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By S Russell

The completion of the $1.1 B Cape Lambert Upgrade project is the second ‘pillar’ in Rio Tinto Iron Ore’s expansion program that has enabled Rio Tinto Iron Ore to effectively double iron ore shipping capacity from the Pilbara between 2003 and 2009 to 220 million tonnes per annum (Mt/a), following the successful completion of the Dampier Port upgrade project two years earlier.The Cape Lambert Upgrade has built on and enhanced many of the engineering achievements of the Dampier Port upgrade project, as well as developing innovative and unique engineering solutions for this complex ‘brownfields’ project that presented its own challenges, particularly in this distinctive open-water port environment.The project was implemented in two phases to achieve an increase in port shipping capacity from 55 to 80 Mt/a – an enhancement phase and an expansion phase.The initial enhancement phase, which provided an increase to shipping capacity from 55 to 60 Mt/a, focused on increasing the utilisation and effi ciency of existing plant and equipment with a relatively small capital expenditure.The expansion phase, which provided the increase in shipping capacity to 80 Mt/a, included extending the existing iron ore wharf by 256 m to create four shipping berths, a new shiploader, an expanded stockyard (including a new fourth bucket wheel reclaimer) and a new surge bin facility to maximise outloading tonnage rates.The Cape Lambert Upgrade project was implemented whilst the port remained fully operational and continued to ship record tonnages of iron ore throughout the project duration. This achievement required signifi cant upfront planning and sequencing of construction activities to support the operation of the port. Innovative design and construction techniques were used to mitigate the impact and enable construction activities in and around the operating plant.Throughout the project, new benchmarks in engineering design and construction practices were established, which have since been adopted for new iron ore port facilities currently in planning phases.

Jul 11, 2011

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 D A. Bowman, S Schafrik

With the goal of reducing injuries and fatalities related to haul truck accidents, this research investigates technologies and intervention strategies for improving worker training using a virtual environment (VE). Funded by the National Institute for Occupational Safety and Health (NIOSH), this research specifically focuses on training workers in preshift inspections of haul trucks to avoid preventable defects from causing worker injuries and expensive equipment damage. Improved training in these inspections is expected to increase uptime. The VE developed to train workers for preshift inspections consists of three phases: the virtual tour, the virtual inspection and the shift simulation. The virtual tour introduces information necessary to conduct a preshift inspection by guiding the worker around a haul truck, identifying parts to be inspected and explaining defects to look for. The virtual inspection assesses retention as the worker navigates around a haul truck and identifies defects. During the shift simulation, the worker is shown a simulation of the work shift, which animates severe consequences of any overlooked defects to emphasise the importance of preshift inspections. To provide multiple training platforms, desktop and CAVEÖ versions of the training VE were created. Flux Studio was used to model the environment and to produce Virtual Reality Modelling Language (VRML) files for the desktop version. DIVERSE, an application programming interface, was then used to implement a more realistic version of the VE in a CAVEÖ, a room-sized visualisation system. Initial feedback from mining colleagues indicates that the training VE may replace normal classroom training for preshift inspections in the future. As opposed to PowerPoint presentations and instructional videos, the training VE provides better spatial understanding of the location of parts and incorporates interactive features to actively engage drivers in the learning process, which may result in better retention. Initial feedback also indicates that minor improvements can be made to the virtual tour and virtual inspection phases.

