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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 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 W J. Shaw

Geometallurgical modelling is now a hot topic in deposit evaluation and in optimising mine performance; however, its history is long and varied. Historically metallurgical sampling has frequently suffered from a lack of data due to the cost of producing representative bulk samples. In the early 1990s geometallurgical modelling similarly suffered from a lack of data due to complex, time consuming and expensive sampling techniques. More recently, simple and relatively cheap tests for geometallurgical variables such as hardness, grindability, throughput, SAG power index, bond work index, crushing index, mineral recovery and concentrate grade have become widespread. The cheaper sampling has resulted in relatively large geometallurgical databases. However, most of the geometallurgical variables sampled are implicitly (and incorrectly) assumed to be additive when modelled by traditional geostatistical techniques, often leading to ill-informed and costly decisions. Geometallurgical variables are mostly non-additive so the current geostatistical challenge is to develop new approaches to dealing with this type of data. This paper briefly describes a historical case study of geometallurgical modelling of the George Fisher Pb-Zn mine completed in the mid 1990s, then outlines some of the current misconceptions of geometallurgical data and modelling techniques regularly applied to it, and finally discusses some recent developments in geometallurgical modelling, with examples from a number of current clients indicating the direction forward.

Jan 1, 2009

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 Y Xie, L O’Connor, S C. Dominy

Sheeted vein gold deposits are characterised by multiple subparallel veins and often free milling gold. Variability in gold grade and recovery parameters are enhanced by poorly designed sampling and test work protocols. Poor quality samples generally equate to an enhanced nugget effect. A sample can be described as being representative when it results in acceptable levels of bias and precision. Total sampling variability can be quantified by the relative sampling variance, which measures the total empirical sampling variance influenced by the heterogeneity of the lot being sampled under the current sampling / test work protocol. Effort should be made to minimise the relative sampling variance through Theory of Sampling (TOS) and quality assurance / quality control (QA/QC) application. This contribution reports on a case study that exemplifies how high-quality grade and recovery data can be gained from a well-designed and planned drilling, sampling and test work program, followed by bulk sampling. Results across historical resource drilling, geometallurgical drilling, laboratory assay / test work, geometallurgical modelling and a bulk sampling/pilot processing study are reconciled. A whole core, entire-sample test work protocol was used to acquire fit-for-purpose gold grade and recovery data for inclusion into a Pre Feasibility Study reported in accordance with the JORC Code.CITATION:Dominy, S C, O’Connor, L, Xie, Y and Glass, H J, 2017. Geometallurgical sampling protocol validation by bulk sampling in a sheeted vein gold deposit, in Proceedings Eighth World Conference on Sampling and Blending , pp 185–196 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2017

Geometallurgical Study of Copper Oxide Mineralisation Hosted in Gravels of Different Physical Quality

Sep 13, 2010

By G Harbort, C Sola

The rapid development of geometallurgy in the mining industry has occurred in relatively recent times. Its importance as an independent discipline in the mineral processing world has been emphasised and recognised. To a large degree, this is the result of a growing understanding of the ore type being processed and their application to provide better metallurgical responses in different mineral processing techniques. The development has matured from early progress through to geological knowledge and into the realm of the metallurgist and mining engineer. Working together, they have developed a powerful framework that will interpret a body of mineralisation into measurable properties.The integration of geometallurgy and operations has become of increasingly important due to improvement in understanding of an orebody as a natural system formed by a number of processes and with a definite fabric of mineralisation within different geological domain. These have to be taken into account when creating techniques that will enable operations to extract the valuable components from a distinct type of ore. Incorporation of such knowledge at an early stage of development, such as the feasibility stage significantly reduces the project risk.This paper is written from the unique perspective of a process engineer embedded within a geological team. It discusses issues such cross discipline communications and misconceptions and details the numerous tricks, traps and treasures of geometallurgy encountered during defining of the Seminco and Taysan resources.CITATION:Sola, C and Harbort, G, 2012. Geometallurgy - Tricks, traps and treasures, in Proceedings 11th AusIMM Mill OperatorsÆ Conference, pp 187-196 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Oct 29, 2012

By K Ehrig

You are a geologist, geometallurgist, or metallurgist/process engineer and are fortunate enough to work for an organisation who asks you to design/execute a geometallurgy program. What seems like a simple request is actually not a trivial exercise. æRecipeÆ style manuals are not readily available. However, many æexpertsÆ are lurking around willing to deliver solutions which will solve all of your problems. Even though similar ore deposit styles (e.g. porphyry Cu, IOCG, Ni-laterites, calcrete hosted U, etc.) have many similar characteristics, each ore deposit is unique. Hence your geometallurgy program needs to be æfit-for-purposeÆ. This paper offers some insights gained via designing and executing geometallurgy programs from exploration through to production, and working at a mine where you are held accountable for your metallurgical performance predictors.CITATION:Ehrig, K, 2013. Geometallurgy - What do you really need to know from exploration through to production?, in Proceedings MetPlant 2013 , pp 28-33 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 15, 2013

