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By A Guillen, J-P ChilFs

Most 3D geological modelling tools were designed for the needs of the oil industry or detailed mine planning and are not suited to the variety of situations encountered in other application domains. Moreover, the usual modelling tools are not able to quantify the uncertainty of the geometric models generated. The potential field method was designed to build 3D geological models from data available in geology and mineral exploration, namely the geological map and a digital terrain model (DTM), structural data, borehole data and interpretations of the geologist. This method considers a geological interface as a particular isosurface of a scalar field defined in the 3D space, called a potential field. The interpolation of that field, based on cokriging, provides surfaces that honour all the data. The 3D model and its parts are always consistent with the observations. New developments allow the covariance of the potential field to be identified from the structural data. This makes it possible to associate sensible cokriging standard deviations to the potential field estimates and to express the uncertainty of the geometric model. It also, for the first time, gives a statistically optimal, geologically sound way of interpolating geology, other than directly joining the dots as you do with CAD. Practical implementation issues for producing 3D geological models are presented: how to handle faults, how to honour borehole ends, how to take relationships between several interfaces into account, how to model thin beds over many kilometres, how to optimise lithological properties and how to integrate gravimetric and magnetic data. We describe all geology surfaces and volumes using implicit functions. These are then rendered onto the required sections, plans, etc. The estimation of orebody grades and tonnes, using an unbiased and optimal geostatistical technique, makes use of the stratigraphically bound 3D geology model. An application to the geological modelling of the Hamersley iron ore district, Australia, is briefly presented.

Jan 1, 2009

By C Tapia, B Hay

There is a close relationship between the mining industry, economic growth, and technological and social development. Mining activities benefit all economic agents, but only during a timespan determined by available reserves, primarily driven by internal factors such as production rate, technology and costs, and external factors such as prices determined by the market and taxes and royalties controlled by governments (Gordon and Tilton, 2008; Henckens, 2021; Tapia Cortez et al, 2018). The intense use of Mineral Commodities (MC) needed to maintain the current lifestyle has placed ore depletion as one of the main threats to sustainable economic, social and technological development. However, ore depletion does not only arise due to the finite nature of MC, price fluctuations or technological challenges. It is also triggered by the ‘economic limits of extraction’, determined by the optimisation of financial factors and technical restrictions within the regulatory framework (Henckens, 2021). Most reporting standards – if not all – define ore reserves as ‘the economically mineable part of a Measured and/or Indicated Mineral Resources’ determined by the technical and economic viability of extracting, processing and commercialising MC having the NPV as the fundamental decision – making tool (JORC, 2012; Krzemień et al, 2016). However, is the NVP an ‘economically’ basis index able to capture the complexity of economic phenomena? No, it is not, and it is crucial to define what is economic and financial. Although related, they are different disciplines. Economics studies the behaviour of the different market agents, including human behaviour and policies and explains the factors involved in the scarcity (or surplus) of goods and services. Finance focuses on financial systems and managing funds considering the time, cash available, and risk. It involves banks, loans, investments, and savings and can be considered a small subset of economics (Simon, 1959; Tapia Cortez et al, 2018). Given the economic nature of ore Reserves, endorsed by governments (Figure 1), NPV is an incomplete tool to determine ore Reserves as it limits the problem to simply maximising cash flows instead of optimising the economic benefits for all economic agents. In addition, using the rigid scheme of controlling taxation – unable to adapt to new market or economic conditions and systematically increasing – within the NPV framework only increases the sub-optimisation of ore reserves, mainly due to the systematic taxation rise. Short-term benefits of higher taxes and royalties are unlikely to offset the impacts of reducing exploration and project development in the long-term, which not only boosts ore depletion concerns but also reduces competitiveness, threatening economic and social welfare (Fisher, Cootner and Baily, 1972; Gordon, Bertram and Graedel, 2007; Lilford, 2017; Mardones, Silva and Martínez, 1985; Radetzki, 2009; Rodrik, 1982; Tan, 1987; World Bank, 2000). Holistic methods and collaborative tools, able to dynamically simulate and assess how changes in the technical settings, regulatory framework (taxes and royalties), and financial factors affect the availability of ore reserves and the impact for all economic agents, should be incorporated into the evaluation process to fill the gap.

