Search Documents

By A Weeks, W J. Shaw, A Kuk

Grade control is a process that requires the interaction between many components of the mining operation and successful grade control is only realised through good data, robust systems, and a well-trained, motivated and disciplined workforce.The Mt Magnet Gold Project Pty Ltd (MMGP), a wholly owned subsidiary of Ramelius Resources Limited, started mining at Mt Magnet in February 2012 with high expectations for success. Positive cash flow would fund an aggressive exploration and mine development program in the area to increase mine life. Disappointment followed when after start-up the operation had issues achieving budget grade and realising the predicted grade of the mined ore. In January 2013, things started to improve. During the next six months, gold production steadily increased with successive months achieving record production. What had changed?Improvements started following the realisation that controlling grade was not the sole responsibility of the mining geologist and that everyone on-site has a role to play. This paper examines the factors that delivered success for MMGP.CITATION:Weeks, A, Shaw, W J and Kuk, A, 2014. Who is responsible for grade? – an evaluation of the value chain at Mt Magnet Gold Project, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 477–482 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 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 C De-Vitry

In skewed distributions seen in many geochemical data sets, samples at the extreme ends of the distribution are often termed ‘outliers’. Samples considered as outliers can often make exploratory data analysis and resource estimation more difficult and less reliable. Such outlier samples may be legitimate because they are part of a natural high- or low-grade tail in the distribution. How these samples are identified and dealt with in resource estimation can often be a material issue for the Competent Person, particularly under the latest edition of the JORC Code (JORC, 2012). This paper discusses the identification and characterisation of outliers and high- and low-grade tails and proposes methods to deal with them in estimation.For dealing with outliers and high-grade tails ,very simple approaches, such as top-cutting through to more advanced geostatistical approaches, are discussed. The strengths and weaknesses of each approach are also outlined. Some examples of how the underlying geological understanding of a deposit influences the view of outliers and low-/high-grade tails is provided. The importance of documenting, communicating and challenging a given geological model is also discussed. Finally, some ideas for dealing with the uncertainty created by outliers are outlined.CITATION:De-Vitry, C, 2014. Identifying and dealing with outliers in resource estimation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 159–168 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By W J. Shaw

Mining operations must become more predictable to overcome the volatility that has characterised the mining industry. Comparisons of production against predictions will become more consistent as mining operations merge and expand, as personnel move from site to site, and as public reporting of reconciliations becomes more prevalent. More consistent approaches are already being seen in the industry using the terminology used in this paper and elsewhere.Examples are provided that show how use of the waterfall chart as a reconciliation management tool can provide objective analysis to improve practices.Geometallurgical modelling is becoming more useful and will continue to do so as we move from a few bulk samples to better interpretation of material properties from geological mapping and drill sampling. Reconciliation has evolved to the stage where predictions of geometallurgical properties to optimise mill performance, and of geotechnical properties derived from better 3D geological models, should also be reconciled.CITATION:Shaw, W J, 2014. Reconciliation – outcomes and expectations, in Proceedings Ninth International Mining Geology Conference 2014 , pp 123–128 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By T Blenkinsop, A Jenkins, H Moore, L Fisher, N Oliver, J Cleverley, M Nugus, J McLellan, J Hill, N Brunacci

The 2 Moz Vogue mineral resource is a recent discovery at the Sunrise Dam gold mine (SDGM), lying approximately 600 m vertically below the Sunrise Dam open pit. Unlike most other lodes, which are dominated either by steep vein sets or shallow high-strain (shear) zones, it lies broadly in the hinge of a folded felsic porphyry body, where it cuts intermediate volcanic lavas and volcaniclastic rocks and is not specifically concentrated at a lithofacies contact. The mineralisation is controlled by a complex interplay of moderate to shallow, west-dipping high-strain zones that are transected by irregular and discontinuous high-grade, north-west-, north–south- and east–west-trending breccia sheets that initially caused problems with attempts to model broad domains. However, by combining the structural controls and styles with the distribution of gold, arsenic, sulfur and antimony, we have improved opportunities for scheduling, extracting and processing the most appropriate material considering the current mining and processing constraints.The early delineation process for the Vogue lode revealed a significant mineral resource for the SDGM, coupled with the recognition of some potentially difficult downstream implications for mining and processing. The ultimate success of mining at Vogue will be a consequence of combining standardised data collection and geological modelling techniques with the results of the novel innovative techniques applied at an early stage of the project.Innovation (in the truest sense) drives change and application to deliver efficient and effective outcomes. Initial data generation and interpretation in lodes above Vogue provided a sound geological model based on strong structural foundations, leading to ideas that could be tested and validated by stress inversion analysis and modelling simulations. Geomechanical modelling simulations, based on the structural analysis, then provided an insight into both the structural and fluid evolution of the system and highlighted target areas. This promoted support for deeper drilling and sampling, which lead to the discovery of Vogue.With additional data, the structural model for Vogue was re-engineered through combination with geochemical and hyperspectral analysis and detailed geological and geostatistical domaining. Initial poor results from metallurgical tests from a small batch sample refocused efforts to undertake mineral and chemical characterisation and profiling (geometallurgy) and combine this data with the composite geological-structural-geochemical model. The result is a conditional probability model for differentiating mineralised or waste domains, with direct outcomes for planning, drilling and mining.CITATION:Nugus, M, Oliver, N, Blenkinsop, T, Hill, J, McLellan, J, Cleverley, J, Fisher, L, Brunacci, N, Moore, H and Jenkins, A, 2014. Exploration and innovation – the discovery and evolution of the 2 Moz Vogue Gold Resource, Sunrise Dam Gold Mine, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 323–340 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By D Smith, A Ramdhani, J Francke