By J D. Lubben

Hibbing Taconite is a Lake Superior-type granular magnetite taconite deposit occurring within the Biwabik Iron Formation along Minnesota’s central Mesabi Iron Range. The deposit is situated on the northern margin of the Proterozoic Animikie Basin. The deposit strikes northeast, dips gently southeast, and occupies 10 km of strike length. Mining focuses on 50 m of granular cherty and laminated slaty taconite within the Lower Cherty member.Ores generally consist of a quartz, magnetite, siderite, ankerite, minnesotaite, stilpnomelane, and haematite mineral assemblage. Processing is optimised by exploiting the physical and chemical variations that exist between three major ore types. Taconite ore averages 20 per cent magnetic iron (MagFe), 27 per cent weight recovery (WtRec) and produces a final concentrate with 4.5 per cent silica (SiO2). Since 1976, production has totalled approximately 237 million long tons (Mlt) of pellets (8 Mlt per year rated capacity).Ore processing uses a simple fl ow sheet of autogenous grinding (<0.044 mm) followed by two phases of wet magnetic separation, fi ltering, limestone/bentonite addition, balling, and firing to create pellets averaging 66 per cent total iron. A Liberation Index (LIS) is used as a primary guide for ore grading and metallurgical control. Grind requirements, magnetite liberation and silica grade are closely monitored to ensure plant optimisation and product quality.A recent program of benefi ciation of low-grade ores by in-pit crushing and dry magnetic cobbing has demonstrated that low-grade ores (<17 per cent MagFe, <25 per cent WtRec) can achieve a signifi cant metallurgical upgrade (up to 25 per cent MagFe and 40 per cent WtRec). This operation recovers 60 per cent of the total crushed volume, and has a calculated effi ciency factor (magnetic iron recovery) of 79 per cent. This paper discusses the benefi ts of this upgrading and its effects on ore blending and processing.

Jul 11, 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 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 D Gerrard, J Begelhole, J Gerber

The Iron Magnet deposit has been mined since 2007 when Arrium (then OneSteel) commissioned the magnetite concentrator to supply feed to the pelletising plant in Whyalla. The concentrate quality requirement for the customer required consistent product with minimal variability. In the early stages of operation, it was identified that the feed variability introduced significant changes in the concentrate quality, which was outside the acceptable customer limits.In 2011, a geometallurgical regression model was developed that allowed for the estimation of concentrate quality produced from the feed material. This was based on a laboratory-scale Davis Tube Recovery (DTR) test performed on the feed material. The objective of the project was to characterise the raw ore in the pit to allow for blending prior to crushing. By blending the feed to the concentrator, minimal concentrate quality variation within the plant was achieved. The orebody was divided into geometallurgical classes, called ore types, based on the mineral texture and magnetic mass recovery. Each geometallurgical class consisted of material with similar metallurgical performances. For each individual blast pattern, the ore was grouped into the geometallurgical classes and a composite sample was created. The composite sample was put through the laboratory-scale DTR test and the results were used to estimate the metallurgical performance of the material.The characterisation process and feed pile build methodology was applied in early 2013 and went through an optimisation and streamlining phase. Since the implementation of the geometallurgical characterisation process, the plant has seen a significant reduction in concentrate variability and measurable throughput gains. The characterisation process has also increased the amount of material that is now classified as ore.CITATION:Gerber, J, Gerrard, D and Begelhole, J, 2015. Geometallurgy of the South Middleback Ranges magnetite deposit – predicting plant performance from the pit, in Proceedings Iron Ore 2015, pp 555–560 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By J Jackson

The term geometallurgy (or geometallurgical) first appeared in the literature some 40 years ago and has a wide range of definitions and perspectives which increases the barriers of communication between practitioners and across functional groups and management levels within organisations. However the consistent theme running through the diversity of definitions and perspectives is the requirement for close collaboration between the relevant disciplines. This concept of geometallurgy arguably goes back to the earliest days of the exploitation of mineral deposits, through the mid-1500s to the beginning of the 20th century.This holistic and integrated view was diminished during the 20th century due to a number of factors which included the commencement and continuing upward trend of large-scale mining and the expansion in production, the rise of scientific and classical management theories and methodologies, increase in specialisation and the development of traditional project planning. The re-emergence of geometallurgy in the late 20th century required the relevant functional units and disciplines to collaborate as a team. This necessitates a common understanding that the geometallurgical program’s goals must be obtained, which requires clear and consistent communication, particularly with the modern trend of virtual teams.A multi-dimensional construct is proposed to assist in providing a consistent approach in the communication of the context and purpose of both general and specific geometallurgical programs, thus simplifying communication. This geometallurgical construct consists of the dimensions of process span, response knowledge, variability knowledge, spatial knowledge, application and project phase in relation to extraction process(es) applied to geological materials from a mineral deposit. These dimensions are then linked to the phase of mineral project development in which the geometallurgical program is being applied, which ranges from advanced exploration through to operational execution. This paper outlines the multi-dimensional construct with examples of how the context, purpose and scope of geometallurgical programs can be clearly delineated and communicated.

Sep 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