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By L Keeney

Cu-Au porphyry deposits are large tonnage low-grade resources dependent on processing large volumes of material. The ability to understand and predict comminution performance is critical, as it is frequently the rate-limiting step during processing. Parameters required from geometallurgical mapping and modelling of comminution performance are: A×b processing domains based on impact breakage variability, and BMWi processing domains showing grind response variability which lead to Mine throughput domains for a specific comminution circuit configuration. Due to the cost and/or large sample requirements of traditional comminution tests, insufficient data density and distribution of comminution indices commonly exist, making it difficult to model and map deposit scale variability. One method routinely applied to three dimensional domaining is to have an a priori zoning based on geological features (lithology, alteration, mineralogy, textures), and then apply to all material within a given domain the metallurgical values measured on a single sample or average of samples from that domain. The problem with this approach is that commonly the geological domains do not reflect comminution response, therefore compromising the quality of the average domain estimate. To resolve this problem an alternate integrated geometallurgical mapping and modelling method is applied to model and map comminution performance at Cadia East. This paper uses a data set of ~32 000 assay measurements and geological logging information, integrated with ~150 comminution measurements to analyse and develop proxy support models for comminution indices (ie A×b, BMWi, and throughput) based on inherent geological variability. Discrete downhole comminution processing domains are created, mapping orebody response while maintaining inherent variability.

Sep 5, 2011

By Claudio Bisso, Javier Vargas, Charles Lozano

"This paper summarizes the activities performed to predict SAG milling throughput at Minera Esperanza. Having highly reliable geometallurgical models aided by the new computer tools and specific metallurgical testing to rely on has become a major issue in recent times due to their impact on the business. Minera Esperanza’s SAG throughput model was constructed by characterizing the ore feed and operational parameters of the plant. Producing a robust model required satisfying number of requirements for the parameters used for both the ore and the plant as follow: 1) geologic and geometallurgical characterization parameters; and 2) parameters of a plant running at the rated production under optimum operating conditions. Obtaining these parameters required increasing the quantity of samples and metallurgical testing through drilling campaigns, mapping the drill holes and putting samples through various comminution tests while sampling all operational flows at the plant to obtain the metallurgical information for the operational parameters. The information was entered on the JKSimMet software to enable a throughput model to be developed to output SAG mill throughput predictions that are very close to actual throughput figures, i.e., accurate within a range of 2% on a monthly basis."

Jan 1, 2014

"The Dumont deposit is a large (1066 Mt probable reserve) low grade (0.27% nickel), nickel sulphide project located in the Abitibi region 25km west of Amos, Quebec. Royal Nickel Corporation acquired the project in 2007 and has since taken the deposit through pre-feasibility. And updated, revised pre-feasibility was released in July 2012.The disseminated nickel sulphide and alloy mineralization is hosted within the serpentinized dunite subzone of the Dumont Sill; a differentiated, pervasively serpentinized, ultramafic sill of komatitic affinity. Pentlandite, heazlewoodite and awaruite are the dominant nickel-bearing, metallic phases and can be recovered by conventional methods (flotation, mag separation). Non-recoverable nickel is also present within the silicate matrix of the serpentinized dunite and is locked in serpentine (Fe and Mg-rich variants) and minor olivine.A detailed mineralogical program including 1097 QEMSCAN® samples and 4300 electron microprobe points were undertaken to increase the understanding of the nickel deportment in the various recoverable and non-recoverable phases in a spatial context across the deposit. Eighty-three (83) metallurgical tests performed under a standard procedure have linked the mineralogy to metallurgical performance. This has allowed the creation and modelling of geometallurgical domains on a block by block basis to understand the recovery variation and metallurgical performance throughout the deposit. Understanding the spatial variability of Ni deportment in recoverable and non-recoverable phases through mineralogy is the key to understanding metallurgical performance thus, unlocking the value of the Dumont deposit and other large tonnage low grade ultramafic nickel deposits."

Jan 1, 2013

By Andres Salazar, Carlos Delgado Robles, Richard K. Preece

The paper discusses the evolution of the geometallurgical model at the Escondida mine in northern Chile, the world’s largest copper producer. It highlights the transition from early metallurgical forecasting methods to a comprehensive model that includes spatial distribution of metallurgical forecasts. This model helps in planning and adapting to the variability in ore characteristics, such as hardness and mineralogy, which affect processing performance.

