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Caterpillar and Fortescue Metals Group have moved forward with the delivery, installation and support of a complete Cat MineStar System at Fortescue?s Solomon iron ore mine in the Pilbara region of Western Australia. The complete technology suite was implemented for the first phase of Solomon, the 20 Mt/a (22 million stpy) Firetail manned mine, in October 2012. As part of an autonomous mining solution for phase two, the 40-Mt/a (44-million stpy) Kings Mine, eight Command for hauling Cat 793F CMD trucks were commissioned and commenced operations in the second quarter of 2013. The mine plan calls for a progressive ramp up to 45 autonomous trucks during the next several years. In addition, other Cat MineStar System capability sets, Fleet, Terrain, Detect and Health, are being used across the mobile equipment fleet, including support equipment and light vehicles. Working closely with Fortescue and its mining contractor, Leighton Contractors, Caterpillar and the Cat dealer in Western Australia, WesTrac, are providing a full solution for managing, operating and supporting Cat MineStar System and Command for hauling. The greenfield Solomon Mine has brought together the skilled team from Caterpillar, Fortescue, Leighton Contractors and WesTrac to deliver an efficient, cost effective autonomous mining solution.

Nov 1, 2013

By Matthew T. Mowry

As the mining industry continues to hire young professionals to supplant the growing number of retirees, a well-developed engineering curriculum, coupled with practical, real-world training, can prepare mining engineering graduates to make meaningful contributions in the industry. Successful companies can be measured not only by their reserve base and annual production but also by their retention of mining engineering graduates with zero to five years of operational experience. My personal experience in the industry during the last five years has been varied and rewarding. The knowledge and experience I have gained have taught me valuable lessons that prepared me for my current role.

Nov 1, 2013

By Otto Schumacher

Shortcut methods are commonly employed for estimating mining costs for prefeasibility studies. Most of these methods, however, are suitable for earliest stage studies or for internal discussion purposes only. The experts at InfoMine?s CostMine division recommend that any cost estimate completed for purposes of significant decisionmaking or for compliance with Canada?s NI 43-101 requirements be completed using a determinative itemized method. The same basic principles apply for an early stage, intermediate stage, or advanced stage estimate. The only difference is in the level of detail and effort employed. ? Based on the results of a completed resource estimate, an itemized cost estimate begins with development of a conceptual mine plan. Using a surface mine as an example, four elements are crucial no matter what level of study is initiated. Basic geometry of the ore deposit and waste material, with a determination of the expected ratio of waste to ore, a reasonable pit slope angle, possibly requiring the completion of geotechnical studies to predict the waste-to-ore ratio with certainty. ? Determination of the assumed ore and waste production rates. ? Locations of all ore stockpiles and waste dumps. ? Segmental haulage distances and gradients for ore and waste.

Oct 1, 2013

By H. M. Park

Risk is a major factor in all mining activities, arising from many internal and external variables. The authors? research has resulted in a systematic method for the quantification of risk in mining projects (Park, 2012). This is the second part of a three-part series. The first part was published in the October 2013 issue of Minining Engineering magazine and can be found here at www.me.smenet.org. This paper discusses methods of assessing the overall risk associated with those variables, and presents a statistical model based on a survey of 31 experts. The third paper, to be publised at www.me.smenet.org on Oct. 14, presents an evaluation of the statistical model, using data from previous mining investment decisions in which the authors have been involved.

