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By J Jackson, D C. Curry, A C. Keith

Australian Bureau of Statistics (ABS) data shows that since 2006 the balance of capital costs associated with mine development has become weighted greater than 75 per cent to enabling infrastructure and less than 25 per cent on process plant, equipment and machinery. The well-developed mine planning techniques including pit optimisation and scheduling and process plant design and optimisation have typically proceeded in a linear fashion from geology, mine planning, through processing, with some iterations back to the mine. Only then is attention paid to planning and costing of enabling infrastructure in any detail.Optimisation has typically involved developing cut-off grades, mine plans and schedules and ore processing that produces maximum economic ore. Infrastructure has then been sized æto suitÆ the mining and processing core business drivers.What the ABS data, together with global trends, indicates is that infrastructure can no longer be an afterthought if miners wish to achieve robust project value estimates, realistic ore to market costing and resource statements based on achievable economic cut-off grades.In addition, with such a large proportion of the costs originating from non-mining or processing activities, a mining operation can only be truly optimal if these aspects are given due consideration in the mine design stages, based on quality geometallurgical inputs so that the size and cost of enabling infrastructure is optimised to maximise project value.This paper outlines an iterative holistic approach to mining project development, which integrates the geometallurgical approach and enables infrastructure planning into project design and evaluation. It presents case studies showing reduced overall costs, increased net present value (NPV) and reduced project delivery timelines.CITATION:Curry, D C, Keith, A C and Jackson, J, 2013. Is a 2.5 per cent success rate good enough? Traditional mine development methods have the tail wagging the dog, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 113-128 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By D David

Geometallurgy is often a misunderstood and poorly defined concept. The first thing the paper will attempt is to provide a definition of geometallurgy. Ultimately this paper has been written to provide guidance to geologists, mining engineers and processing professionals as to what geometallurgy means in the crucial early phases of a potential mining project between the time of discovery and the time of commencing construction, should this occur. The paper covers the options available for conducting a geometallurgical study of a resource or orebody, appropriate to the level of definition required in the projectÆs development cycle. The paper will then describe how the geometallurgical information generated is subsequently used in calculations, planning and preparation of reports designed to inform and reassure stakeholders, such as the market. Ultimately in a successful project, appropriate options adopted in the development phase will form the basis of an ongoing geometallurgical program that links the major site disciplines for the good of the operation.CITATION:David, D, 2013. Geometallurgical guidelines for miners, geologists and process engineers - discovery to design, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 129-132 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By C V. Deutsch

"Geometallurgical variables often cause problems to conventional geostatistical workflows. There are many variables; some are compositional and some are non-additive. They often show: complex multivariate relationships undersampling relative to conventional grade variables unequal sampling; that is, all variables are not available at all data locations.A variety of approaches have been developed over the years, but geostatisticians remain mostly focused on modelling rock types and a few grade variables with an abundance of data. The problems are reviewed and a chained workflow is presented where appropriate techniques are employed in sequence to permit reliable spatial prediction of geometallurgical variables. The spatial models may be used to assess the value of additional data, for prediction of process performance, for improved mine planning and other optimisation tasks. The chained workflow will include data transformations such as ratios and normal scores that make the variables amenable to geostatistical modelling. Data imputation techniques to account for missing values are considered with special consideration to spatial correlation with the available data. Decorrelation techniques such as the principal components, min/max autocorrelation factors and projection pursuit multivariate transformation are employed to manage massively multivariate modelling. Full distribution modelling must be considered to avoid biases in the prediction of non-additive variables. The post-processing of geometallurgical models must be streamlined for robustness and efficiency. The precise workflow varies according to the specific purpose of the study. Guidelines and thoughts on best practice are presented.CITATION:Deutsch, C V, 2013. Geostatistical modelling of geometallurgical variables - problems and solutions, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 7-16 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By R Berry, J Hunt, T Kojovic

