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By F M. Weir, M Fowler

The design of excavations in rock must, implicitly or explicitly take into consideration the influence of small- and large-scale geological structures. For most sites the complexity of a fractured rock mass is best captured using a 3D fracture system model based on field data. A discrete fracture network (DFN) approach involves stochastic modelling of the ‘smaller scale’, nondeterministic structures. For slope stability or tunnelling projects DFN modelling provides a valuable geotechnical tool for characterisation of a rock mass and identification of likely failure mechanisms.This paper presents a suite of the DFN modelling undertaken for the design of a large open pit in Australia. The proposed pit is to encounter a 160?m thick, high strength, sheared shale unit, which overlies a crystalline basement. DFN modelling was undertaken separately for both the shale and basement units. While the model inputs and development for each unit are briefly presented, the focus of this paper is on the various applications of the DFN modelling.A key advantage of the DFN approach for design studies is its probabilistic application to structural analyses and results. Multiple realisations of the same model were generated for both the shale and basement units, with the stability analysis carried out on each iteration. The generation of a large number of DFN models and analyses allow assessment of wedge volume, factor of safety and proportion of unstable slope for a range of conditions. The DFN modelling at the case study site was also utilised for a number of other purposes. For example, investigation of likely fault lengths in the shale unit and combined rock mass and defect failure. The development of this tool has been influential in improving our understanding of fracture networks for excavation design.CITATION:Weir, F M and Fowler, M, 2014. Rock mass characterisation and analysis for excavation design – a discrete fracture network approach, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 445–456 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By I Grewal, M Lundt

Dense medium separation (DMS) is one of several preconcentration methods used for early waste rejection from run-of-mine ores at relatively coarse particle sizes prior to additional milling and beneficiation. DMS has been used extensively in the coal, diamonds, mineral sands, base metals and iron ore industries to produce either a final product or as a preconcentration step. Laboratory scale and pilot test work at the Met-Solve laboratory in Canada has demonstrated successful separation and upgrading of other minerals such as lead, zinc, copper and lithium based ores using DMS.This paper reviews historical dense media systems, results from the pilot-scale multi-stage DMS Separator “Condor” system, as well as production plants and associated laboratory heavy liquid separation (HLS) test work on various minerals. The mineral systems tested included a lithium bearing ore and a fluorspar ore. Other minerals were tested but are not reported in this paper.Pilot plant test work on a fluorspar ore showed that 41.6% of the mass could be rejected to the tailings stream while 95.3% of the CaF2 was recoverable to the product stream. On a spodumene sample that was tested, it was possible to reject 55% of the mass to tailings while recovering over 90% of the lithium.In recent market conditions and with the decreasing grades in existing ores, preconcentration should be a consideration to maximise the value of certain operations.CITATION:Lundt, M and Grewal, I, 2017. Dense media separation – a valuable process for preconcentration, in Proceedings MetPlant 2017, pp 122–130 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 11, 2017

By I Treloar, T Elenbaas, E Isaaks

Critical reviews of grade control generally focus on blasthole sampling and the estimation of ore control block model (OCM) grades, with little or no attention given to dig-line design. For example, the estimation of block grades is deemed important as estimation errors lead to the misclassification of ore types and subsequent dollar loss. Recognition of the problem that the underestimation of block grades may be more or less costly than overestimation led to the application of loss functions to the classification of individual OCM blocks by ore type. The method is known as maximum profit selection (MPS). However, each OCM block may be misclassified a second time by dig-line design. Although each block may initially be assigned an optimum ore type by MPS, OCM blocks are seldom individually mineable by ore type. As a result, a common solution to this problem is the design of mineable polygons or dig lines loosely constrained by a minimum mining width. All material within a properly designed dig-line polygon can be mined and sent to a single destination such as the mill, stockpile or waste dump. These dig lines are often designed manually or by simple variations of computer-generated contour lines. They are generally suboptimal and result in additional misclassifications of ore types. This paper provides an algorithm for constrained optimum dig-line design where dig-line misclassifications are also evaluated through loss functions or MPS. Constrained optimum dig-line designs minimise the dollars lost by dig line misclassifications for a given minimum mining width constraint. A case study is provided illustrating constrained optimum dig-line design and subsequent benefits.CITATION:Isaaks, E, Treloar, I and Elenbaas, T, 2014. Optimum dig lines for open pit grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 425–432 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By S Liu, N M. Rana, A Take, N Ghahramani, D Clohan, S McDougall, S G. Evans, H J. Chen