Jan 1, 2008

By E Nettleton, A Melkumyan

Identification of geology and mineralogy in situ on the mine face is essential if mining processes are to be automated for tasks such as exploration, grading and reconciliation. Hyperspectral data acquired from field based platforms are ideally suited to these tasks, and are set to revolutionise the automated mining industry. Changing conditions of solar illumination introduces variation into the hyperspectral signal, which is unrelated to geology, complicating analysis of data. Thus, algorithms must be able to deal with changing illumination conditions and operate in a consistent and probabilistic framework, which is a prerequisite for data fusion with other sensors. To produce accurate classification maps of geology, algorithms must be developed that are effective under different conditions of illumination.The efficacy of three algorithms to classify hyperspectral data for geology mapping on vertical mine faces was assessed. These algorithms are the spectral angle mapper (SAM), and two machine learning methods operating within a fully probabilistic Gaussian process (GP) framework û the squared exponential (SE) and the observation angle dependent (OAD) covariance functions (kernel). Two experiments were done to assess the classification performances. The first determined the performance of the algorithms by classifying hyperspectral data of known rock samples acquired using a field spectrometer. The GP-based methods had a similar performance, with average accuracies and F-scores of 97 and 88 per cent (GP-OAD) and 95 and 81 per cent (GP-SE), respectively. Average accuracies and F-scores for SAM were significantly smaller (80 and 40 per cent respectively). The algorithms were then applied to hyperspectral imagery acquired from a vertical mine face at different times of the day, under very different conditions of illumination. In contrast with experiment 1, SAM and GP-OAD gave results which were superior to GP-SE and were entirely consistent with geology mapped in the field. Compared with SAM, GP-OAD was less sensitive to the effects of shadow and produced classified images that were less noisy. The GP-SE method failed to delineate even gross changes in geology on the mine face. These results show conclusively that in order to use independent training data (spectral library) to classify imagery acquired under a different set of conditions, algorithms must take into account variability in incident illumination. Measures based on spectral distance are inferior to those based on spectral angle.The OAD kernel within the GP framework (GP-OAD) is superior to the other two methods because:it provides a probabilistic framework;it is insensitive to variability in illumination within and between imagery acquired under different conditions; andit can identify and map geological zones on a vertical mine face using an independent spectral library, without a priori knowledge.

Sep 26, 2011

By E Rubio, N Morales

Currently, mine plans are optimised by using several criteria as objective functions, like profit, life-of-mine, concentration of some pollutants, mining costs, confidence level or ore resources, with consideration of constraints related to production rates, plant capacities and grades. Whilst this approach is successful in terms of producing high value production schedules, it uses a static opening sequence of the drawpoints and therefore the optimisation is made within the level of freedom left by the original opening schedule, and as a result it is far from the true optimal value of the project. This paper presents a model to optimise the sequence of drawpoint opening over a given time horizon. The emphasis is in the precedence constraints that are required to produce meaningful operational sequences considering the exploitation method (panel or block caving), physics considerations and logical rules. Further on, while it applies the standard approach of maximising net present value (NPV), it considers other targets for optimisation, like the robustness and constructability of the plans. Finally, it applies the model to real data to obtain feasible plans by means of this model. The first tests were done varying the production capacity of the mine.

Sep 26, 2011

By E M. Wightman, C L. Evans

A recent survey of mineral processors undertaken as part of the International Mineral Processing Council (IMPC) Education Commission identified mineralogy as one of the key skills required for mineral processors (the other key areas being comminution, flotation, physical separation, sampling and extractive metallurgy). Past experience in a number of operations has shown what can be achieved when the data outputs from mineralogical tools are coupled with people with the right skills who can transform the data into actionable information. This paper reviews what has been done successfully in plant operations over a period of more than four decades and gives examples of a range of applications with both long and short-term objectives. The examples demonstrate the usefulness of mineralogical data – both basic and complex – in optimising mineral processing operations, whether the data are applied in a simple analysis or in more complex modelling. Similarly, the examples show the range of options available for operations to access the mineralogy information they need – through in-house experts and equipment based in centralised technology centres, through on-site equipment and experts or through external laboratories and consultants.The examples from industry highlight the huge potential benefit of including mineralogy as an integral part of operational best practice and raise the question of why more operations do not utilise what should be readily available data. Successful application of mineralogical data requires skilled people to generate relevant data of the required quality, together with skilled people to interpret the data (this may be the same person). And, as in any project, corporate recognition of the value of this approach to best practice is required to ensure continuing support. With fewer university courses providing courses in process mineralogy to undergraduate mineral processing engineers and chemical engineers, there is an increasing lack of knowledge about what mineralogical information is needed, how to get the required data and, equally importantly, how to turn the data into useful information.CITATION:Evans, C L and Wightman, E M, 2018. Understanding minerals in mineral processing – the basics and beyond, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 363–376 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