Oct 1, 2013

By Ihor Kunasz

The high lithium demand forecasted for some high tech applications and batteries for electric and hybrid-electric vehicles, in particular, has sparked increased exploration for lithium, particularly for lithium- and potassium-bearing brine deposits. The latter have generally followed the Canadian Institute of Mining, Metallurgy and Petroleum (CIM) NI 43-101 guidelines on resource reporting, formulated for hard rock deposits (metals and industrial minerals). While a number of the requirements can be appropriately applied to brines, brines are fluids and require a specific analysis leading to a distinct set of reporting requirements. Brines cannot be considered industrial minerals because the various elements occur as ions in a dynamic fluid, rather than being chemically bonded in a solid. Although chemicals are produced from brines, brines have no relation to industrial mineral deposits. This article analyzes the recently released (Nov. 1, 2012) document CIM Best Practice Guidelines for Resource and Reserve Estimation for Lithium Brines, in light of the practical knowledge available from existing brine operations. It recommends modifications to the guidelines, which, if applied in their present format, will result in overstating resources and reserves and mislead potential investors. The CIM Best Practice Guidelines for Resource and Reserve Estimation for Lithium Brines document is generally descriptive and does not fully address the methodology for brine resource or reserve definition. Lithium and other elements (potassium, magnesium) are contained in a fluid, the hydrologic characterization of which should be the principal focus of a brine exploration program. The fundamental requirement in defining lithium brine resources and reserves in a salar is the identification and definition of those formations ? the aquifers ? that will yield brine in a usable quantity to a well, because brines can only be extracted by pumping wells. Fine-grained sediments will never, as required in the summary Table 1, have ?reasonable prospects of economic extraction,? cannot be considered and, therefore, need not be tested. However, the guidelines recommend the collection of solid samples and a high-core recovery for laboratory testing of various sediments instead of focusing on the brine.

Oct 1, 2013

By C Moorhead, J Jones

A common problem in the mining industry is that company geologists can operate in relative isolation to the rest of the company (Jones and Moorhead, 2011). This may result in poor knowledge transfer and often priority conflicts with geology, operations and project departments. This problem is amplified by the acquisition of mineralogy capabilities and other metallurgical (met) test work undertaken by many companies in order to solve for complex orebody problems. Met data is often not located and viewed in 3D space so that geologists and engineers can create and work with geometallurgical (geomet) models (Bye, 2006). Visualisation of data in an interactive graphical 3D model provides a bridge enabling met professionals to collaborate with engineers and geologists to provide a common understanding of the relevance of geomet data.In recognition of this problem, Newcrest has undertaken an effective collaboration strategy to improve internal and external engagement through the use of large visualisation displays (Jones, 2009). The displays are underpinned by IT systems and information management practices that recognise the needs of underlying disciplines. Today it is generally understood within Newcrest that this is required to improve decision-making, deliver faster cycle times and improve governance.Collaboration in companies has been generally associated with the introduction of new IT functions (IBM, 2008). However, the science and engineering process that are used to structure modern IT-based collaboration systems and practices are now known to be simplistic compared to the long-standing practices associated with collaboration and knowledge management in disciplines such as geology and mining.CITATION:Jones, J and Moorhead, C, 2013. Geometallurgical communication as a distributed information system, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 133-138 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By R Castroviejo, E Pirard, L PTrez-Barnuevo

Process mineralogy provides the mineralogical information required by geometallurgists to address the inherent variation of geological data. The successful beneficiation of ores mostly depends on the ability of mineral processing to be efficiently adapted to the ore characteristics, liberation being one of the most relevant mineralogical parameters. The liberation characteristics of ores are intimately related to mineral texture. Therefore, the characterisation of liberation necessarily requires the identification and quantification of those textural features with a major bearing on mineral liberation. From this point of view, grain size, bonding between mineral grains and intergrowth types are considered the most influential textural attributes. While the quantification of grain size is a usual output of automated current technologies, information about grain boundaries and intergrowth types is usually descriptive and difficult to quantify to be included in the geometallurgical model.Aiming at the systematic and quantitative analysis of the intergrowth type within mineral particles, a new methodology based on digital image analysis has been developed. In this work, the ability of this methodology to achieve a more complete characterisation of liberation is explored by the analysis of chalcopyrite in the rougher concentrate of the Kansanshi copper-gold mine (Zambia). Results obtained show that the method provides valuable textural information to achieve a better understanding of mineral behaviour during concentration processes. The potential of this method is enhanced by the fact that it provides data unavailable using current technologies. This opens up new perspectives to the quantitative analysis of mineral processing performance based on textural attributes.CITATION:PTrez-Barnuevo, L, Castroviejo, R and Pirard, E, 2013. New perspectives on quantitative textural analysis, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 191-198 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By K Nguyen