Tailings dam breaches have caused significant life loss, social, economic and environmental damage in recent years. The term "tailings-flow" refers to various forms of tailings outflow movement resulting from the breach of a tailings dam. These flows, comprising a mixture of tailings, water and dam materials, can take different forms, ranging from a debris flood to a flowslide, and can travel long distances and impact large areas. The inundation extents depend on the failure mechanism, tailings dam height, total released volume, sediment concentration (associated with the rheological behaviour of the flow) and downstream conditions (including topography, land cover and presence of a water body). Numerical runout modelling of tailings dam breaches is important for predicting the dynamics and extent of tailings-flows, which are crucial steps in tailings dam consequence analysis and risk management. This paper presents a comparison of numerical simulations of the 1994 Merriespruit tailings dam breach using three numerical models: DAN3D, FLO-2D and MADflow3D. Using compiled site condition information and data from the literature and public domain, model performance was evaluated primarily based on comparisons between the observed and simulated inundation extents. The main purpose of this preliminary model benchmarking exercise was to help us evaluate the capabilities and limitations of each model, and to identify opportunities for future model improvements as part of a broader research initiative known as CanBreach. This exercise also highlights the inherent complexity of tailings-flows and the importance of using judgement to interpret model input and results.

Jul 1, 2021

By B Murphy, S O’Connell, J L. Heath

In the 1989 best-seller The 7 Habits of Highly Effective People, the author, Stephen Covey, highlights the importance of maintaining not only ‘production’, but also, ‘production capacity’. When operating a modern flotation concentrator, production is often measured in terms of concentrate tonnage, tonnes milled and plant utilisation. There are very few metrics that focus directly on flotation equipment condition in relation to performance, which is analogous to Covey’s production capacity principal. It is evident on many mine sites that flotation equipment condition is not monitored on a proactive basis and that the prevailing culture is to wait for a failure, before addressing an issue.This paper discusses examples of how poor equipment condition can lead to production loss through poor metallurgical performance. Actual examples are given where these problems have occurred in operating plants. An outline is provided on how metallurgical and maintenance departments can work together to protect production capacity and gain more from existing equipment.CITATION:Murphy, B, O’Connell, S and Heath, J L, 2014. Maximising value through maintaining your flotation equipment, in Proceedings 12th AusIMM Mill Operators’ Conference 2014 , pp 71–76 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 1, 2014

By M Berry

Many mining companies routinely use benchmarking to review their operational activities and associated costs. The aim is to measure operational performance against industry norms, and identify areas where a company is performing better or worse than industry best practice. The goal is continuous improvement.In general, mine technical services, including mining geology activities, are not routinely benchmarked. There are exceptions, such as the cost of drilling per metre and the average discovery cost per unit of metal, but generally mining geology activities are only included indirectly in mining benchmarking studies.Aspects of benchmarking can play a critical role in assisting mining geologists to improve the efficiency and effectiveness of the services they provide. Industry norms for many generic mining geology functions have not been developed and measured, and therefore it is impossible to use external benchmarking to assess performance against other mines. But when used in parallel with quantifying the value of mining geology functions and establishing strategic goals for the team, key components of benchmarking methodology can provide essential feedback on how a team is performing against these strategic goals.CITATION:Berry, M, 2014. Benchmarking – does it have a role in improving the performance of mining geology?, in Proceedings Ninth International Mining Geology Conference 2014 , pp 361–366 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By Q Wang

