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By L Keeney

Geometallurgy is not a mechanism designed to replace current geological and metallurgical deposit characterisation but an added component required to understand orebody variability. Current geological characterisation approaches focus on understanding deposit genesis aimed at identifying new mineralised regions and metallurgical characterisation determines parameters required for engineering design of processing plants. Geometallurgical integration has the task of drawing on aspects of each stream to enable spatial mapping of performance indices across a deposit. It is a complimentary activity to current practice and adds a new dimension to orebody knowledge. Although the notion of conducting an integrated geological and metallurgical analysis is not a new concept, limited publications exist in the field proposing integrated methods, with several technical issues existing in current geometallurgical integration approaches. An iterative method drawing on existing geological and metallurgical characterisation and new measurement tools and inputs is proposed. The integrated method comprises of discrete components dynamically linked together through iterative feedback loops with each component having a specific purpose achieved by applying a range of data acquisition technologies and statistical tests. The key outcomes of the method are:overcoming the lack of optimised geometallurgical domains relevant to processing performance,development of a rigorous approach to identifying parameters controlling processability,improved protocols for relevant metallurgical test data and sample selection, andability to generate greater data support to enable rigorous geostatistical modelling of geometallurgical attributes. This paper outlines the integrated mapping and modelling method developed and draws on multiple data acquisition technologies applied within the AMIRA P843 GeMIII Project.

Sep 5, 2011

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

By A R. Bye

The mining industry is facing some key challenges that provide a compelling case for geometallurgy initiatives. Over the last 30 years, the average grade of Australian orebodies being mined has halved while the waste removed to access the minerals has more than doubled. In the last eight years, the industry’s energy consumption has increased 70 per cent while multi-factored productivity has fallen 24 per cent. The paper documents a broad range of industry case studies which demonstrate strategies for gaining value from geometallurgy.The mining industry constantly faces the key questions of how significant ore variability is on mine valuation and how would knowledge of the variability change the mining schedule, mine to mill design and operation. Using case studies the paper describes the methods used for incorporating mineral extraction attributes into orebody models and their technical integration into daily operation as well as mine planning optimisation. While pit optimisation from a fully attributed geometallurgical model highlights areas of opportunity and risk it is shown that during the scheduling phase of mine planning that significant value can be added. The benefits from these projects included reducing geotechnical and environmental risk, improving mine to mill performance, option analysis and quantified cash flow risk. There is growing acceptance within the minerals industry that ‘realistically assumed modifying factors’ defined by a competent person/s are not sufficient to mitigate the risk of funding mining ventures. Geometallurgy is moving away from factored ore reserves to data-rich block models providing reliable information for mining, metallurgical and environmental considerations.

Sep 5, 2011

By R Baumgartner

The Canahuire deposit is a recently discovered Au-Cu-Ag epithermal deposit in Southern Peru. A geometallurgy program is a key study element of the project Feasibility study. Metallurgical, mineralogical, and comminution studies have been completed over a suite of samples, spatially distributed among the various geological/ore domains. The early stage of Canahuire presents challenges as there is a lack of metallurgical information to guide geometallurgical sampling, in contrast with an established deposit at a more advanced stage of development or mining. Nevertheless, the available information will assist in the development of geometallurgical domains for Canahuire in order to ensure that future metallurgical, mineralogical, and comminution test work is representative of the deposit variability. This supplementary knowledge will be able to predict important metallurgical parameters which will be incorporated into a geometallurgical model to spatial predict material types, metallurgical recovery and through put. The information obtained will be a valuable addition to the future mine plan, influencing process design, engineering design, plant operation, operating and capital costs, and ultimately will reduce project development risk.