By D Rattray, D Macfarlane, I Robb, N Halpin, G T. Dale

Mining faces many environmental, social and regulatory liabilities of which water management is just one. Others include site rehabilitation, carbon emissions, biodiversity offsets, strategic cropping land, subsidence, and noise and dust generation. Management of these liabilities is commonly seen as a cost of doing business and each is often independently addressed, bypassing the opportunity to reduce costs through integrated approaches. Furthermore, approaches to dealing with these liabilities tend to be constrained by a prevailing culture of engineered solutions and lack of appreciation of risk associated with alternative and hybrid alternative-engineered solutions. Suboptimal outcomes can also be reinforced by rigid regulatory constraints. While the cost of addressing operational liabilities may be a small proportion of overall mine management costs, failure to do so effectively may influence social licence to operate and, as recently demonstrated by the decision of the NSW Land and Environment Court to block expansion of the Warkworth Mine near Singleton, absolute licence to operate.Integration of environmental, social and regulatory liabilities with value-creating and risk-reduction opportunities such as beneficial water use, carbon bio-sequestration, habitat connectivity, keyline farming, improved grazing design and management systems, windbreaks and visual screens, presents opportunities to reduce risk and create value. This potential may achieve overall improved outcomes in both economic and non-economic mine performance criteria.Two case studies in beneficial use of waste water from the mining and coal seam gas (CSG) sectors (which operate under different legislation) will be used to illustrate the potential to address mine development, operational and closure liabilities by understanding opportunities to reduce risk and create value through a holistic water management framework. The technical requirements and alternative approaches to beneficial use of mine water are addressed, along with the direct economic benefits for mine operational costs and opportunities to positively engage communities and build resilience into social licence to operate. Regulatory barriers to achieving improved outcomes will be discussed.CITATION:Dale, G T, Robb, I, Halpin, N, Macfarlane, D and Rattray, D, 2013. Opportunities for integrated mine management to minimise risk and create value, in Proceedings Water in Mining 2013 , pp 227-234 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 26, 2013

By J Pearce, M Barteaux, S Pearce

The prediction of how waste materials will evolve geochemically within waste storage facilities has been the subject of hundreds of thousands of hours researched by geoscientists globally. Despite the quantity of research there are a number of significant areas of uncertainty that remain as partially resolved issues. One of the most significant issues is the applicability of scaling laboratory test results to field conditions, and the use of laboratory data for predictive calculations to determine geochemical evolution of waste materials in the field. This issue has arisen predominantly as a result of the relative paucity of field monitoring data from waste rock storage facilities (WRSFs) and the fact that laboratory test methods are not typically linked to specific field conditions; rather they are based on generic standardised methods and designed primarily to simulate accelerated weathering conditions that do not relate to field conditions in a linear manner.To address these specific issues the authors have in the last two years made significant progress in the development and deployment of advanced field monitoring equipment within numerous WRSFs. O’Kane Consultants (OKC) has previously reported the findings from data collected from these monitoring installations in a number of papers presented throughout 2013–2014. This valuable site data has subsequently been used by OKC as the basis to design and engineer advanced customisable site-specific kinetic leach columns at OKC’s geochemistry research laboratory. These columns represent an important advancement in kinetic column assessment methodology as they have been designed to replicate the field internal conditions within waste facilities.Key features of the columns include their capacity, size and technical specifications; including fully programmable solenoid-controlled air supply with variable flow and pressure control and in-line heating option, automated temperature control and monitoring, automated oxygen consumption and carbon dioxide production monitoring, and soil moisture/matric suction monitoring.This flexibility of the design not only allows for more accurate field-based assessment of pyrite oxidation rates (POR) but also assessment of the potential effectiveness of waste management options such as deposition within a reduced oxygen environment, for example, as simulations of reduced net percolation rates or oxygen ingress rates can be accommodated.CITATION:Pearce, S, Pearce, J and Barteaux, M, 2015. Advanced customisable leach columns – a new kinetic testing method to simulate site-specific conditions, in Proceedings Tailings and Mine Waste Management for the 21st Century , pp 137–144 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 27, 2015