Net present value (NPV) has been the main criterion in mining project evaluation and production plan optimisation. It is a common practice in NPV calculations to take into account only the tangible cost items in the corporate accounting system. The costs incurred due to damage to the local ecosystem and environment are left out and treated as externalities. Such practice on the one hand underestimates the total cost of a mining operation and, on the other hand, ignores the difference in ecological/environmental impacts between different mine plan alternatives. This paper attempts to measure the ecological costs of mining and to incorporate such costs into the evaluation scheme in mining project evaluation and mine planning. The ecological costs of mining are estimated based on the areas and types of land (eg forest land, grazing land, crop land) damaged by mining activities and the carbon emission from fossil fuel consumption. For the land areas (and their associated ecosystems) directly damaged by mining activities, the ecological costs are measured by the prevention and restoration costs, the lost values of eco-services of the damaged land, including bio-product production, soil erosion control, water run-off control, oxygen release, air pollutant absorption and formation of soil nutrients. The ecological cost of carbon emission from the energy consumption of a mining operation is measured by the cost of cultivating the equivalent forest land required to uptake the emitted carbon. A case study on a large-scale open pit mining project is presented to demonstrate the influence of ecological costs on the mine planning outcome.

Sep 26, 2011

"Cash flow modelling during project evaluation is enhanced when probabilistic methods are applied to the inputs. One of the important inputs is the quarterly production profile. Typically, the steady-state production profile provided to project evaluation practitioners is deterministic, with each quarter the same as every other quarter. This is unrealistic as actual production profiles from existing mines exhibit a range or quarter-on-quarter variance. Monte Carlo stochastic simulation of the production profile can be used to provide a range of possible outcomes, but how are these ranges selected? This paper describes the use of quarterly production variance from a large database of mines worldwide as a benchmark to inform the appropriate selection of ranges. The coefficient of variation is used to rank the production from mines, with quartile analysis applied to indicate industry best, median and worst variation. Due diligence of existing mines and evaluation of future production performance can be quantitatively assessed using this approach. Examples of the effect on value are provided.CITATION:Stewart, C A, 2016. Production variance benchmarks and their use in project evaluation and due diligence, in Proceedings Project Evaluation 2016, pp 201–213 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Mar 8, 2016

I once read an æarticleÆ in FHM Magazine entitled æThe Coolest Jobs There Ever WasÆ. It was about a group of guys who were pursuing careers that any person on the planet would just kill for. I distinctly remember drooling over the pages, thinking how much I would love to be Michael SchumacherÆs Chief Engineer at Ferrari, or the Principal Designer and Tester for one of the big Dutch rollercoaster companies. From that moment on, I decided that I wanted a career that was cool enough to make it into the pages of that article. Throughout my time at university, I always had that article in the back of my mind. As a result I constantly wondered about what sort of job I could end up with once I left university. More importantly, I wondered if FHM would be banging down my door to put me in the magazine! After a long and stressful job hunting process (in between completing a thesis and studying for exams) I finally managed to land myself a job with Orica Mining Services. I can honestly say I didnÆt know what to expect when I first joined Orica. Most of my friends ended up working for big mining companies, while I was offered a position with one of the biggest suppliers to these mining companies. However, I had a feeling when I was discussing the role with my future supervisor during the interview process that the job was going to be awesome. I have now spent a year working for Orica and I absolutely love it! While I feel that my job is worthy of being in that FHM article, unfortunately, I donÆt think I am going to get my opportunity to be in the magazine. Apparently I donÆt look too good in a bikini! However, I would love to have the opportunity to discuss the journey that I have taken so far û from my time as an environmental science graduate, then moving on to mining engineering, to now, being part of the Orica Mining Services Graduate Program. My suggestion is to use this paper as a resource. I have learnt during my time at university, as well as my time in the workforce, that the best people you can learn from are your peers. Take what you feel is relevant from the paper; hopefully it will help guide you in shaping your own career.

Jan 1, 2005

The rush for alternate iron-units in the last few years spurred a true outbreak of new alternate iron units projects many of them incorporating new process in what can be classified as the.most fruitful and innovative technology outburst, in the steel industry, in decades In a recent paper we focused on what would be, in our opinion, the ultimate targets of the use of alternate iron-units by mini-mills: 1. to improve quality, 2. to reduce cost, 3. to increase plant productivity, and 4. to improve `supplyability'. With these objectives in mind liquid hot-metal, among all possible scrap substitutes, has been proven to be by far the best. This conclusion stems from many different authors who have reviewed the `value in use' of hot-metal against other alternate iron units and measured its impact on steel-shop productivity and cost (Figure 1).