Sep 5, 2011

By S C. Dominy

For any gold deposit-based geometallurgical study, the collection and processing of representative samples for gold grade and recovery tests is critical. Sampling protocols should be designed to suit the style of orebody in question. The proportion and size of gold particles has a direct impact on the effectiveness of sampling protocols and metallurgical recovery processes employed. Studies focussing on ore mineralogy and gold particle deportment, size and distribution are required. Key issues are the presence of gold particle clustering (important for sampling optimisation) and proportion of coarse versus fine to refractory gold. X-ray computed tomography (CT) is a radiographic technique that produces high-resolution 3D computerised models of objects based on density distribution. The ‘virtual’ specimens are made up of voxels, the 3D equivalent of pixels each assigned a grey value based on X-ray absorption. This paper presents the results of recent research on the imaging of in situ gold particles in a coarse gold-bearing ore. The technique shows promise as a rapid non-destructive method for preliminary characterisation to facilitate more detailed studies. Early and rapid gold particle determination enables sampling protocol optimisation and metallurgical recovery parameters to be defined prior to detailed feasibility studies

Sep 5, 2011

By S Dunham

A cross-discipline approach combining geology, metallurgy and mine planning, geometallurgy is seen as the next logical advance in improving the design and operation of mining businesses. This rapidly evolving field is focused on realising the value that has often been lost in the chasms between the aforementioned technical silos. When successful, the geometallurgical approach promises the ability to tailor mining and mineral processing development and operational options more closely to the characteristics of the resource with resulting lower costs (both capital and operating), improved recoveries and fewer project failures.As with any technological (or managerial) change, there will be side effects from the success of the geometallurgical approach that will impact areas beyond obvious linkages between geology and processing. Some of these effects have the potential to be beneficial to the resource industry and society in general. Beyond the basic geometallurgical promise of closer alignment between processing design/strategy and the multivariate 3D spatial characteristics of the mineralisation, this paper discusses the broader implications and ramifications of the emergent geometallurgical approach: enhancing exploration and discovery; improving project development success; achieving sustainability in an industry working with non-renewable resources; in a world of increasingly hard won license to operate, improving the management of potentially harmful by-products and waste materials (with knock on effects for proactive management of closure issues); smarter approaches to energy management and thus optimisation of projects with respect to carbon footprint; and potential to re-value assets and thus realise a strategic advantage in the area of acquisitions, divestments, mergers and take overs. The authors strongly believe that companies that actively engage with the above issues (and ensure that technical efforts in the area of geometallurgy are not isolated from the larger value chain activities of the firm) will be able to exploit the opportunities that consequentially arise. These early adopters will gain first mover advantages. Firms taking the broad view of geometallurgy will have an opportunity to maximise stakeholder value and win greater success than their less insightful competitors.

Sep 5, 2011

By B Armstrong

The Proterozoic poly-metallic Trilogy deposit was discovered in 1997, and until recently, mining evaluation was stalled due to poor metallurgical performance. Unlocking the substantial economic value of the deposit required a coming together of geologists, mineralogists, metallurgists and mining engineers, who by working collaboratively, uncovered the detail necessary to allow the required metallurgical breakthroughs to occur. The deposit itself is described as a sedimentary exhalative (SEDEX), with an enriched lead-zinc-silver core surrounded by a broader envelope of copper-gold mineralisation. The geological domains were defined in broad terms based on the style of mineralisation, assay values and lithology. These domains, while adequate for the resource estimation process, failed to translate into representative metallurgical domains. Additional work with new techniques defined regions in the deposit with altered processing properties which could not be recognised by conventional geological logging. Such additional complexities could not be appreciated at the outset of the metallurgical test work program.These regions were defined by applying the EDTA analysis method for recognition of where the valuable sulfides, particularly galena, had been partially modified by oxidising conditions. Hence, the flotation response of the valuable sulfide minerals was diminished and the increased amount of heavy metal cations available in the system significantly reduced selectivity in the flotation process.Understanding the detail of this complexity was essential in determining representative metallurgical domains, which was the first step in the long road of development.

