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Exploration for uranium in Australia commenced only during the 1940s, but in this short period has been very successful as one third of the world's low cost uranium reserves have been discovered in Australia. Total uranium exploration expenditure in Australia up to the end of 1983 was $A(1983) 554 million; this discovered 20 potentially economic deposits and official reserves of 560 000 tonnes of uranium oxide at an average cost of $1 per kg of U 0 . An exponential 8 eserves indicates distribution of uranium r that there could be 54 undiscovered uranium deposits in Australia, each with reserves of 20 000 tonnes U308 or more, in addition to smaller deposits. Using a constant uranium price of $A(1983) 79 per kg, no deposit is economic at a grade below 0.12 per cent U 08 or with reserves of less than 3 000 tonnes. Selecting deposits with reserves of 5 000 tonnes U 0g or more as prime exploration targets, only 39 per cent of discoveries will yield a real internal rate of return (IRR) of 10 per cent or more. After committing a minimum exploration budget of $10 million to this search, an explorer has one chance between 7 and 12 of discovering a deposit that will repay the exploration investment.

Jan 1, 1984

The demand for gallium has increased significantly over the last few decades due to the expanding use of Ga compounds in the electronics industry. Because it is widely dispersed and rarely found naturally in concentrations greater than 0.1%, Ga is expensive (approximately US$500/kg) and difficult to produce in large quantities.   A previous study of metals in geothermal systems reported significant quantities of Ga present in the muds on the northeast margin of Lake Rotokawa, an acidic lake associated with a high-temperature geothermal field situated in the Taupo Volcanic Zone of New Zealand. Similar muds are present in many other geothermal fields in the zone, suggesting that geothermal muds could be a commercial source ofGa.

Jan 1, 1994

By M O. Tade, M W. Sze

The particle dynamics of a mixture of coal and zircon system wasstudied in a scaled-down cold model of an industrial kiln. Thefactors investigated in the study were rotational speed (N),zircon-to-coal feed ratio (B), coal particle size (dpc) and the angle of inclination (*) of the kiln. The technique used is the residence time distribution (RTD) method. It was found that rotational speed and angle of inclination are important parameters that affect the residence time of particles in the kiln. A mathematical model for predicting the mean residence time of particles in the rotary kiln was developed. Comparisons with reported models for such systems are discussed.

Jan 1, 1998

By X Ma

Kaolinite is of very fine particle size in nature and thus its dispersion plays a key role in the successful removal of kaolinite in iron ore flotation and selective flocculation processes. As the most widely used dispersant in the world, sodium silicate has been used as a standard dispersant for kaolinite in the iron ore industry. However, the actual effect of sodium silicate on the colloid stability of kaolinite particles and its dispersion mechanism remain unknown in the literature. In this work, the dispersion effect and dispersion mechanisms of some common inorganic and organic dispersants, including sodium silicate, polyphosphate and a low molecular weight polyacrylic acid, on kaolinite particles were systematically investigated through electrophoretic mobility and colloidal stability studies over a wide pH range. It was found that sodium silicate-kaolinite interactions only take place in the neutral and acidic pH range, while polyacrylic acid and polyphosphate interact with kaolinite from pH 3 to 10.5. Consequently, sodium silicate only disperses kaolinite at neutral and acidic pH. In contrast, polyacrylic acid and polyphosphate disperse kaolinite from pH 3 to 10.5, with strong dispersion effect observed at neutral and acidic pH. In the iron ore industry, selective fl occulation and reverse cationic fl otation, the most widely used flotation route, are both conducted at pH 10 to 10.5. The results of the present study show that, at such high pH, polyacrylic acid and polyphosphate are more effective dispersants of kaolinite, in comparison with sodium silicate.

Jul 11, 2011

There are many compelling reasons why correct sampling schemes should be standard practice in the mining industry, yet there are numerous examples where poor sampling practices are known to exist in the business yet permitted to continue. It is not just technical issues that can be ascribed to the reasons for the continued use of incorrect methods. This paper proposes non-technical reasons why incorrect sampling practices continue, and identifies potential ways to overcome them.

Mar 1, 2010

By H Wen

LongWangGou coalmine auxiliary inclined shaft heading face has a large section, fast heading speed, and large dust production. The problems of high concentration and wide distribution of dust in the roadway air are very prominent. To improve the efficiency of roadway ventilation and dustremoval, long-compression and short-suction (after this referred to as LCSS) are adopted. The dust concentration and airflow field distribution in the roadway are numerically simulated by FLUENT. The change of the position between the pressure duct and the exhaust duct and the different pressure-extraction ratios affect the distribution of airflow velocity, the formation of vortex zone, and the distribution of dust concentration in the roadway. When Ly = 25 m, Lc = 5.0 m, W = 1.2, a wind curtain is formed at 5 m in front of the heading face to prevent dust from spreading deeper into the roadway.