The advances in computerised processors and digital microscopic imaging have enabled more studies that attempt to quantify textural information from rock images. However, a texture classification system designed for geometallurgy has always been challenging, as it combines general image analysis techniques and specific texture classifications in terms of the size, shape and orientation of mineral particles. In this paper, a novel texture analysis technique using grey level radial shell association (GLRSA) and spectral angle mapper (SAM) to discriminate between different geological images is outlined. The technique can be applied in routine analysis and characterisation of mineralogical and textural attributes which may correlate with variability in mineral processing behaviours. Using this texture analysis technique, a set of small texture reference images, a texturelet reference library, has been identified from a suite of drill core images. Rock types are classified according to the proportion of each texturelet type recognised. The library is site specific.CITATION:Nguyen, K, 2013. A new texture analysis technique for geometallurgy, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 187-190 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By S H. Begg

"*This is an abstract only*Most technical and economic analyses are performed to reduce uncertainty to help make decisions. Decision-making is about ranking alternatives - rarely are precise predictions required, if even possible. This simple observation has profound implications for modelling approaches, how they deal with uncertainty and the reliability of information provided by subject matter experts.CITATION:Begg, S H, 2013. Some reflections on uncertainty, decisions, models and people, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 3-6 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By D J. Bradshaw, B Lottermoser, A Parbhakar-Fox

"Best practice for acid rock drainage (ARD) risk assessment still relies solely on the geochemical properties of sulfidic rocks and mineral processing products, despite the fact that a rockÆs tendency to produce acid also depends on mineralogy and texture. Consequently, there are a plethora of geochemical tests routinely utilised by the mining industry to predict ARD formation. Due to limitations associated with these tests and their relatively high costs, analysis of recommended best practice sample numbers is rarely achieved, reducing the accuracy of waste management plans. Our research addressed this through examining the application of geometallurgical data for predicting acid formation, and led to the identification of potential environmental geometallurgy indicators.Samples obtained from an iron-oxide copper gold deposit were subjected to the geochemistry-mineralogy-texture (GMT) approach, an improved methodology for classifying acid forming potential. GMT results were compared against geometallurgical and assay data sets to evaluate: relative carbonate content measurements (measured by HyLogger) and identify how these could be used to calculate effective acid neutralising capacity mineral hardness (measured by EQUOtip) to determine application of this data for calculating lag-time to acid formation opportunities to automate the acid rock drainage index (ARDI) using classified images produced by a GEOTEK logger and automated microscopy.Links between the GMT approach and geometallurgical data sets were identified. Classified mineralogy data has application at stage one, HyLogger and EQUOtip at stage two and computer-based ARDI evaluations of classified images at stage three. Through such integration, ARD characterisation costs can be reduced, with value added to geometallurgical data sets. Furthermore, deposit-wide ARD domaining is possible, and acquisition of total-orebody knowledge more likely. Through adoption of this environmental geometallurgy approach, a better informed waste management plan can be formulated, allowing for best practice ARD sampling in a more cost-effective manner.CITATION:Parbhakar-Fox, A, Lottermoser, B and Bradshaw, D J, 2013. Cost-effective means for identifying acid rock drainage risks - integration of the geochemistry-mineralogy-texture approach and geometallurgical techniques, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 143-154 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By S R. Williams

There is a sense of geometallurgy being new; a new methodology for mining project development and improved operational strategy. One of the main challenges that any ænewÆ technology faces is a validation of the value and the need to produce case studies. However, producing case studies can often be problematic particularly given the long cycle from mineral deposit project, through feasibility and construction to stabilised operation of a mine.However, the roots of geometallurgy go back quite some time. Successful practices with geometallurgy can be seen from as early as the 1980s. Many times those practices were not called geometallurgy but something else and, in other cases, what can be seen are various components of the geometallurgical ævalue chainÆ.This paper will analyse a selection of published past practices from a geometallurgical perspective to demonstrate the value realised from the application of this methodology. The paper will then make some general comments on where this history of work in geometallurgy has lead us to and what are the challenges today for the geometallurgical effort.CITATION:S R Williams, 2013. A historical perspective of the application and success of geometallurgical methodologies, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 37-48 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

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 Czerny, T Elkington, L Lorenzen