By J E. Everett

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

Sep 5, 2011

By G M. Jeffress, D C. Arne

There are two discrete aspects to collecting portable X-ray fluorescence (pXRF) data to obtain reliable results and to comply with reporting requirements under the 2012 edition of the JORC Code (JORC, 2012) – sampling method and quality assurance. A robust sampling program is required to obtain representative material for analysis. The appropriate method should be established for a particular project using a small orientation study. A variety of approaches to sampling soils, drill cuttings, rock faces and diamond drill core are discussed. These include using multiple spot analyses, scanning using a single operating beam and the collection of cutting saw pulps. The operator must also be aware of the attenuating effects of analysing through sample bags of different material types for various elements as well as the limitations of current pXRF instruments in reporting reliable data for certain elements. The analysis of the samples must also be accompanied by a quality assurance program in order to generate data that are ‘fit for purpose’. This includes recording X-ray tube resolution on a routine basis, using matrix-appropriate standards for which total elemental concentrations are available, using silica blanks, capturing sufficient duplicate analyses to constrain data precision and obtaining check assays to calibrate pXRF data against laboratory data. Examples of quality control approaches and data are presented. Table 1 of the 2012 JORC Code also recommends that information on instrument make and model, reading times and calibration be provided in any reporting of pXRF data. To this should be added information on operating mode and temperature, software version and moisture content of the samples. A robust sampling methodology with a suitable quality assurance/quality control program should produce pXRF data of sufficient quality for public reporting purposes, provided that the data are presented using appropriate cautionary language and adequate supporting information.CITATION:Arne, D C and Jeffress, G M, 2014. Sampling and analysis for public reporting of portable x-ray fluorescence data under the 2012 edition of the JORC Code, in Proceedings Sampling 2014 , pp 57–64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By R Miller

The enrichment of magnetite to haematite and haematite-goethite leads to a coincident magnetic low and gravity high within the banded iron formation. Palaeochannel deposits of pisolitic limonite can be expected to provide a relative magnetic high and gravity low in a sinuous geometry. Detrital iron deposits of conglomerate, scree or ‘canga’ might have indistinct magnetic response but will usually have a relative gravity high.These signatures provide clear discriminators detectable by a joint gravity and magnetic survey.The combination of airborne gravity gradiometry and magnetometry is particularly powerful in detecting and discriminating targets, as well as mapping lithologies and structure, across a wide variety of iron ore deposit styles. It provides detection capabilities in a platform capable of rapid, complete coverage with minimal access issues. This approach has been used in FALCON™ airborne surveys for iron ore exploration in the Great Lakes, USA; the Middleback Ranges, South Australia; and the Hamersley Basin, Western Australia.The complex magnetic properties of iron formations (particularly remanence, anisotropy and depth of weathering) prevent this approach from being simple. The use of vector residual magnetic intensity (VRMI), calculated from the measured total magnetic intensity (TMI), assists by reducing the complexity due to the different directions of the remanent and induced magnetic fields.Estimations of the density to magnetisation ratio via the pseudo-lithology calculated from the VRMI and gravity gradients provide a useful method of capturing the discriminatory power of joint magnetic and gravity gradient data.