Dec 1, 2023

By Andres Salazar, Carlos Delgado Robles, Richard K. Preece

Minera Escondida, located in the Antofagasta Region of northern Chile, is the world’s largest producer of copper as concentrate and SX-EW cathode. Projects to increase mill and flotation capacity began soon after start-up in 1990 to off-set decreasing copper grade. Subsequent projects had the objective to increase copper production through heap leach and SX-EW production and a second concentrator. The mine footprint concurrently expanded peripherally from the central high-grade enriched core of Escondida and then into the separate Escondida Norte deposit. Early in the mine life, metallurgical forecasting that was based on metallurgical composites of presumed ore types and historical plant production was adequate for operational planning, plant design, and project valuation. This approach became unreliable, however, as the increase in mine footprint was accompanied by an increased variability in key ore body characteristics such as hardness, copper-iron sulfide mineralogy, and sulfide liberation textures that were not reflected in the geological criteria used for ore type designation. The project study teams turned to small-scale physical and chemical tests to better characterize the spatial distribution of these key ore characteristics. Programs associated with capital growth projects were carried out through the mid-2000s to sample and construct a three-dimensional spatial model of hardness, copper sulfide mineralogy, and rougher flotation recovery from tests on 15-m drill core composites. Mathematical models were developed from the respective ore characteristic data to calculate throughput, flotation recovery, and concentrate copper grade. The spatial models were integrated with the concurrent mineral resource block model using standard geostatistical methods and the metallurgical process calculations were applied to the block estimates. The geometallurgical model, originally constructed on a project basis, is now managed by a dedicated team reporting to the manager of Geosciences & Resources Definition in the Escondida organization. The model has evolved with increasing complexity of the mine and processing plants and currently includes seven forecasting areas for three concentrators and four areas for two leach plants. Metallurgical forecasts of mill throughput, final flotation recovery, and concentrate copper grade still have the highest relevance to mine planning and optimization. Sample preparation, test procedures, and quality control methods are summarized for the ore characteristic tests important to these forecasts. Analytical results from recent annual sampling programs are presented for the hardness indices, rougher flotation recovery, and partial extraction copper analyses. Geostatistical analysis of the SAG mill hardness index is summarized as an example for the spatial estimation process. Mathematic models are presented for throughput (based on hardness indices), final flotation recovery (based on rougher recovery and plant calibration studies), and concentrate copper grade (based on sulfide mineralogy and empirical pyrite rejection studies).

Aug 31, 2023

By M Wortley, J Korteniemi, D La Rosa, L Rajavuori

Geometallurgical modelling of an orebody provides benefits to a mine by gaining a better understanding of the ore characteristics and how they affect the performance of the concentrator. With this knowledge, plant operating conditions can be adjusted to optimise throughput and recovery in advance of the arrival of particular ore types. Therefore, it is extremely important that the origin of the ore being processed is known as accurately as possible. Depending on the homogeneity of the ore characteristics, reliance on assumptions about stockpile residence times, scheduling and material handling can render the best geometallurgical models useless.The solution adopted at Agnico Eagle’s Kittilä mine was to utilise Metso SmartTags™ and in-house expertise to develop a system that continuously and accurately links geotechnical and lab data from the mine to the performance of the plant. This application presented several unique opportunities and challenges. For example, this was the first installation of a SmartTag™ system for geometallurgical modelling in an underground mine. Challenges included the fact that the system installation is routinely subjected to temperatures below -20°C.The system was installed and commissioned in early 2013 and has been operating continuously since. Kittilä has begun to see the benefits of the system, with an increased understanding of how different ores are processed in the concentrator. Other advantages include the ability to alert operators about the arrival of difficult ores and a better understanding of the ore handling systems.This paper describes the installation and use of the system at Kittilä and details some of the geometallurgical relationships that have been developed using the data collected so far.CITATION:La Rosa, D, Rajavuori, L, Korteniemi, J and Wortley, M, 2014. Geometallurgical modelling and ore tracking at Kittilä Mine, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 291–298 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By M Sciortino, J Korczak, J Muinonen, A St-Jean