Oct 12, 2022

By J Taylor, M Smith, A Tunnadine, D Nikolakopoulos

As Olympic Dam rapidly expands into the Southern Mine Area (SMA) the Mine Geology team has concurrently ramped up underground diamond drilling to sustain rates of above 175 km/a. With >10 underground rigs double-shifting, traditional paper sections used for the management of drill programs were no longer optimal due to scale of operations. An opportunity was identified to modernise monitoring of all underground diamond drill programs, through the integration of logged copper sulfide estimates with Olympic Dam’s first-fully integrated deposit-scale geological model in Leapfrog Geo. This paper describes the transition within the Mine Geology team from reliance on 2D paper sections, towards near-real time 3D geological modelling for optimising end-of-hole decisions in the field. This transition was enabled by innovative database solutions informing locally constrained implicit models, limited by a distance buffer around active underground fan drilling. Due to the high volume of historic drilling, there were significant computational challenges with the implementation of daily production style implicit models at Olympic Dam and initial testing of regular updates to implicit gradeshells and sulfide domains required in excess of 12 hrs to run. The enabling solution was to optimise the interfaces between the AcQuire database, Deswik MDM and Leapfrog Geo to create a dynamic, streamlined workflow that was easily completed by Mine Geologists in accordance with daily production duties. Geologists are now building rapid implicit models for a range of variables from an integrated data set of logged sulfide estimates and existing assays, spatially constrained by 150 m buffers around active drilling using a unique drill fan identifier flagged during the planning phase. Once the live-implicit models are updated, they are exported for visualisation on field tablets to be used during logging and core checks at the start and end of every shift. To manage the risk of ‘going digital’ interpretation remains at the forefront of the drill section close-out process, with Mine Geologists critically reviewing the finished sections on a standardised template with new learnings wireframed and communicated to stakeholders. The Live Field Model has enabled a step-change in the geological effectiveness of diamond drilling, reducing over – and under-drilling ore-waste at Olympic Dam continuing to push drilling effectiveness towards 20 per cent of intercepts >2 per cent Cu. In addition, upside or risk identified during the proactive management of drilling execution can be rapidly capitalised or mitigated.

Mar 22, 2022

By E N. Isaev, L E. Levin

New data on the geology of the Late Jurassic to Holocene sediments cover of the World and associated mineral resources (oil, gas, ferromanganese nodules, ores of massive sulphides and other metals) have been compilled in the Atlas at scale 1:25,000,000 and 1:10,000,000. The work was performed by scientists from four Institutes of Russia (VNIIzarubezhgeologia, VNIIoceangeologia, Vernadsky Institute of Geochemistry and Analytical Chemistry of theRussian Academy of Sciences and Geological Institute of the Russian Academy of Sciences). The Atlas shows variation of thickness and formational composition of the large complexes (Upper Jurassic-Early Cretaceous, Upper Cretaceous Eocene, Oligocene-Neogene, Pliocene-Pleistocene), distribution of oil/gas and ore deposits in each complex, data of deepsea drilling (leg 1-130),  thermo-pressure condition in the sedimentary basins within Circum-Pacific Rim.

Jan 1, 1995

By C Fischer

The introduction of digital communications technologies into the underground mining industry, in both coal and hard rock mining, has enabled high bandwidth applications to be applied in the mining industry. Digital networks based on 802.11 b/g/n open Wi-Fi standards have allowed numerous applications to be run over a single communication backbone. One of the many important applications is the tracking of personnel and equipment via RFID Tags. This tracking application has formed the basis of a Proximity Detection System or Collision Avoidance System (Schiffbauer and Mowrey, 2001; Kent, Fischer and Schiffbauer, 2011) thereby improving safety and increasing control in the mining environment. This paper discusses the growth of digital technology as the backbone for communications in underground mining applications. This growth has allowed the ‘convergence of technologies’ (occurring in the general business world) to be available to mine operators in general and underground mine operators in particular. Mine Site Technologies’ involvement with major mining companies and mining equipment manufacturers (OEMs) in developing and supplying their communication systems is also discussed.The latest technical requirements and specifications for communication systems for underground and open cut mines will be reviewed.

Nov 22, 2011

By M J. Newton

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

Sep 5, 2011

The mining licence for the Macraes gold mine places emphasis on the progressive rehabilitation of the land to a state compatible with the landscape and environment that existed prior to mining activities taking place. The shallow soils and hostility of the environment dictate that choices of plant species should focus on persistence rather than high productivity, choices that are made easier by observing the vegetation patterns that have developed naturally within the area, by recontouring landforms to integrate with the surrounding countryside and the use of appropriate plants and establishment techniques.

