gravity unit o Sludge sampling of air-leg holes, after the logging of rock chips the sludge was processed through the laboratory gravity unit

1

Dominy & Xie: Heterogeneity Testing of Coarse Gold Ores

1