Jan 1, 1999

By K S. Smith, J Woodhead, K Olson Hoal

Mineralogy is the link between ore formation and ore extraction. It is the most fundamental component of geomet programs, and the most important aspect of a life-of-project approach to mineral resource projects. Understanding orebodies is achieved by understanding the mineralogy and texture of the materials, throughout the process, because minerals hold the information required to unlock the value they contain. Geomet mineralogy programs absolutely require the appropriate expertise and at least three steps of mineral characterisation prior to using semi-automated or other methods: field examination, thorough core logging, and optical microscopy. Economic geological inputs for orebody characterisation are necessary for orebody understanding, and are exemplified by current research in the Zambian Copperbelt, where revised sequence stratigraphy and understanding of alteration, metasomatism and metamorphism can be used to predict topical issues at mine sites. Environmental inputs for sustainability characterisation are demonstrated by recent work on tailings from the Leadville, Colorado, USA area, including linking mineralogy to water quality issues. Risk assessments need to take into account the technical uncertainties around geological variability and mineral extractability, and mineralogy is the only metric that can be used to make this risk contribution.CITATION:Olson Hoal, K, Woodhead, J and Smith, K S, 2013. The importance of mineralogical input into geometallurgy programs, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 17-26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By D J. Brake

The importance of mine ventilation to health and safety in both coal and metalliferous mines has been long recognised. The primary and secondary ventilation systems in most metalliferous mines incur 50 per cent or more of the total mine electrical power consumption and frequently about 10 per cent of total underground mine operating costs. The requirements for ventilation-related horizontal and vertical development, fans and cooling have a significant impact on mine capital costs and also on mine schedules and start-up times and hence cash flows. There are increasing pressures on regulators and miners to reduce airborne contaminants such as diesel particulatematter, nitrogen dioxide and heat (wet bulb temperatures), and significant pressures to reducegreenhouse gases such as fugitive methane emissions from coalmines and the carbon dioxide footprint of both coal and metalliferous mines. Many previously Australian miners are now globaloperators and have extensive overseas mining operations where local ventilation standards and expertise may not be consistent with Australian practices. The role of the site ventilation officer is also changing with strict new requirements for the statutory position being introduced into Queensland metalliferous mines and the potential for this to become more widespread. Recent regulator and parliamentary review committees have identified systematic shortcomings in mine ventilation compliance, and statutory certificates in both Queensland and NSW now require continuing professional development to maintain currency. Public and investor support for mining are also increasingly contingent on safe, healthy and environmentally responsible practices and the standards for these are frequently tightening. Good ventilation design and operating practices that are consistently well executed therefore contribute significantly not only to a safe and healthy mine but also to a productive and cost-effective operation and the ongoing social licence to operate. There are a variety of ways of providing technical design and oversight into a mine’s ventilation systems; this paper explores some current trends in ventilation standards and statutory requirements, as well as ways to support and develop mine ventilation staff for both domestic and international operations and also the emerging senior technical roles of Group/Principal/Corporate mine ventilation engineer.