Geometallurgy aids the understanding of orebody variability through the integration of geological and processing information, thereby enabling spatial mapping of processing (eg comminution or separation) performance across a deposit. In order to do this, estimates of quantitative geometallurgical attributes are needed so that continuous downhole profiles can be generated for each attribute, providing vital data for the development of processing domains through geostatistical modelling. However, as traditional comminution tests are high cost and/or require large samples, current practice typically results in insufficient data density and distribution of comminution indices making it difficult to model and map deposit scale variability. The aim of this work was to find a method to estimate comminution indices based on data that is widely available at mine sites. This data includes mineralogy and chemistry of drill core samples, plus logging information such as lithology and alteration. Work to date indicates that comminution parameters such as semi-autogenous grinding (SAG) Power Index (SPI), Bond Work Index (BWI) and A*b (Julius Kruttschnitt Mineral Research Centre (JKMRC) drop weight test (DWT) Index) can be modelled using chemical and/or mineralogical data. The estimated hardness indices can then be propagated into the mine site database and used in the definition of processing domains that map inherent variability across a deposit. The estimates can thus provide geometallurgical inputs for spatial modelling, mine planning and optimisation initiatives.CITATION:Hunt, J, Kojovic, T and Berry, R, 2013. Estimating comminution indices from ore mineralogy, chemistry and drill core logging, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 173-176 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By G J. Harbort, K Lam, C Sola

The relationship between the geology of porphyry copper deposits and their processing performance is an area of interest. Being able to predict comminution properties of the ore from physical characteristics and geological descriptions would allow an increase in the precision of capital cost estimates, operating cost estimates and throughput rates. This geometallurgical approach would reduce the requirements for expensive comminution tests.As the comminution circuit is the highest capital cost item in the plant and a possible throughput bottleneck, understanding the variability in hardness within the orebody is critical. A geometallurgical model allows calculation of ore hardness values in mining blocks from ore characterisation data. This model subsequently uses a combination of simulation and power-based approaches to relate ore hardness and flotation feed size to grinding circuit throughput.This paper reviews the geometallurgical models developed for seven porphyry copper deposits and discusses the strengths and shortfalls of the methodology and similarities and differences between the different deposits.CITATION:Harbort, G J, Lam, K and Sola, C, 2013. The use of geometallurgy to estimate comminution parameters within porphyry copper deposits, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 217-230 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By Y Akiti, J Moller, E Esper, R Rugolo, A Pains

"Morro do Ouro Mine is a high tonnage/low-grade mine located in Paracatu, Minas Gerais State, Brazil. The mines move around 55 Mt of ore per year at an average grade of 0.4 g/t. The auriferous mineralisation of Morro do Ouro is related to hydrothermal fluids rich in arsenic (As), gold (Au), lead (Pb) and zinc (Zn). These percolated along favourable structures contained within phyllites of Upper Proterozoic age and defined a mineralised megaboudin which outcropped with 4 km extension and up to 2 km in width. The litologies in the interior of this structure are typically more deformed, sericitised and sulfidised, and exhibit the development of quartz boudins in the centre of the more deformed zones where are found the higher Au grades and the coarser sulfide crystals. Gold is preferentially associated with arsenopyrite, mainly occurring in fractures or aggregations of crystals and is rarely in solid solution or refractory. Over 90 per cent of the gold contained in the sulfide ore is free or extractable by cyanidisation. The current mineral reserve is 17.9 Mt at 0.403 g/t published at the end of 2012.In order to get a good grade estimation that represents the orebody more accurately a solids methodology was used to distinguish the different orebodies. Before 2011 the orebodies were worked with two domains relating to the weathered mantle. The B1 ore, which is oxidised, is located at the top of mineralisation, and is used to feed Plant 1. Underneath B2 ore, which is fresh sulfide bearing, represents over 30 years of production in Plant 2.In order to improve the predictability of gold grade estimation in geological modelling and to get a better predicting behaviour of each domain on the deposit, studies were carried out in which it was possible to show a correlation between elements and the mineralisation. One strong correlation and spatial distribution between Au and As, As and sulfur (S), Au and Pb, Au and Zn were found.Based on geochemistry, mineral correlations, amount of sulfide, structural deformation, texture of sulfides and the daily experience of the mine, it was possible to create solids that individualised bodies with similar mineralogical and chemical characteristics using the parameters listed above.After 2011, a new modelling concept was proposed and built with 11 different domains, compared with the previous, and with two more parameters: recovery acid neutralised capacity (ANC).Each of these bodies have different behaviours in mineral processing, like flotation and metallurgy. For example, bodies with pyrrhotite bring problems in the flotation, bodies with high arsenic do not recover well, bodies with high As with coarse texture have good recovery, bodies with fine texture do not have good adherence in production.In the present state of knowledge, protocols are being developed for bench testing to predict the recovery of each geochemical domain aiming to include these in the geological model for the parameter recovery. It is intended to create a field throughput in the model of ounces per hour, from each block of each domain to better predict the production, using the parameter recovery, Au and Bond Work Index (BWI).CITATION:Esper, E, Rugolo, R, Moller, J, Akiti, Y and Pains, A, 2013. Morro do Ouro geological model with a metallurgical view, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 67-74 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By K S. Smith, J Woodhead, K Olson Hoal