Jul 11, 2011

By S J. Clarke, C S. Walker

The South West Rail Link (SWRL) project involved construction of a rail line to service new residential areas in south-west Sydney. The 11 km rail line is conveyed through a short tunnel at shallow depth where it crosses beneath the eight lanes of the Hume Highway. The underpass location is one of the most heavily trafficked within Sydney’s motorway network.The New South Wales Roads and Maritime Services (Roads and Maritime), as the owner of the highway asset, had the responsibility of managing the risks to the highway and traffic associated with the tunnelling project from the pretender stage through to completion. This paper considers the primary risks and mitigation measures employed, including geotechnical investigation, and development of appropriate construction constraints and concept design of an extensive real-time survey system to monitor pavement deformation during the tunnel works.The geology comprises fresh Minchinbury Sandstone in the tunnel invert and side walls, and variably weathered Bringelly Shale in the haunch and crown. Few tunnels have been excavated in these rock types in Sydney, and there is little information relating to the in situ stresses and stress-relief deformations in these materials.During tunnel construction the monitoring data indicated unexpected surface heave of up to about 24 mm. A multiparametric back-analysis of the deformation data is presented, which provides information on the deformation mechanisms and key geotechnical parameters, including rock mass modulus and in situ stresses.The approaches and methodologies developed for the SWRL underpass were effective in maintaining the safe operation and traffic capacity of the highway throughout the construction period, and the analysis of the monitoring data provides a useful reference for similar future projects, or projects constructed in similar ground conditions.CITATION:Clarke, S J and Walker, C S, 2014. Deformation mechanisms of the South West Rail Link underpass beneath the Hume Highway, in Proceedings 15th Australasian Tunnelling Conference 2014, pp 631–640 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 17, 2014

By A Querzoli, B Williams

In late 2014 the Flinders Power Management Team was executing business improvement plans to ensure continued electricity generation until 2028 and beyond. Six months later, in June 2015, the Board announced the closure of the Flinders Power South Australian business, including the Leigh Creek Coal Mine, the Northern and Playford Power Stations located at Port Augusta and the 250km railway line. The announcement was preceded by a brief period of internal planning. A date was soon set for ceasing coal mining operations, being November 2015. The mine is unique in many ways. Located approximately 550km north of Adelaide the site has over 100 years of history and was formerly operated by the South Australian Government. Privatisation in 2000 saw the mine continue operation under Perpetual Leases from the South Australian Government. The leases included exemptions from multiple sections of the Mining Act 1971, obliging primary regulation under the Mines and Works Inspection Act 1920. The coal, being a low rank sub-bituminous brown coal, is prone to self-heating and spontaneous combustion. The mine and company town Leigh Creek were the economic and cultural heartbeat of the community. Facilities at the mine were shared by the community and vice versa. While many mines across Australia and the world enter periods of care and maintenance, few have been actively closed to the point of relinquishment (Bennett and Lacy, 2016). A swift decision to close, followed by a short mining operations shutdown period, presented significant technical and regulatory challenges for both the mine operator and for Regulators. The subsequent joint risk mapping process employed by Flinders Power and South Australian Mining Regulators was a unique real-world example of collaborative mine closure planning and execution. Lessons learnt are valuable for all mines, production facilities and for Regulators, even for those who may wrongly assume that closure is many years away. CITATION:Williams, B and Querzoli, A, 2018. Risk management for minesite closure planning and execution – start now! Lessons from the closure of the Leigh Creek Coalfield, South Australia, in Proceedings Life-of-Mine 2018, pp 68–72 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 25, 2018

By C V. Deutsch

"Geometallurgical variables often cause problems to conventional geostatistical workflows. There are many variables; some are compositional and some are non-additive. They often show: complex multivariate relationships undersampling relative to conventional grade variables unequal sampling; that is, all variables are not available at all data locations.A variety of approaches have been developed over the years, but geostatisticians remain mostly focused on modelling rock types and a few grade variables with an abundance of data. The problems are reviewed and a chained workflow is presented where appropriate techniques are employed in sequence to permit reliable spatial prediction of geometallurgical variables. The spatial models may be used to assess the value of additional data, for prediction of process performance, for improved mine planning and other optimisation tasks. The chained workflow will include data transformations such as ratios and normal scores that make the variables amenable to geostatistical modelling. Data imputation techniques to account for missing values are considered with special consideration to spatial correlation with the available data. Decorrelation techniques such as the principal components, min/max autocorrelation factors and projection pursuit multivariate transformation are employed to manage massively multivariate modelling. Full distribution modelling must be considered to avoid biases in the prediction of non-additive variables. The post-processing of geometallurgical models must be streamlined for robustness and efficiency. The precise workflow varies according to the specific purpose of the study. Guidelines and thoughts on best practice are presented.CITATION:Deutsch, C V, 2013. Geostatistical modelling of geometallurgical variables - problems and solutions, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 7-16 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By C A. Foss, D A. Clark, D Hillan