Sep 5, 2011

By M A. Wells

A new approach to more reliably predict the Ni (and Fe, Mg) composition of Ni laterites was tested for RC samples from the (siliceous) oxide–style, Siberia North deposit, Kalgoorlie Nickel Project (KNP), in the north-eastern Yilgarn (WA) using partial least squares regression (PLSR) analysis of diffuse reflectance spectra over the 380 - 2500 nm wavelength range with a multi–element chemistry data set. PLSR cross-validation models were developed to predict FeO, MgO and Ni contents in composite samples with bulk composition limits of >0.08 wt per cent Ni and <6 wt per cent MgO. Calibration and validation models showed a strong, linear trend for predicting FeO and, to a lesser extent, Ni content, whereas PLSR models for predicting Mg content were less reliable. This reflected the prevailing mineralogy and associated element deportment within the oxide laterite profile. For example, Fe and Ni distribution is controlled by relatively few minerals, predominantly goethite and, to a lesser extent, the Fe3+-bearing smectite, nontronite. Magnesium is associated with a range of Mg-bearing minerals, some of which are compositionally complex (eg serpentine, talc, chlorite, smectite and carbonates). Magnesium chemistry alone does not reflect the varied mineralogy of samples with relatively high (5 - 6 wt per cent) MgO contents, which can be spectrally distinct. Hence, samples with similar Mg contents, though comprising Mg-bearing minerals with distinct reflectance spectra, were difficult to model (eg smectite versus Mg-carbonates). The findings of this study demonstrate that characterisation of Ni laterite composition may be achieved as part of routine logging of either drill chips or diamond drill core using PLSR analysis, but that a detailed understanding of the mineral-element association is essential for reliable predictive analysis. This has particular relevance to characterising the geometallurgy of Ni laterites, especially where deposits may be classed as the same type, but have distinct compositional and mineralogical differences.

Sep 5, 2011

By G Harbort

The use of geological data for optimisation of operating plants has become a significant part of the modern process mindset. The underlying principle is to convert spatial geological data into metallurgical information to drive production and mine planning, blast design, blending strategies and plant set-up. Increasingly the process designer is required to interface with geological and mining staff to propose the best investment strategy for a project’s benefit.The geometallurgical model development for the Zafranal copper-gold project commenced in March, 2010, several months after the start of a major drilling campaign by AQM Copper Inc. The initial evaluation stage required review of historical Teck RC data to determine areas of metallurgical interest within the project. As drilling transitioned from RC to diamond drilling, core that was considered representative of the resource was selected and subjected to MLA mineralogy analysis. When coupled with sequential copper analyses this allowed calibration of an assay derived mineralogy model, allowing process concept options and a preliminary test program to be developed. This Phase 1 test program provided a preliminary process design, operating costs and anticipated concentrate grades and recoveries. Both this data and resource estimation were used to generate a preliminary Whittle pit optimisation based on maximising net smelter return, which in turn fed into a preliminary mine plan. The preliminary mine plan, in conjunction with geological logs and core results was used to develop a phase 2 metallurgical test program, where variability tests were conducted throughout the resource and composites formed to investigate specific years of the mine plan in locked cycle flotation. In addition comminution tests were modelled against geometallurgical domains allowing comminution components values to be calculated for 36?000 m of core. A flotation geometallurgical model was developed and incorporated into the resource model allowing concentrate grades and recoveries to be estimated on a block-by-block basis.

Sep 5, 2011

By L L. Kuhar

The AMIRA International P843A Geometallurgical Mapping and Mine Modelling (GeMIII) project is an interdisciplinary research collaboration between 17 global mineral companies and four research organisations aimed at providing support for the emerging industry trend of geometallurgy. The main aim of the project is to develop predictive geometallurgical indices which can be incorporated into a resource block model to maximise the commercial value of an orebody and to minimise the social and environmental impact of mining operations.Researchers at the Parker Centre/CSIRO have been focusing on the development of predictive hydrometallurgical indices for the GeMIII project via rapid, small-scale, cost-effective tests and protocols for comparative ranking of attributes relevant to leach performance. The focus of the small-scale leach tests has been to determine the leach index (relative indication of leach performance), recovery, impurity deportment, reagent consumption, effect of size/degree of liberation and mineralogy of samples for their relative ranking. Predictive tests for heap leach hydrology (related to agglomerate characteristics) and slurry rheological behaviour are also being developed.