The Dumont deposit is a large (1179 Mt reserve), low-grade (0.27 per cent nickel) nickel sulfide project located in the Abitibi region 25 km west of Amos, Quebec. Royal Nickel Corporation (RNC) acquired the project in 2007 and has since taken the deposit through to feasibility. The disseminated nickel sulfide and alloy mineralisation is hosted within the serpentinised dunite subzone of the Dumont Sill; a differentiated, pervasively serpentinised, ultramafic sill of komatiitic affinity. Pentlandite ((Ni,Fe)9S8), heazlewoodite (Ni3S2) and awaruite (Ni2.5Fe) are the dominant nickel-bearing metallic phases and can be recovered by conventional methods (flotation, magnetic separation). Non-recoverable nickel is also present within serpentine and olivine of the silicate matrix.A detailed mineralogical program including 1420 QEMSCAN« samples and 4400 electron microprobe points was undertaken to increase the understanding of the nickel deportment in the various recoverable and non-recoverable phases in a spatial context across the deposit. A total of 105 metallurgical tests have been performed under a standard procedure which have linked the mineralogy to metallurgical performance. This has allowed the creation and modelling of geometallurgical domains on a block-by-block basis to understand the recovery variation and metallurgical performance throughout the deposit. Understanding the spatial variability of Ni deportment in recoverable and non-recoverable phases through mineralogy is the key to understanding metallurgical performance, thus unlocking the value of the Dumont deposit and other large tonnage low-grade ultramafic nickel deposits.CITATION:Sciortino, M, Muinonen, J, Korczak, J and St-Jean, A, 2013. Geometallurgical modelling of the Dumont Deposit, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 93-100 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By P A. Montoya

La Colosa is a world-class porphyry Au project located in Colombia, currently undergoing prefeasibility analysis. As part of collaboration between AngloGold Ashanti and the AMIRA P843A GeMIII Project, the application of emerging geometallurgical characterisation testing and modelling tools has been incorporated in early stages of project development. The aim of the geometallurgical study is to map inherent comminution variability across the La Colosa deposit providing information critical for mine/mill design and optimisation. In this study, site-based data incorporating multi-element assays, quantitative analyse X-ray difraction QXRD bulk mineralogy measurements, EQUOtip rebound hardness data, and routine geological logging information from 59 diamond drill holes has been integrated with a range of geometallurgically specific comminution test (ie GeMCi, A × b, BMWi). The work in this paper demonstrates the integration techniques used at La Colosa to link routine data acquisition methods with comminution test results through the development of proxy support models. The integration incorporates a range of statistical techniques including principal component analysis and regression modelling. By creating proxy models, comminution index estimates can be propagated into the geological database enabling comminution processing domains to be defined. These domains provide the first spatial representation of comminution performance and variability at La Colosa and can be compared against traditional geological domains. This study provides the foundation for ongoing comminution characterisation as the La Colosa project evolves through project cycles into an operational mine.

Sep 5, 2011

By A Stradling

For a geometallurgical program to be successful, linkage must be made between the geologists and geostaticians who understand and model the orebody, the metallurgists who determine the value that can be extracted from the different geometallurgical units, and the mine planners who develop and optimise the plan to extract maximum economic value from the resource. One of the primary purposes of geometallurgical models is in the determination of the economic cut-off between ore and waste. Recognition of the level of confidence required in the estimation of grade, throughput and recovery is critical to the planning of a successful geometallurgical program. It also helps clarify the scope of work needed to mitigate risk at each stage in the development of a new mine projectThis presentation provides some of the author’s experience with development and application of geometallurgical models for existing base metal operations. It discusses how geological units defined by lithology, structure, alteration etc, can be translated into geometallurgical ore types defined by mineralogy, ore hardness, and flotation behaviour. Examples of how these characteristics have been used to estimate key economic parameters such as mill throughput and flotation recovery at two brown-field operations are provided. The first example relates to the modelling of metallurgical performance at Teck’s Red Dog zinc-lead mine in Alaska. Prior to 2000, zinc, lead and silver recoveries from a block of ore at Red Dog were either assumed constant, or were varied according to simplistic models. Throughput was not thought to vary substantially between blocks, so an average value was used for each blended stockpile. It is quite possible that some ore-value blocks were classified as waste, and some waste-value blocks treated as ore, as a result of poor understanding of the true economic cut off across the wide range of ore types observed at Red Dog. After an extensive flotation test program, the first assay-based zinc recovery model was developed for the Main pit reserve in 2003.**This is an abstract only. No paper was prepared for this abstract**