Oct 12, 2022

By P B. Card

"The website www.economicevaluation.com.au, which had its origins at the Project Evaluation Conference 2009, provides a free way for industry professionals to teach themselves economic evaluation. At its core is a set of fast-moving modules and three worked examples.The website recognises that economic evaluation is a discipline with a hierarchy of three levels:decision-makingevaluating the project/businesshands-on modelling.There are a set of modules for each level that describe the concepts and activities in detail. These emphasise that the most important and rewarding work is the evaluation of Level 2. The economic model created in Level 3 is merely a working tool and should not become a sophisticated ‘trophy’ in Excel that only one or two people can comfortably use.Hands-on modelling contains three sets of practices designed to make any model rigorous and intuitive so that it can be easily understood and used by others in the project team. Even if the model develops into a long, detailed and complex workbook, it should remain easy to follow and be intuitive. The website advocates freedom to devise any architecture that best suits the project under study, but promotes rigour through the following practices:four cash streams and graphsthree architectures – concept, prefeasibility and feasibilitysix principles.The modules in the Level 2 evaluation use conversational language to describe in detail the broad range of activities needed to properly understand and characterise a project/business. It stresses that net present value is nothing more than the mathematical treatment of a whole set of opinions, is not an absolute truth and is only a fraction of the evaluation process. The modules describe in detail the range of economic metrics that should be computed and the full spectrum of equally important characterisations required to make the decision in Level 3.CITATION:Card, P B, 2016. Teach yourself economic evaluation, in Proceedings Project Evaluation 2016, pp 160–171 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Mar 8, 2016

By P Stoker

The need for quality assurance and quality control (QA/QC) in the sampling and assaying of minerals is fundamental to the reliability and confidence of a mineral resource estimate, reserve estimate and possibly profitability of a mine. In spite of this, QA/QC practices in the mining industry are commonly applied poorly, or misunderstood. As New Leaders, we should aim to correct the poor practices and become fully informed on appropriate procedures. This paper uses worked examples that show the usefulness and importance of best practice QA/QC procedures. Fundamentals of reviewing the performance of the laboratory by examining the results of client inserted standard reference material (standards), blank material and duplicate samples are discussed. To do this, three examples from Australian data sets have been used. For each example, simple and efficient plotting techniques are suggested with subsequent evaluations of each plot. The first case study compares the results of internal standards from a laboratory with blind standards (where the expected value is unknown to the laboratory) submitted by the client. It was demonstrated over time that the laboratory was unintentionally analysing the internal standards in a different manner to the remainder of the sample batch. In this example, not understanding the cause of a high negative laboratory bias could have led to poor understanding of the depositÆs grade and in the extreme a proposed mining operation may have reached operational stage with a subeconomic grade. The second case study discusses the quality of blank material submitted by a mining operation to monitor cross-contamination within the laboratory. The blank material contained background levels of the element under investigation. This created uncertainty in the assay results, which could have led to the need for additional assays and drilling programs. Finally, the third case study demonstrates the use of the relative paired differences (RPD) technique to cross-validate the results from duplicates and repeat analyses from two laboratories. The three examples given show either laboratory or operational error. If left undetected, each example could have had serious implications for the mineral resource estimate and ultimately, the mining operation. These examples are not isolated occurrences; poor QA/QC practices are an industry wide problem exacerbated by rapid staff turnover and increased contractor positions on-site. New Leaders must be equipped with a thorough grounding in QA/QC best practices to improve its application and confidence in the results of sample analysis.

Jan 1, 2009

By B Yeganeh, A Sam, A Kohsari

The base of separation at Gol-e-Gohar iron ore plant (Sirjan in the south of Iran) is magnetic separation after milling. Magnetic separation in the plant is divided into two parts: dry magnetic separation and wet magnetic separation. Sixty-five per cent of the plant production belongs to the dry magnetic separator section. Therefore, investigation of this part of the plant is necessary. Prediction of plant production is one of the most important subjects in mineral processing plants. That means, before feed enters the plant, specification of production has been calculated with laboratory methods. The purpose of this paper is the prediction concentrate quality has achieved from the dry magnetic separator. The content of iron in the final dry concentrate will be predicted, with laboratory, pilot and modelling methods, before feed enters the plant. Different variables are used in this approach, which consist of: speed of the first dry magnetic separator (rougher), speed of the third dry magnetic separator (cleaner), iron content in plant feed, size of 80 per cent passing of feed, size of 20 per cent passing of feed and iron content in pilot dry magnetic separation concentrate that performs in a standard manner. The artificial neural network is used for modelling and one of its branches is the radial basis network (RBN). Iron content in magnetic separating concentrate in plant will be introduced as the target and will be calculated with the RBN method. In the RBN method, a set of data enters to neural network and they will be trained and simulated. Finally, the target will be predicted. Ultimately, the original target (actual iron content) and the predicted target (predicted iron content) compare and error of them will be calculated. The obtained result is acceptable and satisfactory.