Sep 5, 2011

By E Macmillan

For any processing plant there will be deleterious elements or minerals which affect production or quality, and a strategy to predict their occurrence and mitigate their impact is required. An early objective of the Olympic Dam geometallurgy program was prediction of the acid consumption and gelling behaviour of the ore, which affects leach recovery, throughput and circuit availability. The geometallurgical test program measured the response of a wide range of ore types, and then relationships between mineralogy, metallurgy and chemistry were developed. Thus the drivers of acid consumption and triggers for gelling events could be described in ways that were meaningful to plant operations.To enable optimisation of the mine planning and ore blending processes, the parameters driving metallurgical response must be translated to the block model. Data support is critical in populating a block model. Assay information is easily obtained, but mineralogical and metallurgical information is more expensive and time consuming to collect. Hence population of a block model with mineralogical and metallurgical values using a conventional geostatistical approach is not always possible.An alternative approach employed at Olympic Dam was the development of a suite of assay-to-mineral algorithms. These algorithms were calibrated using all available mineralogical information, and this enabled the calculation of mineral abundances for more than 1.5 million assayed samples. Estimation of the minerals in the block model, and the generation of acid consumption values for each block could subsequently occur.The use of back-calculated mineralogy from assays as part of process model generation is an innovative tool which can be used for mine planning and optimisation and to ensure the plant does not receive any unwelcome surprises. Ultimately, one purpose of geometallurgy is to predict potential processing issues and their drivers so that these can be mitigated. A strategy to achieve this is outlined hereafter.

Sep 5, 2011

By L Lorenzen

The selection of samples for metallurgical test work is generally focused on providing geologically representative samples. One of the major problems experienced with metallurgical test work using drill hole data, is the small sample sets selected for metallurgical testing. Major process and financial decisions are being made from results obtained using snapshot samples. Snapshot samples means that samples are basically selected only by grade and spatial location with the assumption that the rest of the orebody or portion of orebody is similar and will respond metallurgically the same way – ie the assumption is that the mineralogy and lithology are basically the same as the test sample. From the test work, algorithms were usually developed and used to describe throughput and recovery using some explanatory variables including grade (mineral chemistry) and ore hardness. These algorithms were then used in the recovery models to determine tonnes produced and plant throughput. However, the metallurgical parameters are a function of many geological factors including grade, lithology, alteration, mineralogy, spatial relationships and SG. In previous years, the limited mineralogical information available was deemed enough for the metallurgist to make decisions as to how many samples are needed to evaluate the metallurgical performance of the ore during processing, and subsequently the basis for the plant design. If the orebody is consistent and not complex or refractory (thus, relative simple lithology), then only spatial and grade samples will be needed to evaluate the throughput and recovery, so limited mineralogical information may be acceptable. There is now, however, an increasing realisation that the mineralogy and geology change, as do the metallurgical characteristics of the orebody, so limited samples may not be sufficient for effective metallurgical test work.It is the purpose of this paper to discuss the effect correct mineralogical information has on the subsequent metallurgical test work program and process selection using a case study. Factors such as type of rock, rainfall and topography are thought to influence the minerals that ultimately form in various orebodies, with the result that different orebodies often react differently during metallurgical test work programs. It is therefore important to obtain accurate mineralogical and elemental deportment data, which will also indicate where the valuable metal containing minerals are located within the orebody. The better you plan and execute your metallurgical test work program during the early phases, the more accurate the decision-making process will be during the selection phase. Improved integration between geology and metallurgy data gathering (geometallurgy) during early phases will result in more accurate predictions with regard to throughput and recovery during modelling and process. Equipment selection will be considerably simpler in later phases with early planning, with improved mine and process scheduling and subsequent net present value (NPV).

Sep 5, 2011

By M J. Newton

As part of the AMIRA P843 project Keeney and Walters (2008) describe how the principal components analysis (PCA) method can be used to identify classes of samples with similar metallurgical characteristics. However PCA does not take account of the location of each sample in 3D space. This paper describes a study to analyse the spatial distributions of the classes and determine appropriate modelling methods to control the estimation of the comminution parameters and mill performance indices into a 3D block model. This includes but is not restricted to geostatistical techniques that are used for grade modelling. The starting point for the study is the class definitions and the regression models for estimating the comminution parameters and performance indices. Each sample is assigned a class and the spatial distribution of each class has been analysed using different techniques including the calculation of variograms. This establishes whether the classes can be used as domain control for estimation into the block model – a procedure similar to using geological rock type domains for controlling the estimation of grades for a resource model. However, standard geostatistical estimation methods such as ordinary kriging assume that the variable being estimated is additive or linear. This assumption is valid for variables such as grade but this is not necessarily the case for the comminution parameters or the performance indices. Therefore the estimation procedure must either use variables that are definitely additive or the effect of potential non-additivity must be tested and accounted for where possible.The results of the study show how performance indices such as recovery, throughput and specific power can be estimated into the block model. This model is then combined with the geological model to provide a multi-parametric model that is used to optimise the mine planning and scheduling activities which can lead to significant improvements in NPV.