Aug 2, 2023

The variation of austenitic grain size with temperature for the steels XKSlSO and XK9261 was determined using the vacuum ctching technique.It is shown that the effect of temperature on the mean grain intercept is relatively small, up to approximately 950°C. Above this temperature the rate of increase of grain size rises sharply.Within the limits of the 1-4 hr vacuum etching times used the effect of time at temperature is relatively small on the ASTM grain size of the steels.

Jan 1, 1967

By M Bettison, R Marton, R Wright, M Lowry

Depending on the geological setting, waste rock from mining can present risks to achieving acceptable closure outcomes. In the Pilbara iron ore mines, the majority of waste rock is geochemically inert. However, small percentages of pyritic material with the potential to generate acid and metalliferous drainage (AMD) require considered management within mine waste stockpiles designed to minimise AMD release to the environment. A larger percentage of waste rock has physical characteristics (e.g. erodibility) that may impact upon long-term landform stability. CITATION:Marton, R, Wright, R, Lowry, M and Bettison, M, 2018. The golden thread of waste characterisation from exploration drilling to waste rock placement, in Proceedings Life-of-Mine 2018, pp 90–92 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 25, 2018

By M Campbell, A Jeffcoate, J-C Vannay, B Perriaux

Phyllite waste rock at the Simandou Pic de Fon and Oueleba Iron Ore deposits (Guinea, West Africa) variably weather to form clay-rich rocks. This weathering modifies the mineralogical, geochemical and mechanical properties of the phyllites. Final pit walls will largely be formed in phyllite, so it is critical that the slope design takes account of the distribution and variability of weathering within this material. Phyllite intact material strength has been correlated with geochemistry (ie mineralogy) facilitating the establishment of domains of intact rock strength (IRS). In order to calibrate this geochemically-based strength model, core from diamond drilling (DD), comprising a variety of phyllite material types (from soft clay to moderate strength rock), was geotechnically logged to assess intact strength; further validation was achieved by uniaxial compression (UCS) testing and point load tests (PLT). The correlation between geochemistry and strength offers a potentially powerful tool for differentiating basic mechanical properties of the rock mass, especially at Simandou where a significant proportion of the resource drilling is done by reverse circulation (RC). Unlike DD, reliable measurements of material strength from RC samples can prove difficult, especially in clay-rich material. Therefore, gaining information from routine geochemical assay results, independent of the sampleÆs physical integrity, is a valuable and cost-effective source of reliable empirical data. Data acquired using this approach provides an opportunity to develop strength domains, which are integrated into mine planning block models. In combination with other geotechnical characteristics, this can be a valuable input to the development of geotechnical models. This technique has allowed spatially representative rock strength data to be derived and offers the potential for optimising pit slope angles in areas where hitherto conservative design criteria had been assumed.CITATION:Jeffcoate, A, Campbell, M, Vannay, J-C and Perriaux, B, 2013. Modelling intact rock strength of clay-rich rocks with geochemistry at the Simandou iron ore deposit, Guinea, West Africa, in Proceedings Iron Ore 2013 , pp 193-202 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 12, 2013