Sep 5, 2011

By J N. Farrell

Metallurgists frequently use a small number of large samples to characterise expected mill performance, with the a priori assumption that these few samples are representative of the entire deposit. Geometallurgical sampling is becoming more prevalent as a way to use many smaller samples to indicate the expected recovery as part of the Mineral Resource or Ore Reserve estimation.The evaluation of magnetite deposits involves specialised approaches to sample preparation, sample analysis and resource estimation. The sampling protocol for magnetite deposits will typically include the use of Davis Tube analysis. The Davis Tube is a mini-pilot plant that is used for determining the mass magnetic recovery from a small amount of sample ground to a specific size. The magnetic concentrate may then be analysed and together with the mass magnetic recovery, may be used to simulate the expected mill recovery. The magnetite sampling protocol is specific to each deposit, and is typically designed around a specific metallurgical flow sheet.During resource modelling, the mass magnetic recoveries and concentrate grades may be estimated directly or assigned to a block model using regressions with other chemical constituents. For estimation, the concentrate grades are weighted to account for the different mass magnetic recoveries of each sample and the impact of these differences on the concentrate estimates.

Sep 5, 2011

By D Lozada, A Salazar

Geometallurgy is a tool that, for more than a century, has been present in the implicit operations of mineral beneficiation. There’s a need to understand the characteristics of the material to be processed. This has led metallurgists to ask geologists what type of rock and mineralogy is entering the Beneficiation Plant and vice versa. The geologist needs to understand the beneficiation process in order to be able to carry out the production programming. The paradigm is whether geometallurgy can be applied to small-scale mining or if it is only aimed at large companies that invest millions of dollars to conduct studies. With this work, we provide an example of how geometallurgy can help improve the processes of a small mining company located in Ecuador (South America). We performed characterizations of geological and mineralogical and metallurgical tests in universities and the National Research Institute of Geological Metallurgical Mining. The origin of the theme is based on the fact that gold has been detected in the final tailings. The flotation concentrates meet the standards in terms of the content of economically profitable metals, but this isn’t the case with regards to the percentage of arsenic, which has hindered sales. The hypothesis is: conducting technical and scientific research will optimize the metallurgical process for the recovery of gold and concentrates. The referential framework is the mining geology of the Bella Rica District, current status of the Beneficiation Plant. In the theoretical framework there are parameters of the veins, comminution operations, gravimetric concentration, flotation, and cyanidation. The methodological framework contemplates the characterization of the gold ore, the chemical, mineralogical, textural, metallurgical analysis and the interpretation of the results. Thus, the design of a geometallurgy model of the deposit, with its main characteristics, is a conclusion that serves as a basis for the proposal of the optimization of the metallurgical process.CITATION:Lozada, D and Salazar, A, 2018. Geometallurgy applied to small-scale mining: a case study, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 153–162 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

By Kari Niiranen, Andreas Fredriksson

LKAB (Luossavaara-Kiirunavaara AB) is operating iron ore mines, concentration plants and pelletizing plants in Northern Sweden. Geometallurgy, which combines geological and metallurgical information is not a new way of thinking at LKAB, but rather a revised and updated version of an old working process. A project called "Silica in the Mine" which started in 2007, was an important reason to set a new focus at the geometallurgy. The target of the project was to develop a simplified method in laboratory scale to predict SiO2 grade in the magnetite concentrate in Kiruna and further predict the physical properties of the crude ore with respect to processing characteristics. The connection between mineralogy and products properties have started to be even more vital and necessary to examine due to the future exploiting new iron ore deposits. Geometallurgy at LKAB can be described as a mental and strategic framework where the Research and Development department (R&D), and others within the organization of LKAB, aims towards the connection of the minerals-production-products. It could in its basics be called "research & development", but it must be clarified that changes have been made, mainly due to the development on the instrumental analysis side. LKAB’s idea is to work quite broad, with internal educations, an active working process in ongoing projects, together with external parties (such as universities), with several PhD-projects and an upgrading on the instrumental side at the LKAB Research & Development department. This paper is a summary about the concept Geometallurgy at LKAB and some of the actions within its framework.