Sep 5, 2011

By O Rojas

The Telégrafo copper – gold deposit is located in the Centinela district of the Antofagasta region in northern Chile. Telégrafo is a porphyry copper deposit of Eocene – Oligocene age which has a total mineral resource in measured, indicated and inferred categories equal to 2.6 billion tonnes with an average grade of 0.38 per cent copper.Currently the project is in the prefeasibility study phase, including an infill drilling campaign to improve the knowledge of the deposit that should result in an improvement of the mineral resource classification. In this context was decided to review the classification criteria in order to optimise the drill hole density necessary to support the project.This paper presents an application of conditional simulation to evaluate the risk related to drill hole spacing, using a geostatistical approach that mimics the process of evaluation of resources from the perspective of geological modelling and grade estimation. The first step of the approach is the generation of conditional simulations using the available samples to generate several plausible scenarios of the deposit in terms of copper grades and geological units. These scenarios are considered as the unknown reality of the deposit and sampled by synthetic drill holes in order to replicate the geological model process and copper resource estimation. In this way it is possible to establish differences between the possible scenarios and the generated resource estimation models for several simulated drill hole spacing alternatives. These differences or errors can then be quantified in terms of estimated mean, metal content and tonnage over different production volumes.The resulting errors were useful in assisting the decision making process related to the design of drill hole spacing for each category of mineral resource in the Telégrafo project, and to redistribute the budget associated to the drill campaigns for the next stage of the project.

Aug 22, 2011

By D Cooke

In 2010, Kalgoorlie Consolidated Gold Mines (KCGM) was Australia’s largest gold producer, with total annual production of 788 000 ounces. Of the gold produced by KCGM in 2010, 95 per cent was extracted from the Fimiston open pit, also known as the Superpit. The Fimiston operation encompasses the historic Golden Mile, from which more than 55 million ounces of gold have been extracted from the world-class Fimiston lode style mineralisation.The operational performance of the KCGM Fimiston open pit was reviewed for the period between 2005 and 2010. Key performance metrics reviewed included mined tonnes and grade, cost per ounce of gold produced and the mine to mill reconciliation trends. The years 2007 and 2008 were characterised by a decline in performance against key performance metrics. The ore zones were diluted, with the excess tonnes mined resulting in lower grade and an increase in the cost per ounce. Poor reconciliation between ore mined, the ore reserve model and the grade control polygons was also observed.A series of improvement initiatives were implemented in late 2008. As a result of changes made to the grade control and mining practices, the site performance recovered. Unplanned dilution was reduced, which had a positive impact on mined grade. The lower tonnes combined with higher grade reduced the cost per ounce to below budgeted levels in 2009 and 2010, enhancing the profitability of the operation. The operational performance between 2005 and 2010 was compared to the turnover statistics for the KCGM geology department over the same period. Turnover accelerated between 2005 and 2007, peaking at an annualised rate of 43 per cent. With the onset of the Global Financial Crisis and the implementation of retention initiatives, turnover reduced significantly between 2008 and 2010. A strong consistent correlation was observed between the turnover trends in geology and the performance of the grade control function and resultant site metrics.The cost of turnover is known intuitively, however, rarely quantified. To evaluate the benefit of the improved performance, a detailed financial model was used to quantify the impact of the grade control function. In 2010, the headgrade exceeding budget by just four per cent contributed an additional A$24 M of value to KCGM. In contrast, if the 2008 performance had been replicated in 2010 (-9 per cent on headgrade), the result would have removed A$61 M in value from the business. The KCGM experience between 2005 and 2010 demonstrates the value of human capital in a mining operation and the importance of a high performing geology grade control team to the profitability of a mining operation.