Mineralogy is the link between ore formation and ore extraction. It is the most fundamental component of geomet programs, and the most important aspect of a life-of-project approach to mineral resource projects. Understanding orebodies is achieved by understanding the mineralogy and texture of the materials, throughout the process, because minerals hold the information required to unlock the value they contain. Geomet mineralogy programs absolutely require the appropriate expertise and at least three steps of mineral characterisation prior to using semi-automated or other methods: field examination, thorough core logging, and optical microscopy. Economic geological inputs for orebody characterisation are necessary for orebody understanding, and are exemplified by current research in the Zambian Copperbelt, where revised sequence stratigraphy and understanding of alteration, metasomatism and metamorphism can be used to predict topical issues at mine sites. Environmental inputs for sustainability characterisation are demonstrated by recent work on tailings from the Leadville, Colorado, USA area, including linking mineralogy to water quality issues. Risk assessments need to take into account the technical uncertainties around geological variability and mineral extractability, and mineralogy is the only metric that can be used to make this risk contribution.CITATION:Olson Hoal, K, Woodhead, J and Smith, K S, 2013. The importance of mineralogical input into geometallurgy programs, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 17-26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By F Minz, P Lamberg, A Mwanga, C Lund, C Wanhainen, M Amiri Parian, J Rosenkranz

A geometallurgical model is currently built in two different ways. The first and the most common way relies on geometallurgical testing, where a large number of samples are analysed for metallurgical response using small-scale laboratory tests, eg Davis tube testing. The second, mineralogical approach focuses on collecting mineralogical information over the orebody and building the metallurgical model based on mineralogy. At Lules University of Technology, Sweden, the latter method has been adopted and taken further in four ongoing PhD studies. The geological model gives modal composition by the help of element-to-mineral conversion and Rietveld X-ray diffraction. Texturally, the orebody is divided into different archetypes, and liberation measurements for each of them are carried out in processing fineness using IncaMineral, a SEM-based technique. The grindability and liberation spectrum of any given geological unit (sample, ore block, domain) are extrapolated from the archetypes. The process model is taken into a liberation level by mass balancing selected metallurgical tests using the particle tracking technique. The approach is general and can be applied to any type of ores. Examples of ongoing studies on iron and massive sulfide ores are given.CITATION:Lamberg, P, Rosenkranz, J, Wanhainen, C, Lund, C, Minz, F, Mwanga, A and Amiri Parian, M, 2013. Building a geometallurgical model in iron ores using a mineralogical approach with liberation data, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 317-324 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By K C. Runge, E Tabosa, A Jankovic

Flotation recovery in geometallurgical modelling is usually predicted based on relationships developed from batch flotation testing of different ore types. These batch flotation tests are usually performed at a constant set of operating conditions and at a fixed feed grind size P80. Usually the laboratory feed grind P80 is that which is expected to be produced in the full-scale flotation circuit for that particular ore type.Flotation recovery will be a strong function of the valuable mineral particle size distribution, with lower recovery of ultra-fines due to poor flotation kinetics, optimum recovery for the intermediate sized particles and lower recovery for the coarser particles due to poorer liberation of this fraction. This valuable mineral particle size distribution is not characterised by the solids P80 parameter alone. The proportion of material in each class will also be a function of the slope of the size distribution and the degree of preferential grinding of the valuable mineral in comparison to the total mass of the ore.This paper will demonstrate (through example) how these other size distribution parameters can change with a change in grinding technology, the size and operating conditions used in a grinding unit and the characteristics of the classification technology used in conjunction with the grinding unit. Case studies will be presented that demonstrate how this can result in these parameters being very different in laboratory testing to that produced in the full-scale comminution circuit. A rule of thumb that laboratory rod milling rather than ball milling produces a size distribution most similar to that of the full-scale grinding circuit will be challenged. These differences can result in a significant change in flotation recovery. It is therefore important to consider these parameters when developing a laboratory geometallurgical program, to enable more accurate prediction of the flotation recoveries that will be achieved in the full-scale process.CITATION:Runge, K C, Tabosa, E and Jankovic, A, 2013. Particle size distribution effects that should be considered when performing flotation geometallurgical testing, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 335-344 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By J E. Everett, K Jupp, T J. Howard