Jan 1, 2014

By C M. W Boyle, E K. C Phuak, A Lewan, E Ryan, M D. Paine, P H. Mackenzie

"Rio Tinto Iron Ore (RTIO) has an extensive history in the application of geometallurgy to the iron ore value chain. Fundamental to this has been the geological logging of material types which are assigned processing attributes such as lump per cent and density. Initially these were used for product (lump and fines) grade predictions in relation to grade blocks to be used within short-term planning horizons.More recently the predictive reach of the material types and their associated processing attributes has been extended due to their inclusion into geological block models. These predictions can now be used to influence mine plans across multiple planning horizons in such a way that the extremes of geometallurgical properties can be pre-empted and managed thus improving efficiency. Spatial material type domains are also used in the planning of metallurgical drill holes to ensure greater representivity of material than was typically obtained by chemical and/or stratigraphic criteria alone.Material type logging has also been enhanced by the introduction of modern, rapid mineralogical techniques that have complemented visual logging. This has enabled the identification and quantification of contaminant minerals and their relationships with host ore types to be established. This data is used to better manage product grade predictions and identify risks to the short-term plan.Work is ongoing in RTIO to further refine logging based predictions and in addition apply them to new areas of the business. This work requires collaborative and multidisciplinary teams working on an integrated approach combining geology, metallurgy, technology and innovation, mine planning and technical marketing.CITATION:Paine, M D, Boyle, C M W, Lewan, A, Phuak, E K C, Mackenzie, P H and Ryan, E, 2016. Geometallurgy at Rio Tinto Iron Ore – a New Angle on an Old Concept, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 55–62 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By V Liebezeit

Data management is a significant, but perhaps unrecognised, consideration for any organisation embarking on a geometallurgy program. While resource geologists are accustomed to dealing with thousands or millions of samples and their associated assays, metallurgists and mineralogists have traditionally carried out only a few expensive and complicated tests and consequently tend to manage the resultant data in spreadsheets. The emerging discipline of geometallurgy arrives with significant challenges as a result of the sheer volume of data generated. As an example, the Olympic Dam geometallurgy program has generated more than:60 000 physical subsamples analysed for up to 30 analytes; 25 000 spreadsheet-based laboratory test results; 30 000 sized fractions analysed via QXRD, MLA and/or QEMSCAN;multiple external providers of data, and more than seven terabytes of data. Considerations for any geometallurgy data management system include storage space, data integrity, accessibility, traceability (sample provenance), maintenance and ease of use, integration with data providers and the ability to modify the system to adapt to changing requirements. Further, aspects of a geometallurgy program, such as conducting a range of tests on one sample, producing subsamples such as concentrates and tailings, compositing and routine QA/QC may not be well handled by existing software and providers geared to standard geochemistry, mineralogy or metallurgical test programs. The development of a geometallurgy database using existing software (AcQuire), and the associated file management system will be described for a large geometallurgy program at Olympic Dam. As with many aspects of geometallurgy there is no approach that meets the needs of every site or program. Recognition of data management as an issue, a structured approach in the program planning phase and commitment to executing the strategy will increase the chances of successfully mining the geometallurgical data.