By A Jewbali, R Perry, R Inglis, L Allen

"The use of conditional simulation to characterise mine plan uncertainty is increasing for the assessment of risk in mining projects. While the development of grade uncertainty profiles is relatively straightforward and can be validated using standard geostatistical techniques, the addition of geological uncertainty to evaluate total risk remains problematic. Some of the problems associated with geological uncertainty methods include the clustering of data in favourable geologic units, difficulty in training image definition and the inability to address change of support issues for categorical variables. Despite these obstacles, the importance of geological uncertainty as a contributor to total uncertainty has prompted Newmont to explore and evaluate the use of various techniques (and combinations of techniques) on different deposit types.Two orogenic deposits of different geological complexity were selected for the study: Subika, a shear zone-hosted deposit, and Merian, a deposit containing gold mineralisation associated with quartz vein zones and stockwork within which are found higher-grade quartz breccia zones. Newmont trialled various categorical simulation approaches to determine the applicability of these methods for each deposit type and the effect of parameter choice on the width of the uncertainty interval. Some of the techniques that were trialled include multiple point statistics methods, sequential indicator simulation using local probabilities as well as variations of these methodologies.The goals of this study included: gaining an understanding of which techniques may work best in which deposit types gaining an understanding of the intricacies of each method gaining an understanding of the effect that each method has on total uncertainty analysis.This paper presents a comparison of the various techniques and makes recommendations for their use in uncertainty analysis.CITATION:Jewbali, A, Perry, R, Allen, L and Inglis, R, 2014. Applicability of categorical simulation methods for assessment of mine plan risk, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 85–98 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By J Santana, V Ferraz, G Pinto, G Cruzado

Morro Agudo is an underground zinc and lead mine owned by Nexa Resources. The mine uses room and pillar as the main mining method. The recovery of pillars as well as the opening of new excavations using sublevel stoping as mining method has been studied. On some occasions, the need to recover pillars and open a stope by using the sublevel method happens in a region that is already excavated or in deeper areas than those mined so far. These changes represent a major geotechnical challenge due to the complex openings of the mine and interaction between two different mining methods. Historically, geotechnical mapping, kinematic analysis and a 2D numerical model were used to evaluate the new mine openings, and in 2021, 3D numerical model was introduced, which enabled global and local assessment of new excavations impact and the stability of openings after recoveries. The 3D model, made with MAP3D, is used to evaluate each pillar to be recovered, considering the spans of the resulting openings, the ideal sequencing of removal to maintain stability, in addition to the impact and geometry of the pillars left in the chambers. Pillar recoveries done in 2021 and the impact of it on the pillars left were the sources of the back analysis to calibrate parameters inputted on numerical model to assess recovery on new chambers and Phyllite has been considered into the model and it has been a source of instability due to its parallel position to roof of room and pillars and stope hanging walls.

Nov 29, 2022

By B E. Hall, D B. Kahler

"'Optimisation' has become a catchcry among many mining companies looking to tell the market how mining businesses will be improved and shareholder value increased. Consequently, the term 'optimisation' has been adopted by many service providers as they look to assist mining companies in achieving their objectives. But the explosion of services and products being offered with the label 'optimisation' has created some confusion. Mining companies ask for help in 'optimising' and service providers offer their assistance because they have a product that has the word 'optimisation' in its title. This is of course an over-simplification, but not by much! The authors' discussions in recent years with both mining companies and service providers have uncovered a number of very different definitions of optimisation.This paper provides a framework for identifying the scope and approach of different mining optimisation products and services, particularly the distinction between optimisation of components of the operation and the business as a whole. The different types of business optimisation are discussed, highlighting the failings of the mining industry's typical approach of strategy selection (as opposed to strategy optimisation). Mining business optimisation is discussed as a wicked problem, with the implication of this on how strategy optimisation models should be used and what the objectives of a business optimisation study should be.Case studies are also included to illustrate how fully flexible strategy optimisation models have been applied to assist decision-makers understand the impacts of changes in one part of the operation on the whole mining and treatment process, from geological models to the sale of product to customers.CITATION:Kahler, D B and Hall, B E, 2016. Strategic decision-making in mining – business optimisation using flexible evaluation models, in Proceedings Project Evaluation 2016, pp 215–225 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Mar 8, 2016

By S M. J Koleini, F Hedjazi

The purpose of this research was to study the calcination of lead-zinc flotation tailings from the Angouran lead and zinc flotation plant in Iran as a pre-concentration step prior to hydrometallurgical processing of the oxidised tailings. There is an abundance of these tailings in the Angouran region and making use of these tailings would help preserve national wealth and also reduce the serious problems of environmental pollution caused by the tailings. At the optimal conditions of calcining at 750 - 800¦C for 45 minutes, the sample showed a mass loss of about 19 per cent. Mineralogical analyses showed that under these conditions the carbonate minerals including smithsonite (ZnCO3), calcite (CaCO3) and dolomite (Ca Mg (CO3)2) decomposed to their respective oxides. Hemimorphite (Zn4Si2O7 (OH)2.H2O) converted into willemite (Zn2SiO4) and this transformation postponed the formation of silica gel in the leach solution. The grade of zinc increased from 22.20 per cent to 29 per cent. These mineralogical changes resulted in desirable reactions in the acid leach process.