Simulation modelling is a practice commonly used in the mining industry to evaluate alternative process designs. Such modelling is typically undertaken as an optimisation study to increase the efficiencies, productivity and product quality of operating mines. In this situation, real short-term grade variability data of extracted ore are available from production records as input data into the simulation.There is also a need for simulation modelling to be performed before mines are approved for construction to clarify the grade variability characteristics that can be expected from the operating mine and assist in the optimisation of the process design. In this situation no historical short-term grade variability data are available. To achieve meaningful and reliable results from a simulation it is necessary to have input data for the ore to be extracted from the pits, representative of the short-term grade variability that would be expected for the operating mine.This paper describes an example of a path taken to generate realistic input data.A method described as composite cut-off criterion was used to distinguish ore from waste, which gave substantially greater recovered tonnage at target grade compared to the conventional quadrant cut-off grade criteria.The only data available for the project was resource model data in the form of kriged block models, which are known to underestimate true ore grade variability. To achieve realistic results from the simulation it was essential to increase this variability while maintaining the accurate average grades. Areas of certain deposits that were modelled using both kriging and conditional simulation estimation techniques were quantitatively compared to establish the comparative variance and the kriged data was modified to match the conditionally simulated variance.A realistic mining model was generated via a process of discretisation and regularisation of the resource blocks. Quantitative assessment demonstrated that this method adequately compensated for ore dilution and that adjustment for ore loss was not required due to an ore skin surrounding the edge blocks.The conditioned data was then used to generate a schedule of daily mine extraction, considering grade variability, tonnage, equipment constraints and extensive blended-in-blended-out precrusher stockpiles to feed into the process design simulations.For the precrusher stockpiles a number of alternative allocation criteria were examined for ore being extracted from the pits to identify the best method in achieving reduced variability through the daily scheduling system. The study concluded that a single analyte separation criterion produced acceptable variability with minimal complexity.The blending efficiency of manually stacked and reclaimed precrusher stockpiles was studied to determine a realistic blending efficiency within the pile. A recommended method of building and reclaiming was determined to give maximum blending efficiency.Finally, the data was used as input into process design simulation models; simulation from crusher feed to shiploading demonstrating that control of shipment grade variability was achievable and that the conditioning of the data delivered realistic results.CITATION:Jupp, K, Howard, T J and Everett, J E, 2013. Generating synthetic data for simulation modelling in iron ore, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 231-238 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By B J. Beven, A Vatandoost, J Young, S Campbell-Hardwick

The intrinsic value of iron ore depends on its physical and chemical characteristics. For example, silica and alumina are unwanted elements, downgrading iron grade and adversely affecting high temperature processing, attracting penalties in smelter contracts. For this reason, an informed knowledge of processing characteristics and product quality of the ore is valuable and cost effective during mine planning and processing.Ore variability is a significant factor that affects metallurgical behaviour and efficiency of ore processing equipment. Ore of sufficient chemical and physical quality needs to be modelled, mined, processed and usually blended. Feed and product assays are commonly used to assess potential ore upgradability. However, assays alone cannot be all informative of actual processing response given the variability of the physical properties of the ore.This study investigates the potential benefit of implementing a geometallurgical approach during the commissioning stage of the Kings deposit, part of the Solomon Iron Ore project in Western Australia. Kings drill hole database information, ie geological, textural and geochemical data, together with the results of metallurgical test work were used for geometallurgical analysis and modelling. Three main ore types were identified at Kings, namely channel iron deposit (CID), bedded iron deposits (BID) and Detrital Iron Deposit (DID). Additional classifications were utilised to better characterise these units in terms of their physical properties.Bulk sampling for each ore type was carried out across the deposit for metallurgical testing. Multivariate statistical models were developed for prediction of product quality for each geometallurgical unit. A new approach for modelling yield based on ore upgrade factors is introduced. These models were then applied to the Kings regularised mining model to assess product quality across the mining blocks and to plan product stockpiling and blending strategies.CITATION:Vatandoost, A, Beven, B J, Campbell-Hardwick, S and Young, J, 2013. A geometallurgical approach for iron ore product evaluation, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 259-266 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By D L. Reid, G Nwaila, J Petersen, J-P Franzidis, Y Ghorbani, M Becker, F C. de Beer, L C. Bam