Aug 22, 2011

By V Yadi

Geostatistics has been widely used for more than four decades as a powerful tool in ore resource/reserve estimates and grade control. This method has gradually replaced the conventional method such as polygon and cross-section for grade estimation by more mathematical techniques such as kriging. The advances in geostatistical understanding and the availability of appropriate software packages have given much more contribution in speed and high accuracy during production. However, in many cases, these techniques are sometime applied without support with a good thorough understanding of the geological controls on metal distribution. To produce the result close to actual, the geological control in interpretation and appropriate geostatistical task is a must. Geological logging was described in the core must be consistent with the level plan produced by commercial modelling software used as a guide for grade control during production. Experience gained through evaluation of the Central I deposit resulted that the most effective systems continue to be based on geostatistical methods of resource estimation. Computer applications modelling software packages are necessarily as the core of an efficient in undertaking these assignments. They contribute to make a valued to data management and are becoming increasingly effective during processing. The latter role is particularly important to check the actual versus estimated values where will significantly to improve personnel to have a confident with their knowledge combined with experience and complete their jobs satisfy.

Aug 22, 2011

By R H. Sibson

Magmatic and/or hydrothermal fluid systems in island or mountain arcs self-organise to critical states subject to perturbation by changes in the regional stress, which plays a controlling role in the containment of overpressured fluids. Whether the magmatic arc is under compression (eg Andes, northern Honshu) or extension (eg Taupo Volcanic Zone, New Zealand) is a key factor controlling the ease of magmatic or hydrothermal fluid ascent. Abrupt changes in the stress regime have the potential to induce major episodes of fluid redistribution. Large earthquake ruptures along plate boundaries may induce such changes over broad areas, also contributing to fluid redistribution by renewing fault permeability along the causative rupture zone or reactivating distant fault-fracture permeability by shaking from radiated waves. High-resolution geophysical investigations of active arc systems and the subduction thrust interface underlying their fore-arcs reveal repositories of overpressured hydrothermal fluids. In active magmatic arcs under compression such as NE Honshu or Cascadia, there is evidence for a heterogeneous distribution of overpressured hydrothermal fluids in the middle-to-lower crust trapped around the base of the upper crustal seismogenic zone. Investigations of the subduction thrust interface responsible for great (Mw = 8.0) ‘megathrust’ earthquake ruptures has revealed in some instances (Cascadia, SW Japan) the existence of a belt of non-volcanic tremor (NVT) with accompanying slow slip episodes defining the base of the megathrust interface at 40 ± 5 km and 350°C??-??550°C. Aqueous fluid at these depths is likely derived from dehydration reactions accompanying the basalt-eclogite transition in subducted oceanic crust. NVT sequences in the hanging-wall above the interface may be defining migration pathways into the overlying crust.The potential for eruptive episodes in magmatic arcs and redistribution of hydrothermal fluids is assessed in the light of the stress changes that followed the 2011 Mw9.0 Tohoku subduction thrust rupture which extended along strike for over 500 km and down-dip for over 150 km, with maximum slip of c 50 m.

Aug 22, 2011

By D Timms

The Kempfield deposit is located in the Hill End Trough, one of several intracratonic basins developed during Silurian–Devonian time, in the eastern province of the Lachlan Orogen, Eastern Australia.The deposit contains an oxide resource of 5.8 Mt @ 58 g/t Ag and a sulfide resource of 14.4 Mt @ 45 g/t Ag, 1.7 per cent Zn and 0.6 per cent Pb, classified and reported in compliance with the JORC Code. The deposit has been previously explored by a number of companies, including INCO, Shell, Jones Mining, Golden Cross Resources and recently Argent Minerals Ltd (Argent). Argent is currently completing a definitive feasibility study with a view to mining the deposit.The deposit is hosted at the boundary between the Molong High to the west, comprising Ordovician sediments and volcanic rocks and the Hill End Trough to the east, interpreted as a back-arc basin containing Silurian sediments and siliceous-feldspathic volcanic rocks. The boundary between these two strato tectonic units is an imbricate thrust fault zone known as the Copperhannia Thrust.The Kempfield deposit is hosted in felsic volcanic rocks known as the Kangaloolah Volcanics. These have been in-faulted and folded into the Middle Ordovician meta-sediments of the Coombing Formation of metasediments along the Copperhannia Thrust. The Kangaloolah Volcanics belong to the Late Silurian Mumbil Group, comprising submarine carbonate-shale facies interspersed with extensive felsic volcanic piles, which grade conformably upwards into turbiditic sandstone and siltstone sequences (interpreted to represent a deeper depositional environment). These turbiditic rocks are known as the Campbells Formation, comprising siltstone, sandstone and andesitic tuff. The rocks at Kempfield are metamorphosed to lower greenschist facies, reflected through the different type of schists.Silver, gold, lead, zinc mineralisation is hosted in barite-rich horizons, near the boundary to quartz-phyric tuffaceous rocks in submarine, immature, reworked felsic ash tuffs. Barite appears to be hosted in greatest concentrations by the coarser grained volcanoclastic sandstones and grits, whilst intercalated siltstones are volumetrically minor and tend to return low barite and silver. Mineralisation is hosted in stratiform and probably stratabound barite-rich horizons. A northeast-trending, steeply dipping, metamorphic cleavage (S1) occurs throughout the project area.