Jan 1, 2004

By Dudgeon RN, Houston ML

When the original Mount Gunson joint venture,between CSR Limited and United Uranium N.L. ceased operations in December 1971, an intensive exploration campaign was launched to prospect for more ore in the Mount Gunson region. This campaign resulted in the dis- covery'of the Cattle Grid copper deposit. A comprehensive sampling pro- gramme including the sinking of over 200 diamond drill holes and two vertical shafts,proved the existence of 4.6 million tonnes of ore, at a mean grade of 2.4% Cu,calculated at 1.00% Cu cutoff.

Jan 1, 1975

By B P. Voutharoj, R A. Dutch, M Paknezhad, T Ostersen

With the proliferation of new sensor technologies, acquiring multiple data sets over the same ground is becoming cheaper and easier than ever. This new, higher resolution multivariate data provides a significant resource for exploration and resource geologists but comes with the added complexity of effectively integrating the various data sets in useful and meaningful ways to elucidate new geological understanding. Both geophysical data sets and hyperspectral data are extensively used for exploration targeting, providing different information at different resolutions and crustal scales. One of the biggest challenges comes from trying to effectively integrate data sets that record very different physical properties, across the different scales these data are captured at, in a way which can allow for a data-driven analysis of these combined data sets.

Sep 1, 2024

By M Field

Kimberlite pipes, as opposed to dykes, sill and secondary deposits, are the primary target for diamond exploration companies because they have simple geometries and can contain large volumes of potentially diamond-bearing ore. Once discovered, important decisions have to be made regarding the sampling of these geological entities to establish the total volume of ore present, and to define the internal geology, which can be complex in nature and controls the distribution of diamond grade. It is essential that as part of this process the uncertainty in constructed geological models are assessed. In this paper the Orapa AK1 kimberlite pipe in Botswana is used as a case study to explore a potential methodology for defining this uncertainty. The uncertainty of the rock volumes of different types can be characterised by a geostatistical approach. Geostatistical simulations, based upon a plausible representation of the geological bodies, provide different possible images of the orebody that can be considered as different realities. By testing different borehole layouts and drilling the orebody virtually on the computer, many different, but equi-probable realisations of the pipes can be produced. It is then possible to estimate the rocksÆ volumes and compare them with the actual ones. A statistical analysis of the relationship between estimation error and the number of boreholes can then be used to optimise the next sampling campaign. The rock volumes are obtained from a two-step simulation process. Firstly, the pipe geometry is simulated by means of introducing variations around the geological block model, by an original method called centre point simulation (CPS), which has been developed for this purpose. Secondly, the internal geology is then simulated within the pipe. The methodology for simulating the internal geological zones has to be adapted to the level of information and to the geological structure itself. The upper portion at Orapa AK1 is filled with sedimentary crater facies. Here plurigaussian simulation techniques can be applied that are adapted to the simulation of sedimentary facies. The central zones of the pipe are typically subvertically-oriented massive volcaniclastic deposits and breccias and the lower regions comprise a complex root zone. CPS is appropriate for these zones.

Jan 1, 2006

By H F. Galbiatti, G J. I dos Santos, A de C Zapparoli

The Grao Para and Rio Maria greenstone banded iron formations (BIFs), within the Carajas mineral province, exhibit distinct lithological and petrographic fabrics, together with pronounced differences in their surface expression, real thickness, iron grade and tonnage. These geological differences support a new model for the regional distribution of iron formations in the Carajas Mineral Province.