Jan 1, 2007

By P Dowd, R Jeuken, C Xu

In Australian coalmines there are a number of coal quality parameters that are measured by analysing samples from boreholes. The data points are used to generate spatial models of these parameters, typically using inverse distance as an interpolation method. Numerous additional boreholes are drilled which have geophysical logs measured downhole but from which no coal quality samples are taken. Full suites of coal quality analyses are expensive and time consuming to drill and sample. If geophysical proxies for coal quality could be used, this would greatly improve the accuracy of the resource estimation without additional cost.This paper examines two of the most important coal quality parameters – ash and volatile matter – and assesses the results of a number of geostatistical interpolation methods. The aim is to improve the accuracy of the interpolated models. Auxiliary variables from geophysical logs are also trialled to improve the estimation.A multivariate analysis of ash, volatile matter and several auxiliary variables of a selected coal seam was undertaken in a spatial context, using variography. This was used to construct a model of co-regionalisation that relates all of the variables as manifestations of an underlying geological theme.The traditional inverse distance interpolation approach was compared to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with external drift approaches. The relative merits of the six interpolation methods were compared by removing all points, one at a time and estimating at the thus known location. The mean error and the root mean square error were evaluated as a measure of bias and precision.This paper demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with external drift. For example, the results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter. Furthermore, when using borehole wireline density logs as an auxiliary variable for ash content, there is improvement in the estimation of the in situ ash. The underpinning reasons for this are discussed in the context of the underlying geology and the physical properties of the coal. These findings hold promise for utilising cheaper proxies for coal quality parameters to dramatically improve data density and the quality of estimations.CITATION:Jeuken, R, Xu, C and Dowd, P, 2017. Improving coal quality estimations using geostatistics and auxiliary variables, in Proceedings Tenth International Mining Geology Conference 2017, pp 157–168 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

By A Bossilkov

Although environmental and sustainable development reporting has now become widespread in the Australian mining and minerals processing sector, there remains a great deal of diversity in reporting contents and practice. Moreover concerns remain about the effectiveness of reporting for delivering the companyÆs business case for sustainable development as well as for communicating sustainable development performance to a range of external stakeholders. This paper therefore reviews the status of sustainable development reporting in the Australian minerals processing industry. Pertinent international and national developments are briefly captured, leading to a discussion of the framework for integrating sustainable development reporting with sustainable development management (as proposed by the World Business Council for Sustainable Development). This leads to a discussion of the results of a comparative review of sustainable development reports of a cross-section of eight Australian resource companies. Best practice elements are highlighted in regard to reporting on company context, governance, performance and assurance.

Jan 1, 2004

By T Kojovic, S J. Windle, J Sullivan

"The Geometallurgical Mapping and Mine Modelling (GeM) comminution index (CI) was developed as part of the AMIRA P843 GeMIII project. Drill core geochemistry samples were passed through a Boyd Crusher with standardised settings and the resulting particle size distribution (PSD) was measured using sieves.Disadvantages of the original measurement were the relatively coarse crush size, requiring a second pass of crushing for geochemical sample preparation, and the limitation of throughput caused by the sieving step. At Antamina, the measurement has been modified to use a 2.2 mm crusher size setting, which permits a single pass. The PSD is measured using a Camsizer, an automated optical sizing instrument. The Camsizer sample is a +180 µm fraction, used to avoid passing too many fines through the instrument and slowing down the measurement. In the sieving step, the weights of the two fractions are recorded and subsequently used to normalise the distribution measured by the Camsizer. In this way, the throughput of the Camsizer can match that of the Boyd Crusher. The PSD data are therefore measured without penalising the throughput of the sample laboratory.The normalised PSD distributions are used to derive modified CI parameters, based on the slope and intercept of the breakage product size distribution, which are indirect measures of the material breakage hardness.Fifty samples were selected as a training set, each sample a composite of five or six individual assay intervals and each with its own measured CI. The average PSDs were calculated for the composites and used to calculate a composite CI. The intact half of the core, approximately 40 kg, was tested to measure the BWi, A*b and crushability. The results were used to develop predictive algorithms for these hardness parameters.A further 50 composites were chosen for lab testing, to serve as a blind test of the algorithms. The paper reports on the test results and the incorporation of the modified CI data and predicted hardness parameters into the Antamina block model.CITATION:Windle, S J, Kojovic, T and Sullivan, J, 2016. Use of a Modified Comminution Index to Predict Bond Work Index and SMC A*b at the Antamina Mine, Peru, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 153–160 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By D Beck