Aug 22, 2011

By M F. Gazley

The amphibolite-facies metabasaltic rocks of the Mine Mafic Package at Plutonic Gold Mine, Marymia Inlier, Western Australia, contain an estimated total endowment of 12.2 Moz of Au, which includes 4.71 Moz of past production and 2.77 Moz of reserves and resources; the remainder comprises lower-grade inventory. Over 65?000 multi-element analyses of whole-rock core and face channel samples from the underground workings of the deposit have been collected by portable X-ray fluorescence (pXRF) using a handheld Innov-X Omega pXRF unit. The analyses were performed on pulverised samples through paper bags, and were corrected using a pulverised, matrix-matched, reference standard. This method of data correction compares favourably with conventional XRF analyses performed on the same samples.A preliminary study based on pXRF analyses from a small number of drill holes found that a geochemical stratigraphy was evident in the pXRF data, and that this stratigraphy strongly controlled the location of Au mineralisation. The present study incorporates a much larger pXRF data set that samples a greater volume of diamond drill core and face channel samples and presents the data in a three-dimensional (3D) framework.This data set allows an investigation of the mineralogy of Au mineralisation with varying geochemical associations across the deposit. Historically, there has been a strong relationship identified between As and Au, which has caused issues with metallurgical performance, rendering some areas of the deposit only marginally economic. Utilising seamless data integration of the pXRF data set allows for recognition of the different styles of Au mineralisation using elemental concentrations and ratios from the multi-element analyses (Au:As, Au:As:Cu, As:Cu vs. K:V), and to visualise the distribution of these different mineralogical associations in 3D. The results of the 3D modelling and geochemical characterisation of the different styles of Au mineralisation are currently the focus of an extensive metallurgical testing program, the preliminary results of which are presented here.

Aug 22, 2011

By P Hodkiewicz

Recent structural interpretations based on historic stope shapes were used to develop a rapid and innovative method to domain and simulate structurally complex, high-grade gold veins at depth in the Edna May deposit. This involved ‘implicit’ modelling of drill hole data using Leapfrog software, which allows complex wireframe domains to be built and updated rapidly, compared to ‘explicit’ manual wireframing methods that are too subjective and time consuming. Conditional simulation was used for resource estimation, in order to simulate the highly variable gold grades associated with the veins. Similar modelling methods could be used to determine the mining potential of other historic gold deposits that are receiving renewed interest because of the high gold price.Gold at Edna May is hosted in the Edna May Gneiss, which is a WNW-striking tonalitic intrusion along a shear zone that dips approximately 45° towards the NNE. Gold occurs in multiple 0.5 - 5 m thick arcuate quartz veins that plunge steeply towards the west. Two phases of historic underground mining at Edna May (1911 to 1922 and 1935 to 1947) produced 360 000 ounces of gold at an average grade 19.5 g/t from seven ‘reefs’ to a depth of 240 m. This established Edna May as one of the highest grade gold mines in Western Australia at the time.Recent drilling by Catalpa Resources confirmed the potential for down-plunge continuity of high-grade veins. New structural interpretations, based on historic level maps and wireframe re-constructions of the arcuate stope shapes, were used as ‘structural trends’ in Leapfrog to model the mineralisation. The resulting wireframes capture the complex distribution of gold in the deposit and were used as domains for resource estimation.Conditional simulation using the Turning Bands method was used to simulate the expected variability of gold grades associated with this mineralisation style and the median of the 100 realisations was used to report an inferred resource. Results of this modelling method are being used to target vein extensions at depth, to consider different underground mining scenarios, and to assess the risks associated with developing and mining this high-grade and high-nugget gold deposit.

Aug 22, 2011