Traditional methods of gold extraction have involved comminution and processing via cyanide leaching, all of which are associated with energy, cost and environmental implications. Subsequently, numerous opportunities for improvement and optimisation strategies in gold mining and processing have been explored, including heap leaching, which has significantly lowered comminution costs. This paper explores the effect of the more energy efficient high-pressure grinding rolls (HPGR) on the comminution behaviour (especially on the crack density) and cyanide leaching performance of laboratory reactors study on run-of-mine gold ore comprising the Ventersdorp Contact Reef (VCR) and the Elsburg Reefs (ER), sourced from Carletonville in the Witwatersrand Basin in South Africa. The ore was comminuted using HPGR at three different pressure settings (120, 90 and 60 bar). Large (-16/+11.2 mm) and small (-5.6/+4 mm) particles of the HPGR product where then mineralogically characterised using optical microscopy, quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) and X-ray computer tomography (CT) before cyanidation. The results of the leach experiments indicated a correlation between gold extraction, particle size and crack density. Mineralogical characterisation of the ore indicates that the Fe-sulfides present in the VCR are likely to be more reactive than those in the ER, thus having a more favourable influence on gold cyanidation. Overall, the results show promise for the heap leaching of Witwatersrand gold ores prepared using HPGR and demonstrate the value of a multi-disciplinary geometallurgical approach.CITATION:Nwaila, G, Becker, M, Ghorbani, Y, Petersen, J, Reid, D L, Bam, L C, de Beer, F C and Franzidis, J-P, 2013. Morro do Ouro geological model with a metallurgical view, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 75-84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By T Muzondo, C Prins, D De Vaux, R Schouwstra

The Mogalakwena Platinum Mine in the northern limb of the Bushveld Complex is Anglo American PlatinumÆs only open cast operation exploiting the Platreef. The Platreef, which extends along the basal contact of the Bushveld Complex, is geologically and mineralogically a much more complex orebody than the Merensky and UG-2 reefs. Changes in the footwall and the genesis of the Platreef translate into a number of rock types being present. These rock types vary in hardness and recovery potential and present challenges to metallurgical staff trying to optimise the concentrator. A true understanding of the implications of treating these rock types is required if the maximum value from this orebody is to be obtained.In order to more accurately forecast production and incorporate ore variation in the mine plan and comminution and flotation circuits, a geometallurgical approach to managing the operation has been used and is being further developed.CITATION:Schouwstra, R, De Vaux, D, Muzondo, T and Prins, C, 2013. A geometallurgical approach at Anglo American PlatinumÆs Mogalakwena Operation, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 85-92 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By J Jasper, L Koroznikova, J Begelhole

This paper outlines a comparison of heavy liquid and heavy suspension separation methods for iron ore characterisation.As part of Arrium MiningÆs program to improve its knowledge of ore types being processed in its two hematite ore beneficiation plants (OBP), metallurgical evaluation of hematite feed for the upgrading process has become a major focus.Iron ore deposits almost always contain more than one valuable (and relatively dense) iron mineral. Iron ores are found with a range of iron contents, giving rise to density variations.At present the industry relies on heavy liquid separation techniques for the evaluation of iron ore samples arising from exploration, mining or metallurgical processes. There are only a few high-density liquids available, which are both high-cost and highly toxic.Low-toxicity solutions that can be utilised at relative densities up to 3.0 have been developed. However, highly-toxic organic liquids are required presently to achieve relative densities beyond 3.0.Bromoform which has a specific gravity (SG) of 2.89, and diiodomethane (SG 3.31) are commonly used; both present significant health and safety hazards.æClericiÆs solutionÆ (mixtures of thallium formate and thallium malonate) provide liquids having specific gravities between 4.0 and 5.0. ClericiÆs solution is highly toxic and testing is currently conducted by a limited number of laboratories worldwide.An alternative to ClericiÆs solution and organic liquids is a low-toxicity, high-SG, suspension technique, which has been demonstrated successfully for heavy mineral sands. This heavy suspension method employs mixtures of fine tungsten carbide particles in lithium heteropolytungstate (LST) solutions.Heavy liquid separation is not commonly used as part of routine iron ore feed characterisation due to the expensive, toxic and time consuming nature of the technique. Our results show that the heavy suspensions method can achieve low-cost, low-toxic separation and are outlined and results compared with results using ClericiÆs solution presented.Heavy suspension technique provides a theoretical/absolute separation of a particular sample. By placing an iron ore sample in a suspension of a particular density, it produces two products: a sink fraction and a float fraction. As iron oxides-hydroxyoxides are denser than the gangue minerals associated with the ore, particles that have high iron content will sink and the particles with gangue association will float. This process is repeated over several densities, thus also enabling separation of the constituent iron ore phases. A theoretical grade and a theoretical mass recovery can be calculated. With these calculations, a grade-mass recovery curve can be constructed for any element that is of interest.This type of characterisation can be used to either prepare OBP feed-piles of known processing characteristics, or to benchmark the performance of the process against what can be theoretically achieved on a continuous basis.CITATION:Begelhole, J, Jasper, J and Koroznikova, L, 2013. Application of the heavy suspension technique for ore beneficiation plant feed characterisation from the Southern Middleback Ranges, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 269-278 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By M I. Pownceby, S Bhargava, F Charalambous, S McMaster, R Ram, J Tardio