Sep 5, 2011

By G Williams

Somewhat to the surprise of many heavy mineral sands (TiO2 and zircon) producers, there are important geological structures within their typical placers and aeolian sands deposits that affect plant metallurgical performance. After many years of operations, even experienced producers have encountered unexpected changes in production, product quality and recovery. After looking in all the obvious (but wrong) places, it is recognised that the mine has advanced into ore with different separation characteristics. Metallurgical process response can vary significantly between ore sourced from different geological domains. The mineral characteristics that are exploited for effective separation may be associated with differences in the depositional environment, or be post-depositional in origin. Surface coatings that interfere with electrostatic separation might be associated with paleo-water table movements. Major storm events in the deposition history can also leave distorted mineral assemblage through stranded formations or incisions in older deposits.Apart from the influence on capital and operating costs, geometallurgical variances add another dimension to orebody modelling. Each domain could have specific recovery, mineral assemblage and product quality values to be considered in the value model. Project success is often directly dependent on understanding the geometallurgy of the resource. Tailoring the exploration and early process flow sheet development programs to account for such variances should be standard practice. Such practices have had a chequered history in the mineral sands industry, with sophisticated processes having been developed, only to be shelved for ‘economic’ reasons, and then once again ‘discovered’ when problems re-emerge.It is clear that knowledge gained through a higher level understanding of the changing mineral separation characteristics and advance warning of mineral behavioural differences can mean the difference between lost recoveries and disappointed customers or well timed capital plans and maximised revenues.

Oct 5, 2011

By L O’Connor, S C. Dominy

"Geometallurgy is an important addition to any evaluation project or mining operation. As a discipline, it seeks to maximise the net present value (NPV) of an orebody while minimising technical and operational risk. It also aims to promote sustainable development and initiatives by ensuring that all stages of extraction are performed in an optimal manner from a technical, environmental and social perspective. To achieve these goals, development of innovative technologies and approaches along the entire commodity value chain are being established (Glass, 2016). Geometallurgy has been shown to increase operational stakeholder collaboration, creating an environment for knowledge sharing and improved data acquisition and interrogation, with the end result being the integration of such data into mine planning and scheduling. All of these aspects create better business optimisation, utilisation of staff and targeted and realistic key performance indicators.The mining industry faces numerous challenges including, but not limited to:declining ore gradesgeometrically and/or internally more complex depositsdeep-seated deposits, with potentially high in situ stress regimesincreasing quantities of mine waste that needs to be managed appropriatelyhigher energy, water and chemical costsprocessing of more challenging and refractory ores – textural complexitiesstricter environmental/permitting conditions – so-called ‘licence to mine’increasing demand for specialist metals (eg rare earth elements, In, Ge, Te, Rh, Se, Ga and Li)commodity market volatilitya difficult funding environment.Given these challenges, geometallurgy provides the opportunity to control or at least manage some of them.CITATION:Dominy, S C and O’Connor, L, 2016. Geometallurgy – Beyond Conception, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 3–10 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By S Robinson, A Turner, R Dale, C Butler

"Sandfire Resources NL- (‘Sandfire’) DeGrussa definitive feasibility study (DFS) identified geometallurgy as a major factor in achieving optimum plant performance at the DeGrussa mine. A geometallurgical initiative was created to proactively investigate this issue, and a key initial achievement was the 2013 paper by Condon et al (2013) on developing a working geometallurgical model from first principles. Significant advancements in Sandfire’s geometallurgical understanding since that publication now shape how information is presented and communicated.The main geometallurgical parameters so far identified as critical factors affecting plant performance are Cu:S ratio, iron sulfide mineralogy, talc carbonate content and sphalerite content. Apart from specific mill strategies, geometallurgical issues have been managed through communication between departments and strategic run-of-mine (ROM) pad management.This paper uses the current theories of geological evolution of the volcanogenic massive sulfide (VMS) deposit at DeGrussa, to discuss the variability between the orebodies C1, DeGrussa (sea floor mounds) and C4, C5 (sub-sea floor replacement) to highlight the different issues each orebody is expected to encounter when processing.A zone of altered low-grade mineralisation surrounds the main orebodies at DeGrussa, referred to as a halo. Talc minerals are often patchy within this halo and often cause significant recovery issues during processing. This halo has been successfully modelled using MgO as a proxy. The ability to model the talc material assists with both identifying potentially problematic zones for processing and geological interpretation of the ore deposits evolution.Early in geometallurgy studies at DeGrussa it became apparent that it would be useful to identify processing performance prior to mining. This necessitated the incorporation of specific sulfide species into the mining block model. These attributes are interpolated from the logged sulfide estimates allowing a clear picture of the abundance of each mineral type within a defined area.In conjunction with the block model a geometallurgical factor (GMF) graph was developed, identifying sulfide mineralogy based upon mineral assays. These two recent additions to the model provide a clear picture of the nature of the ore sources that will be presented to the processing plant.The future of geometallurgy at DeGrussa will see these tools used to aid mine scheduling with a view to further improve processing recoveries.CITATION:Butler, C, Dale, R, Robinson, S and Turner, A, 2016. Geometallurgy – Bridging the Gap between Mine and Mill: a Case Study of the DeGrussa Geometallurgy Program, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 77–88 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By J Beniscelli