Jan 1, 2009

By C Fricke, R Wood, P Velletri

"In a climate characterised by an ever increasing focus on cost reduction and maximising the utilisation of existing assets and infrastructure, understanding the uncertainty associated with alternative investment and operational choices becomes paramount to minimising the risk of making an ineffective decision. To assist in this process, TSG Consulting has developed an analytic framework to capture the underlying complexity of a mineral supply chain, and then quantify the impact of the uncertainty associated with the key drivers of business productivity. The technical basis of this approach follows three distinct steps: analyse the current system and identify the major factors that drive value build detailed models that can measure the response of the system to potential changes in the factors identified quantify the sensitivity of financial and capacity forecasts to these factors.Each of the above steps draws on a different area from the field of applied analytics, namely: data analytics dynamic modelling and designed experimentation meta-modelling and optimisation.Following the three-step approach described above ensures a rigorous modelling and analysis process is executed to support strategic mine planning decisions. The approach is equally applicable to the analysis of fully integrated system supply chains (pit-to-port), the evaluation of incremental capital investments to targeted areas of a supply chain, or when considering revisions to the operating philosophy of a system in the short term. The basis of each of the three analytic steps is explored in detail in this paper. The result is the definition of a structured mechanism for a business to actively manage risk and drive productivity as a component of the strategic mine planning process.CITATION:Fricke, C, Velletri, P and Wood, R, 2014. Enhancing risk management in strategic mine planning through uncertainty analysis, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 275–280 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By A Finch, C Pridmore

The Cosmo Project falls within the Archaean to Palaeo-Proterozoic Pine Creek Orogen, one of the major mineral provinces of Australia.The Cosmo Deposit is interpreted to be a series of steep north-west-plunging gold mineralised vein, breccia and shear systems within the tight Howley Anticline and hosted within interbedded siltstones, mudstones, banded iron, phyllites, dolerite sills and greywacke.A folded environment poses a number of technical challenges, particularly for estimation.Handling of tightly folded and in some cases narrow domains might include subdomaining for orientation, omni-directional three-dimensional (3D) estimation within constrained domains or software-enabled unfolding/un-wrinkling procedures (transformation of the data and estimate space into a two-dimensional environment). Each technique has its own unique set of advantages and disadvantages.A further method (one applied at Cosmo) is where the estimation parameters (specifically search and variography orientation) are modified in a frequent or ‘dynamic’ sense to suit the orientation of the domain whilst maintaining 3D space. Control of the resource estimation orientation can be done in several ways, including the use of sectional panels of a specific size or, alternatively, orientation sector divisions. The sector approach provides some significant reductions in processing time over the panel technique and could be applied in a number of software packages.Three-dimensional ‘dynamic’ interpolation reconciles well with production data from Cosmo, whilst the sector method provides a practical technique that can be executed without the complications of transformation or the need for labour-intensive orientation subdomaining and with acceptable resource estimation run time.CITATION:Finch, A and Pridmore, C, 2014. Dynamic interpolation – estimation in a folded environment at the Cosmo Deposit, Northern Territory, Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 107–114 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By B Laidens, D Souza, W Bielefeldt