"A key component of any geometallurgical investigation involves being able to predict element or mineral recoveries from simplified input data such as bulk chemistry and/or mineralogy. This relies on the metallurgist having access to accurate information regarding the chemistry of the ore and gangue minerals as well as the likely impact on processing/extraction caused by the impurities (present either as gangue or as substitutional impurities). In this study the chemical properties of two commercially important uranium minerals, brannerite (U4+Ti2O6), and uraninite (U4+O2), were characterised using X-ray diffraction (XRD), scanning electron microscopy (SEM), and electron probe microanalysis (EPMA). Significant levels of impurities were present in both samples with the uranium minerals deviating significantly from their ideal chemical formulae. Differences in chemistry were due to: cationic substitution decay of the uranium isotopes into radiogenic lead and other daughter products mixed uranium oxidation states post-depositional alteration.As well, the brannerite sample showed evidence of significant radiation-induced metamictisation. Leach tests to measure the ease of extraction of uranium from both samples were conducted over a wide range of conditions (temperature, acid concentration and oxidant concentration). For uraninite, the lower U dissolution rates observed in the natural sample compared to a synthetic UO2 sample were directly attributed to the presence of impurities. For brannerite, significant metamictisation of the natural sample led to enhanced U extraction rates compared to a heat treated fully crystalline sample. This study highlights the importance of detailed mineralogical characterisation studies in any uranium process mineralogy investigation as the compositional, textural and microstructural aspects of the main uranium phases present will likely play an important role in any process to extract uranium.CITATION:Ram, R, Charalambous, F, McMaster, S, Pownceby, M I, Tardio, J and Bhargava, S, 2013. Chemical and microstructural characterisation studies on naturally occurring uranium minerals - implications for processing, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 325-334 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By G N. Musafer, M H. Thompson, R C. Wolff, E Kozan

The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when non-linear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bßrdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.CITATION:Musafer, G N, Thompson, M H, Kozan, E and Wolff, R C, 2013. Copula-based spatial modelling of geometallurgical variables, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 239-246 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By A F. Cropp, D J. Bradshaw, W R. Goodall

Mineralogy and critically the texture of both the ore and gangue phases are of paramount importance in the flotation recovery of copper from porphyry ores. Mineralogy and texture will define the theoretical grade recovery curve for a feed ore. Actual grade-recovery falling below this may be due to texture and gangue influences, whilst desired grade-recovery above this line will not be possible unless the characteristics of the feed are altered.This review discusses examples of porphyry copper deposits where process mineralogy has been used to characterise these textural and gangue influences on recovery by flotation. More specifically, the influence exerted by grain size, liberation, association and elemental distribution is explored. The implications of these on overall plant philosophy and operation are highlighted, along with the subsequent potential impact on recovery.CITATION:Cropp, A F, Goodall, W R and Bradshaw, D J, 2013. The influence of textural variation and gangue mineralogy on recovery of copper by flotation from porphyry ore - a review, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 279-292 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By W T. C Kendall, H D. Ngo