Jan 1, 1992

By H S. Pescini

A material aim when feeding ore blends into a processing facility is to reduce the variability of the properties of the feed material and to maximise the output, or throughput. At the Mining Geology conference of 2019, we presented a paper on optimal blending of coking coal given geological variability. The paper introduced integer-programming techniques to both maximise value and minimise feed or product variability. We discussed an application where the geological uncertainty is characterised using a normal distribution and exact solutions are readily obtainable using second order conic constraints in the mathematical model. Geological uncertainty is not always normally distributed, many properties will be characterised as log normal or some other skewed distribution. For example, copper can be some form of lognormal and Fe in Iron ore has a left skewed distribution. In this paper, we discuss some distribution free techniques to optimise the blends of plant feed or output given a quantified geological uncertainty. We discuss the sample average approximation method and how to set-up and apply the method to an ore blending problem. Evaluating a case study demonstrates that the explicit use of non-normally distributed geological uncertainty can better optimise feed into an ore processing facility and potentially add significant value. The approach is equally applicable to all mining and processing operations that blend material into a processing facility or directly into a saleable product.

Mar 22, 2022

By R Cannings, J Wallace, M McCamley

The mining industry continues to have major disasters (Bingham Canyon, Pike River, Upper Big Branch, Mount Polley and Samarco), which often have a devastating effect on the enterprise, in terms of personnel deaths and injuries, environmental destruction, and financial and reputational loss. These disasters are not imposed from outside the business or organisation, they are almost always a function of loss of control of the management of the organisation’s critical assets and processes that they contain or to which they are exposed.Asset integrity is discussed as an effective response to business risks in order to mitigate, control and recover from loss scenarios that could expose a mining operation to significant property damage and business interruption, or even total loss. Vital to this process is the identification and control of risks to critical assets. Components of a critical asset assurance program are presented for discussion.Formal risk assessment has a longer history in industries other than mining, eg petrochemical, nuclear, military, aviation and space industries. Risk assessment is a structured, proactive approach to understanding and improving risks, as opposed to a reactive ‘fix-it-when-it-breaks’ mentality. Risk assessment techniques were triggered by major public disasters, such as the Flixborough chemical plant disaster (1973), Three Mile Island nuclear plant event (1979) and others.Today, most industries see risk assessment as an inherent part of their business, but do mining sites capture business risks that are related to major loss scenarios, which could have a significant impact on the operation?Does your risk assessment process:- involve a team having the right skill set so that the discussion is both stimulated and technically sound?- use generic assessment when a site-specific assessment is needed?- fail to consider all possible outcomes, including maximum foreseeable loss (MFL)?- fail to identify all hazards and controls associated with a particular activity?- fail to monitor controls effectively?This paper addresses the issues identified by these questions and provides some direction for developing a risk management process where business risk associated with critical asset integrity is integrated with other business and safety and health risk processes to provide a robust method for managing your business. Case studies and common findings from critical asset failures are used to support the need to include critical asset assessments as part of business risk management processes.CITATION:Wallace, J, McCamley, M and Cannings, R, 2016. How robust are your asset integrity management processes? In Proceedings International Mine Management Conference, pp 53-64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jun 22, 2016

A model has been developed for drum scrubbing which allows selection of geometry and power input. Specific aspects considered are: Calculation of total static and operating volumes. Total residence time based on total operating volume. Solids residence time based on solids operating volume. Selection of the aspect ratio. Alteration of operating fill to allow for smaller or larger feed openings. Selection of proportion of critical speed. Calculation of shell and motor power requirements. The model uses either solids or total residence time to calculate the required operating volume. The solids residence time is based on the proportion of coarse solids in the feed. Material finer than the reject size is considered as part of the slurry. The solids operating volume is the static volume plus the surcharge on the discharge weir required for flow of the solids from the unit. The total operating volume is the static volume plus the surcharge on the discharge weir for the total flow to exit the scrubber. The burden density is calculated from the coarse solids bulk density and the slurry density that includes all the fine solids. Power is calculated using the Liddell and Moys correlations for burden position and shape, and the operating rotational speed. Results from the model (especially power) have been verified from industrial installations of significant size. Predicted and observed power draws are within two per cent. A check against the JKMRC mill model shows power draw prediction agreement to within four per cent.

Jan 1, 2004

By R Garzon

For resources projects with healthy net present value (NPV) and low cash flow volatility, conventional discounted cash flow (DCF) analysis will continue to provide the dominant investment decision-making criteria. However, DCF analysis can be biased because it often applies a single risk-adjusted discount rate (RADR) to compare the value of projects with different risk characteristics. Many of the difficulties with DCF modelling arise from analystsÆ inability to determine appropriate risk discounts and to estimate expected spot prices inputs for the commodities produced over the life of the project. Modern asset pricing (MAP) is a very valuable complement to DCF analysis in addressing some of these issues. Most papers dealing with MAP, however, while academically rigorous, tend not to be explicit in terms of practical application of this methodology in routine project evaluation. This paper has the objective of reviewing the MAP methodology and of demystifying its complexity, by providing a simple but realistic step-by-step evaluation of a mining project, comparing its DCF and MAP NPV values. The paper concludes that MAP provides a minimum, risk-adjusted æfloorÆ value, thus representing a valuable complement to any DCF valuation.