While magnetic surveys are the most common geophysical method used in mineral exploration, magnetics and geology remain to be fully integrated quantitatively in iron ore provinces. Although high-resolution aeromagnetic data has been collected over prospective areas of the Hamersley Province, much of the information in the data sets has hitherto not been fully exploited due to a lack of suitable interpretation methods. Recent advances in the processing and modelling of magnetics in highly magnetic terrains, constrained inversion and 3D visualisation and understanding the magnetic properties of banded iron formations and iron ores potentially create the capability to generate realistic 3D mapping of magnetite and hematite concentrations over large areas. Initial processing of conventional total magnetic intensity data produces true potential field maps that are unaffected by local perturbations of the regional geomagnetic field direction by intense local anomalies. The true potential field can be converted into vector and tensor components, each of which emphasises different structural features of the geology. Scalar quantities derived from these components simplify interpretation, using new methods, developed by CSIRO and elsewhere, that are less sensitive to magnetisation direction. Preliminary interpretations allow interpolation between mapped units and structures and evaluation of remanence and anisotropy effects. Accurate modelling requires rigourous treatment of self-demagnetisation and magnetic interaction effects. Semi-automated constrained inversion, combining magnetics with available geological information and other geophysical data, can be utilised to generate models of disposition of major magnetic units and the 3D magnetisation distribution within them. The final stage of interpretation is to exploit the understanding of magnetic properties (susceptibility, anisotropy and remanence) developed over many studies by CSIRO, the University of Western Australia and others to convert the interpreted magnetisation distributions into 3D maps of magnetite and hematite contents, which are the quantities of direct exploration interest.CITATION:Clark, D A, Foss, C A, Austin, J and Hillan, D, 2015. Three-dimensional mapping of magnetite and hematite concentrations from reprocessing of detailed aeromagnetic data, in Proceedings Iron Ore 2015, pp 229–240 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By Davis RA, Wasp EJ, Cowper NT

The transportation of solids by pipeline is not new. In 1891 a United States patent broadly covering a method of pumping coal with water was granted to W. C. Andrews. His pilot plant was constructed on what is now the site of the New- York Public Library in Manhattan. His process was applied to pumping coal mine waste back into the worked out portion of coal mines. On October 26, 1967, the world's first long distance iron ore slurry line was put into service by Savage River Mines. The commissioning of this 5.0 million dollar installation climaxed three years of development, testing, and construction and proved the Company's faith in pioneering' this unique transportation method for iron ore. This paper will discuss some of the more pertinent items in connection with that three-year period. Also to be discussed will be the operation of this line during the past eleven months.

Jan 1, 1969

By S N. Donaldson, B L. Hollis, K Wynn, L Potts, M Evans

A real-time load-haul-dump (LHD) dispatch optimisation tool has been deployed at Panel Cave 1 and Panel Cave 2 at Newcrest’s Cadia Valley Operations. The tool, known as ORB, is the first known successful implementation of an optimisation-based, autonomous, real-time dispatch tool, custombuilt for underground mining operations. ORB can co-ordinate the optimal dispatch of LHD’s in a block cave to achieve a range of objectives while adhering to draw compliance and geotechnical constraints. It is an example of highly automated short-term interval control. This paper starts by outlining the pre-existing business planning process, detailing the simple logic that produced the daily draw order. Next, the motivations for a real-time dispatch tool are presented, drawing comparison to the limitations in existing planning processes and how these can be overcome through an optimisation-based, autonomous, real-time dispatch tool. Subsequently, the paper details the Ratio Bogging Draw Strategy, through which tonnes targets are expressed continuously on draw bells or draw points as a ratio of total cumulative cave draw. This signifies artificial planning boundaries are removed and that draw targets are linked within a cave; such that tonnes are unlocked by bogging other parts of the cave, instead of as a function of time. This creates incentive within the target mechanism for fixing and bogging struggling draw areas whilst allowing uncapped progress if all draw targets are progressing within compliance. Furthermore, the optimisation tool developed is outlined, including the data it uses and the objectives it optimises. Finally, detail on the improvements to operations the implementation of this tool has brought, and the business process change it has facilitated are presented using Newcrest’s Cadia Valley Operations as a case study.