The CaO-MgO-SiO2-Al2O3 system, characterised by its intricate phases and thermodynamic properties, plays a pivotal role in steel secondary refining processes, encompassing desulfurisation, non-metallic inclusion capture, and refractory protection. Accurate predictions for diverse industrial applications, including metallurgy, ceramics, and materials science, are imperative. To address this challenge, a combination of machine learning techniques will be specifically applied to model the liquid fraction of the slag and the solid fraction of MgO. The development of an artificial intelligence (AI) system, leveraging various machine learning techniques, has gained momentum in this project. The focus of this work is on constructing an AI model, based on machine learning techniques, within the CaO-MgO-SiO2-Al2O3 system, utilising simulation results from FactSage™, version 8.1 (by GTT Technologies). The primary objective is to train the AI model using these simulation outputs to predict the percentage of liquid fraction and MgO saturation based on chemical composition parameters. The AI model will undergo training with a comprehensive data set of simulations within the CaOMgO- SiO2-Al2O3 system, covering a diverse range of compositional at 1873 K. These simulations, conducted through FactSage™ 8.1 software, provide a robust foundation for AI model training, ensuring generalisability and precise predictions for the liquid fraction of the slag and the solid fraction of MgO, the solid fraction of MgO in this case is determined by the difference between the total MgO and the MgO in the liquid fraction, so it is not the objective of this study to determine which phase of MgO is in the solid state.. The predictive capabilities of this AI model hold significant implications for process optimisation, quality control, and decision-making in CaO-MgO-SiO2-Al2O3- dependent industries. Precise estimations of the liquid fraction and MgO saturation empower researchers and engineers to enhance operational efficiency and quality. This paper explores the methodologies employed for AI model creation and training, achieved results in terms of prediction accuracy, and potential applications in the field. The development of this AI system signifies a notable advancement in utilising machine learning for better comprehension and control of complex chemical systems. Furthermore, to align the study with real-world steel production, we introduce FeO and MnO at concentrations of 2 per cent and 1 per cent at 1873 K, respectively, following the validation of model results using the CaO-MgO-SiO2-Al2O3 system. This adjustment aims to bring the study closer to the observed reality in steel mills globally.

Jun 19, 2024

By Smit J. G

Following an increase in the number of methane ignitions in South African coal mines a new ventilation system was developed. The "Hydravert" system conceived in late 1979 for use in low seam coal mines, where the bord and pillar method of working is used, has been extensively developed to include applications for mining seams up to 4.5 metres high. A brief history of the development is supplied including some of the pitfalls encountered in the hydraulic equipment design and selection.

Jan 1, 1988

By Willett, Jacka

Group 3 were asked to discuss the treatment of spontaneous combustion. Before discussing specific cases we agreed that certain preliminary information should be available. The following questions are typical of the information which might be requested: 1. Have workmen been withdrawn? 2. Have gas samples been taken? 3. Is the mine gassy? 4. What are the details of water supply? 5. Are mine plans available? 6. What equipment is available? We discussed treatment in four different circumstances as follows: 1.

Jan 1, 1973

By A Murphy, I Samsonova, N Eastwood, D Whittle

Part XI of the United Nations Convention on the Law of the Sea (UNCLOS or the Convention) (United Nations (UN) Division for Ocean Affairs and the Law of the Sea, 1982) establishes a comprehensive regulatory framework for the conduct of deep seabed mining (DSM) activities of mineral resources in the Area (defined in Article 1(1) of UNCLOS as ‘the seabed and ocean floor and subsoil thereof, beyond the limits of national jurisdiction’). Under that framework, DSM activities can only take place in the Area pursuant to an approved Plan of Work in the form of a contract with the International Seabed Authority (ISA) (the Authority), a 168-member international body created under UNCLOS to administer the Area. Private contractors can undertake DSM activities if they are sponsored by Member States of UNCLOS, providing a dual system of international and domestic regulatory control and oversight for activities in the Area.

Sep 1, 2024

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.Recent increases in prices for iron ore, together with the potential to produce high iron and low contaminant concentrates, have resulted in a renewed interest in recovering magnetite from banded iron formation and other deposits.Geometallurgical evaluation of magnetite involves approaches to sample preparation, sample analysis and resource estimation that are different from the methods commonly used for haematite iron ore. The magnetite sampling protocol is specific to each deposit, and is typically designed around a specific metallurgical flow sheet.The sampling protocol will typically include the use of Davis Tube analysis. The Davis Tube is a bench-scale test 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.During resource modelling, the mass magnetic recoveries and concentrate grades may be assigned to a block model using regressions with other chemical constituents, or may be estimated directly. For estimation of the concentrate grades, a weighting can be applied to account for the different mass magnetic recoveries from each sample and the impact of these differences on the concentrate estimates.This paper presents an overview of the use of metallurgical test data in resource evaluation for magnetite deposits.

Jul 11, 2011