Garden Well is a shear-hosted Archaean orogenic gold deposit located 100 km north of Laverton, Western Australia. The Garden Well processing plant is designed for a nominal 491 t/h milling rate and annual capacity of 4 Mt. The plant has three key innovations:1. a scrubbing circuit, expected to reduce grinding power consumption by up to 20 per cent2. a secondary cycloning/gravity circuit, providing a second opportunity for gravity gold recovery (additionally, the circuit effectively increases the leach residence time of the coarse gold bearing fraction of the leach feed by approximately 60 per cent, without any additional tankage)3. the use of mid-stream oxygenation to enhance gold recovery.The Garden Well deposit is free-milling with overall laboratory gravity/leach gold recoveries exceeding 95 per cent at a P80 grind size of 150 ¦m. Three mineralogical domains have been identified: oxide, transition and fresh, with the fresh domain having subdomains of fresh ultramafic and fresh shale. There is a high component of gravity recoverable gold in all three domains.This paper will discuss these innovations and the design challenges and the risk mitigation strategies that were adopted to ameliorate the prototyping risk. The performance of the plant since commissioning together with lessons for the future will also be presented.CITATION:Smith, R J, Kendall, W T C and Ngo, H D, 2013. Treatment plant innovation at Garden Well, in Proceedings World Gold 2013 , pp 315-324 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 26, 2013

By J Savage, A Crawford, M Doyle, N McNaughton, T G. Blenkinsop

Area selection criteria for gold exploration have historically highlighted the low prospectivity of high-metamorphic grade terranes relative to regions with lower metamorphic grades. The Tropicana gold project, Western Australia, is a rare example of a major greenfields gold discovery in Archean mid-amphibolite to granulite-facies gneissic rocks that have experienced widespread recrystallisation and partial melting.The project, located on the tectonically reworked eastern margin of the Yilgarn Craton, is part of the Tropicana Joint Venture, which is 70 per cent owned by AngloGold Ashanti Australia (manager) and 30 per cent by Independence Group NL. Construction of the mine commenced in the June quarter of 2011 and first gold pour from open pit mining is anticipated in the December quarter of 2013. The approved project will have a ten-year mine life and in the first three years of operation, gold production will be between 470 000 - 490 000 oz/a at a cash cost of A$590 - A$630/oz.Reserves as at 31 December 2011 total 56.4 Mt grading 2.16 g/t for 3.91 Moz of gold. The mineral resource, as of 30 December 2012, has grown to 7.89 Moz of contained gold, including Inferred Resources of 11.9 Mt at 2.83 g/t for 1.08 Moz.Economic gold mineralisation post-dates peak metamorphism and is interpreted as younger in age (ca. 2500 Ma) than other gold deposits in the Yilgarn Craton on the basis of structural and geochronological constraints. Mineralisation is genetically related to an imbricate thrust stack that records a prolonged history of reactivation during the Proterozoic era. Gold mineralisation formed from higher temperature (>350¦C) silica-undersaturated fluids that preferentially migrated though a favourable intensely potassium metasomatised zone. Permeability created during brittle fragmentation was accompanied by replacement of mafic metamorphic minerals, and synchronous partitioning of strain into pervasively biotite-sericite-pyrite-altered stylolites and shear planes that bound more competent lithons.CITATION:Doyle, M, Savage, J, Blenkinsop, T G, Crawford, A and McNaughton, N, 2013. Tropicana - unravelling the complexity of a +6 million ounce gold deposit hosted in granulite facies metamorphic rocks, in Proceedings World Gold 2013 , pp 87-94 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 26, 2013

By Q Zhou, G Barrett, Y Choi, J Jiang

As part of a general review of processing double refractory ores through Barrick GoldÆs autoclaves /carbon-in-leach (CIL) facility at Goldstrike, a study was made to evaluate the use of surfactants for reducing the loss of gold during cyanide leaching of preg-robbing gold ores. Consistent improvement of gold recovery was observed with surfactants at various testing conditions. This paper will discuss the results obtained from laboratory and pilot-scale testing, as well as, review potential mechanisms for the observed improvement in gold recovery.CITATION:Zhou, Q, Barrett, G, Jiang, J and Choi, Y, 2013. Surfactants for gold recovery improvement with preg-robbing gold ores, in Proceedings World Gold 2013 , pp 367-372 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 26, 2013