Jan 1, 2007

Removal of Thiocyanate from Solutions by Precipitation

Sep 13, 2010

By A Self, B Robertson

During 2015 and 2016, the authors conducted a number of surveys, workshops and reviews of ventilation and gas management practices in Australian underground coalmines. The study was funded by ACARP with a brief to identify gaps in ventilation and gas management practices for current and future needs, and to prepare a road map for change that would assist in delivering improvements.The study found that despite many examples of leading practice, gas and ventilation management is not afforded the attention and priority that is warranted and that this must be remedied if future operational performance targets are to be achieved and the safety of the industry protected. This paper summarises the findings of the study and presents the recommendations proposed.CITATION:Robertson, B and Self, A, 2017. A review of ventilation and gas management in underground mines, in Proceedings Australian Mine Vent Conference 2017, pp 277–284 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 28, 2017

By Y Xie, D Willingham

Predictive maintenance (also known as ‘condition/health monitoring’) refers to the intelligent monitoring of equipment to avoid future failures. In contrast to conventional preventive maintenance, the maintenance schedule is not determined by a prescribed timeline; instead, it is determined by analytic algorithms, such as machine learning, using data collected from equipment sensors and/or via simulation.Predictive maintenance offers the following benefits for operators and equipment manufacturers:- reduces equipment downtime by identifying issues before failure, thereby enabling convenient scheduling of equipment service and extending equipment lifetime- determines the root cause of the failure, enabling appropriate service to be performed without utilising resources to determine a diagnosis- avoids the unnecessary costs of maintenance and unexpected failures- improves safety and product quality.Algorithms and data are critical to predictive maintenance success. Sensor data is first preprocessed using advanced statistical and signal processing techniques; it is then combined with predictive modelling techniques, such as machine learning, to estimate equipment health.Once tested, predictive maintenance algorithms may be used in an operational setting within an IT environment, such as a server or cloud. Alternatively, algorithms may be implemented in an embedded system directly on the equipment, allowing for faster response times and significantly reducing the amount of data sent over the network.CITATION:Willingham, D and Xie, Y, 2017. Predictive maintenance modelling for bearing-based equipment, in Proceedings Iron Ore 2017, pp 627–630 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

By M Rayner, C Tsouris, A Komelkov

X-ray fluorescence (XRF) is a widely accepted technique for the elemental analysis of iron ores and their concentrates. Wavelength-dispersive, or WDXRF, and energy-dispersive, or EDXRF, spectrometers offer distinct advantages for particular applications, elements and concentration ranges and are, therefore, more complimentary than people might realise. A key example is the ability of EDXRF to identify, and often quantify, unexpected elements in production samples that would typically be missed by routine WDXRF. In this paper we discuss recent technological advances in XRF and present a novel application example that demonstrates the additional technical and practical benefits of using both EDXRF and WDXRF to characterise iron ores and concentrates.CITATION:Tsouris, C, Komelkov, A and Rayner, M, 2015. A novel approach to the characterisation of iron ores and concentrates using recent advancements in wavelength- and energy-dispersive x-ray fluorescence spectrometers, in Proceedings Iron Ore 2015, pp 591–594 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By M K. Nahian, R G. Reddy

The thermodynamic model for species distribution in aluminium chloride (AlCl3) and 1-butyl-3- methylimidazolium chloride (BMIC) system was developed. The experimental thermodynamic data, considering a range of aluminium chloride species, such as AlCl4-, Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6 were used in developing the model. When the XAlCl3 was in the range of 0 to 0.50, only anion species Cl- and AlCl4- were existing in the solution. As the XAlCl3 value increased more than 0.50, the available anions were Al2Cl7-, Al3Cl10-, Al4Cl13-, and Al2Cl6. Specifically, the concentration of Al2Cl7- increased in the composition range from 0.50 to 0.67 XAlCl3, after which it decreased. This change in the concentration of Al2Cl7- was due to its reaction with excess AlCl3, leading to the formation of Al3Cl10-. The average cathode current density was determined by the electrochemical experiments varying XAlCl3 from 0.50 to 0.71 in the AlCl3:BMIC solutions. The average cathode current density increased as the XAlCl3 increased from 0.50 to 0.67. However, it decreased when the XAlCl3 > 0.67. This trend can be attributed to the electroactive species Al2Cl7-. The Al2Cl7- promotes the reduction rate at the cathode, resulting in an increase in the average cathode current density.

Aug 21, 2024