Mar 15, 2021

By D Kent, D Eisner

A lot of talk has been generated about the so called ‘Internet of Things’ (IoT) and its potential to transform the way we interact with our homes and devices. But the true potential and value of IoT is not going to be realised by the general consumer but by businesses.This paper outlines the application of IoT in mining and how it is a natural extension to the base networks becoming commonplace in both surface and underground mines. The potential for ubiquitous monitoring throughout a mining operation at low capital and support costs will transform the ability to monitor, analyse, report and manage all of the key processes involved in a mining operation.Importantly, the paper will discuss the practical applications that the IoT offers mining and explain how this really is transformative technology, not just the latest buzz words from the information technology (IT) world. If leveraged correctly the impact on mining, its cost base and efficiencies, is enormous.CITATION:Kent, D and Eisner, D, 2015. What the internet of things means to mining, in Proceedings Third International Future Mining Conference, pp 65–70 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

By A Tawadrous, D S. Preece

Cave mining is of interest to the mining community as it offers a chance to extract large, deep orebodies with low operating costs and high production rates. It allows for extracting large low-grade orebodies, which may not have previously been considered for mining. Cave mining is done either top down (ie sublevel caving) or bottom up (ie block/panel caving). Both approaches rely on gravity, stresses and weakness of the rock to fracture and achieve a controlled collapse.Block caving starts at the base of the orebody. It progresses upward and across through continuous collapse of the roof. To achieve this, a critical hydraulic radius must be exceeded. This is accomplished by blasting drawbells, through which the caved ore passes to the production level. An entire level above the drawbells (undercut level) is excavated to help initiate the cave. The undercut level ensures the connection between drawbells and achievement of the required hydraulic radius.Conventionally, drawbells are generated by drilling and blasting several times from the production level as well as the undercut level. Mucking between each shot is required to generate enough void space for the rock to swell. The need for several blasts necessitates some downtime between each blast. Also, the cost of developing and maintaining the undercut level can constitute up to 35 per cent of the cost of mining the panel.A new blasting technique was developed to create the drawbells in a single blast from the production level. The technique ensures the connection of the drawbell to the neighbouring ones, thus, the critical hydraulic radius is reached and propagation of the cave achieved without the need for the undercut level. The technique has the potential to reduce the capital cost of a block caving operation, increase its feasibility and reduce time to reach the ore and consequently the payback period. This paper presents the modelling of a traditional drawbell excavation process, the philosophy of the developed technique, the modelling of that new design and its implementation.CITATION:Tawadrous, A and Preece, D S, 2015. A novel blasting technique to create drawbells and eliminate the undercut level in block cave mining, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 617–624 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 24, 2015

By AJ LYNCH

Broken Hill metallurgists have been responsible for some of the most important developments in mineral processing technology. These occurred mainly in two periods, 1902 - 15 and 1955 - 70. Mineral flotation was developed as an industrial process during the first period and this happened in two stages, the recovery of zinc minerals from the tailings dump accumulated during the gravity concentration of the oxidised ores and the selective recovery of galena and marmatite during flotation of the primary ores. During the second period fast accurate analytical procedures were developed to provide rapid assessment of process performance, and new means of controlling the process were devised which improved throughputs, grades and recoveries. These technological successes were due to the skills of the metallurgists and the commitment of the companies. They brought large financial returns. They were achieved under difficult circumstance. There are important lessons to be learnt from these successes.

Jan 1, 1992