The Dutwa Nickel Project is a nickel laterite atmospheric leach project located in Tanzania that has been under development by African Eagle Resources plc (2012). A bankable feasibility study (BFS) has been progressed to evaluate mining of the resource (107 Mt at 0.92 per cent Ni) followed by hydrometallurgical processing on-site to make a mixed nickel-cobalt intermediate product. The unique relatively high silica contents in the Dutwa deposits, as opposed to limonite, which is more commonly occurring in nickel laterites, presented the possibility for beneficiation of the ores to enhance the leach feed nickel grades and provide economic benefits in terms of operating and capital cost efficiencies.Geometallurgical relationships, based on the results of an extensive variability metallurgical test work program for beneficiation and leaching, were developed for the BFS, which resulted in an improved understanding of ore classifications within the deposit and their responses. The geometallurgical information obtained has been instrumental in making key preliminary techno-economic decisions, such as forecasting whether or not mined material should be beneficiated and was ultimately used to drive the mine plan towards the prioritisation of areas within the deposits that delivered the best cost efficiencies and overall project economic outcomes.CITATION:Elkington, T, Lorenzen, L and Czerny, C, 2013. The use of geometallurgical relationships in process route selection and mine plan optimisation for the Dutwa Nickel Project, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 207-216 (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 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 N L. Turner, K Ehrig, V Liebezeit, D J. Robinson, L L. Kuhar, N Francis

Conventional industry tests used to determine leach recoveries are often fully monitored and may be time-consuming and expensive. Such tests may be limiting in geometallurgical applications where large numbers of samples are required to be processed for characterisation of an ore deposit. BHP Billiton currently use a fully instrumented leach test for characterisation of Olympic Dam uranium-rich samples. Researchers at the Commonwealth Scientific Research and Industrial Organisation (CSIRO) were approached to develop an alternative to these full-scale leach tests that could allow for the ranking of samples in terms of their leachability. The novel geometallurgical test was required to use samples of small mass and be affordable and rapid.Three leach test protocols were pursued in developing the small-scale tests. Kinetic leach tests were performed using mild conditions at higher pH, low temperature and low oxidation reduction potential, moderate conditions at intermediate pH, temperature and oxidation reduction potential and aggressive conditions at lower pH, higher temperature and higher reduction potential.This paper presents results from 44 leach tests on 11 samples with varying uranium mineralogy. The developed small-scale tests correlate well with data from the more costly conventional industry laboratory tests, indicating the possibility of using this alternative test as a geometallurgical leach proxy. Simple regression analysis confirmed the importance of pH, reduction potential and temperature on uranium extraction. Experimental data were fitted to published leach models to predict uranium leach extraction for a range of operating conditions.The ultimate aim of the test work is to combine a limited number of large-scale calibration tests, a large number of small-scale geometallurgical tests and leach models for geometallurgical sample characterisation and evaluation of a wide range of scenarios or processing options.CITATION:Turner, N L, Kuhar, L L, Francis, N, Liebezeit, V, Ehrig, K and Robinson, D J, 2013. Development and testing of a small-scale uranium leach for geometallurgical applications, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 345-350 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By K G. van den Boogaart, S Konsulke, R Tolosana Delgado

Adaptive mineral processing has to rely on spatially predicted information on primary geometallurgical parameters, like phase composition, size and shape distributions of grains from various phases, portions of value elements in different grain types. Naively, one would predict these parameters geostatistically and select an optimal processing for the predicted structure. This is suboptimal, due to various kinds of non-linearities in the problem. First, some primary geometallurgical quantities themselves are measured in non-real scales, like compositional or stereologically distorted geometric information. Standard geostatistics has to be replaced by compositional and geometric geostatistics, involving complex transforms and restrictions. Further, only partial and uncertain information is available, introducing a stochastic character to the optimisation problem. Moreover, many response variables leading to costs, outcomes and eventual effects of later processing depend non-linearly on the primary geometallurgical parameters, which implies that the final monetary value is not estimated unbiasedly by kriging. Finally unbiased linear prediction (such as kriging) is not the best method of prediction for decision making. The conditional expectation of the monetary values is needed instead. The impact of these problems is explained in this paper, with simplified examples, and a first approach to a general solution is proposed. CITATION:van den Boogaart, K G, Konsulke, S and Tolosana Delgado, R, 2013. Non-linear geostatistics for geometallurgical optimisation, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 253-258 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013