Open access to forecasts of mine geotechnical performance in the form of open databases of model results has been considered risky in the past, with a concern that the results will not be understood or will be misused. However, some modelling techniques allow very high similitude modelling of mine deformation and the results can be presented as deformation, damage and other parameters which are unambiguous and which all engineers can be more easily trained to understand. With some effort, sufficient reliability and quantifications of error are possible to overcome many of the issues.Allowing more members of the planning team to have direct access to forecasts of mine deformation will promote awareness of geotechnical issues and will act as a mechanism for improving mine designs. The models will also be more easily integrated into quality assurance programs, by providing a framework for understanding measurement results.The sufficiency requirements for undertaking simulation aided mining engineering will be presented, included some conclusions about requirements for training, quality standards and software development.

Mar 21, 2011

By R O’Sullivan, D Taylor, J G. McLellan, B Miller

The Mount Isa copper deposit is located adjacent to the city of Mount Isa, Queensland, and lies within a series of Palaeoproterozoic to Mesoproterozoic Superbasins. The deposit is hosted almost entirely within the Urquhart Shale (US), a unit of the Mount Isa Group sediments and part of the Isa Superbasin. The copper mineralisation is separated into two distinct orebodies: the X41 mine (1100 and 1900 orebodies) and the Enterprise mine (3000 and 3500 orebodies). The orebodies are situated in the hanging wall of the major controlling structures, the Paroo Fault, which has juxtaposed older basement Eastern Creek Volcanics against the younger Mount Isa Group sediments cf 1655 ± 4 Ma. Conjecture remains over the exact timing of this thrust event. However, it is clear that inflections on the Paroo Fault have a close association with the orebodies and are an important structural feature in the mineralisation of the Mount Isa copper deposit.The life-of-mine is reducing steadily and new geomechanical modelling techniques were employed to target structurally controlled mineralised zones in three dimensions. Following a structural review of the mine using underground mapping, structural data and core shed observations, a conceptual 3D mine model was constructed utilising existing data modelled in MineSight®. This conceptual model included all the main lithological units and structures. The conceptual model aimed to test the effects of deformation on the main lithological and structural components of the system and attempted to highlight areas of anomalous stress and strain that may indicate a higher likelihood of fluid focusing and mineralisation potential. This project was focused on testing the latter stages of a D3 event (NE–SW compression) and D4 event (SE–NW compression), which are considered to be responsible for the current location of the mineralisation.The fully coupled 3D finite element analysis models resulted in highlighting anomalous patterns of stress and strain and subsequent fluid flow as a result of the two deformation events. The NE–SW D3 simulation provided the best correlation with the known distribution of mineralisation. This event also indicated several areas on the Paroo Fault and within the US that have potential to host further areas of mineralisation. The SE–NW D4 simulation provided less of a correlation with known mineralised zones. However, this event may have been responsible for post mineralisation re-mobilisation of copper on a relatively small scale. Areas of maximum shear strain, shear stress, volumetric strain and fluid flow correlated well with areas of minimum principal stress and provided the best overall match with known mineralised zones. Furthermore, several additional highlighted areas provide a high potential for further discovery of copper mineralisation. Recent exploration drilling north of the Enterprise mine 3000 orebody, utilising geomechanical modelling as part of the targeting criteria, intersected copper mineralisation, providing further validation of the modelling results.CITATION:McLellan, J G, O’Sullivan, R, Miller, B and Taylor, D, 2014. Geomechanical modelling of the Mount Isa copper deposit – predicting mineralisation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 197–206 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014