Some words to honour Pedro:Pedro was among the few persons with a very high level in geology modelling, resource and reserve estimation, geometallurgy development, sampling theory applications and a deep understanding of the mining industry needs. He had brilliant ideas about new developments on economic geology. He was always looking at the long-term and proposed challenging questions a decade in advance on their solution.The fundamental aim of geometallurgy is to add economic value to the mining of mine resources by timely providing information and knowledge about the relevant metallurgical variables represented by their space models. In this manner, geometallurgy allows obtaining the optimal design of a project, mitigating processing risks, optimising and supporting production plans and identifying and assessing mining business opportunities.This paper describes the conceptual framework and geometallurgical definitions and some of Codelco’s experience during the last 15 years.

Sep 5, 2011

By R. Bridge

Mining companies are progressively finding themselves having to develop operations for more complex, deeper ore bodies, which require the use of more complicated mining and mineral processing methods. This coupled with the generally increasing trend of higher capital and operational costs have led to a need in the industry for improving ore body knowledge, mining and mineral processing. Geometallurgy is a relatively new concept that can link the three aspects, and when used effectively it is a method that can produce the necessary information for designing and building operations for reliable and optimum performance. Geometallurgy not only involves the integration of geological, mining, and metallurgical fields, but it can also be expanded to include environmental and economic information to produce a block model that can be used to obtain the best outcome in terms of plant response and plant sustainability. The geometallurgical program should not end once the block model has been populated. A detailed geometallurgical approach should be applied to all stages of the operation encompassing sample selection, through to equipment sizing and production forecasting. It can also become a useful optimisation tool thereby allowing the operation to be proactive rather than reactive against changes in the ore characteristics. With the development of metallurgical performance predictors it is possible to quantify how the ore will behave in the process plant in terms of throughput, recoveries, reagent consumption, etc. Therefore, in terms of responsible mining and sustainable resource development, a geometallurgical approach to operations is the logical step for plant development. In this paper we describe the state of the technology with respect to the application of geometallurgical modeling and its utilisation in the fields of design, forecasting and optimisation of mining operations.

Aug 1, 2013

By Michel Brissette, Shaheer Sanuri, Veroljub Mihajlovic

"The main purpose of geometallurgy is to improve the mine planning by mapping hardness and throughput into the mine block model using geostatistics to eliminate the large production fluctuations caused by the ore hardness variability coming from different parts of the pit. However, not all grinding testwork available commercially can be applied to geometallurgy because of large amount of sample required and the associated cost per test. Geometallurgy is now being used in designing grinding mill but as the mining project progress, the accuracy of engineering must improve from 30-35% during the scoping study to 10-15% at the bankable feasibility stage and less than 5% for Engineering Procurement and Construction Management. For SAG milling, the SAG Variability Test (SVT) is an abbreviated version of the standard SAGDesign test developed for this geometallurgical need. The same amount of ore than the original test is ground for three cycles into an open batch SAG test and then the SAG pinion energy is predicted to the standard end point of 80% passing 1.7 mm. For ball milling, a Bond Variability Test (BVT) was also developed using the SAG ground ore from the SVT. The Bond ball mill grindability (Gpb), corresponding to the average of the net grams per revolution from the last three cycles of the Bond test, is also predicted from the third cycle. The relative error for both the predicted SAG ore hardness (WSVT) and Bond Work Index on SAG Variability ground ore (Sv-BVI), in kWh/t, averaged 5.5% and 3.8% respectively compared to the SAGDesign testwork values and are within 7% and 10% respectively from plant benchmark and within 7% from the samples sent to all partner laboratories. Both tests can be continued to measure the true hardness necessary for mill sizing. This article discusses the development of these two new tests, SVT and BVT, their potential use and accuracies in any geometallurgical program."

Jan 1, 2014