Ground penetrating radar (GPR), a well-established geophysical technique generally used for shallow civil engineering applications, has, in the last decade, found increasing acceptance as a complementary tool in mineral resource evaluations. As new sites are trialled with the method, a greater understanding is being garnered regarding the most suitable environments for long-range radar. Although successful projects have been conducted worldwide for mineral sands, iron ore and alluvial projects – tropical weathering environments have produced some of the most impressive results. Specifically, tropical nickel laterites have shown to be, with some notable exceptions, ideal GPR environments.Such high-resolution remote sensing has particular relevance to bulk commodities or those which possess significant rheological variation within geological units, and has led to some innovative downstream uses within exploration, project development and the larger mining industry. In this paper, we examine the application of long-range GPR in Indonesian nickel laterite deposits in general, to highlight some of these novel applications with particular reference to resource modelling, mine geology and operational economic implications.CITATION:Francke, J, Smith, D and Ramdhani, A, 2014. Ground penetrating radar to enhance the exploration-to-mining value chain, in Proceedings Ninth International Mining Geology Conference 2014 , pp 175–182 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By S Mundell, J Armstrong, M Evans

"Automation is a common goal within the coal industry for reasons such as efficiency, reliability and sustainability. However, it requires standards and frameworks so business systems can communicate effectively. Automation of sample analysis processes has been difficult to establish due to a lack of direct business system communication between commercial laboratories and mining companies. This has resulted in manual procedures that have contributed to problems relating to analysis instructions, sample identification, results formats and visibility of status.These problems result in loss of data and confidence in data validity, loss of process efficiency and inability to react to issues. An Australian Coal Association Research Program project (Evans, Armstrong and Arboleda, 2014) has addressed these issues through the Coal Quality Data Exchange methodology for direct business system communication between coalminers and commercial laboratories to optimise the transfer of coal quality data.The benefits to the coalminer of the framework are:increased clarity and auditability of what is being sent to the laboratory and what was requestedreduced potential for error introduced through manual transcription tasksincreased speed of loading of analytical results to the customer Geoscientific Information Management Systemimproved turnaround time for analytical resultsincreased knowledge about what took place in the laboratory with respect to the determination of the analytical resultsincreased visibility of the status of a ‘work order’. The benefits to the technology companies and commercial laboratories is a common framework on which to build a sustainable solution that gets away from the multitude of formats catered for today and time consuming manual processes. The common framework significantly advances the future possibilities for the automation of sampling and analysis processes in a production environment.CITATION:Armstrong, J, Mundell, S and Evans, M, 2014. Automating communications between laboratories and mines – a case from the coal industry, in Proceedings Ninth International Mining Geology Conference 2014 , pp 351–360 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By J P. Sykes, A Trench

"World-class mine projects are increasingly failing to become world-class mines. Non-technical, socio-political and environmental problems seem, in part, to be the cause. However, the intangible and qualitative nature of these problems means overcoming them will require a greater systemic understanding of how the various technical and non-technical factors interact. This is particularly important as the concept of sustainable development has changed the industry paradigm sufficiently that it is no longer clear what world-class means. Finally, this better systemic understanding of mine projects needs communicating back to the exploration sector to improve exploration targeting.However, a disconnect between the exploration and mining sectors and between geologists and mining’s other professional disciplines means this is currently not possible. The use of economic evaluation techniques to assess the risk and value presented by the various technical and non-technical factors can assist with this by giving the varied professions a common language and including inputs from all disciplines. This paper therefore suggests a theoretical framework for analysing the various technical and non-technical factors, particularly the most challenging intangible and qualitative ones, and incorporating them into the typical economic evaluation techniques used in the mining industry.Understanding the risk and value relating to both technical and non-technical risks, however, places a greater emphasis on mining geologists to be conversant with a wide range of disciplines. Mining geologists will have to develop three types of knowledge:focusedinter-disciplinarybroad. In addition, they will have to become systemic thinkers to connect these types of knowledge. This multidisciplinary approach will require the use of fundamental critical thinking skills, common sense, intuition, experience and quantitative modelling techniques, dependent on the situation. As a result, both companies and professional societies, such as the Australasian Institute of Mining and Metallurgy, will have to develop ways of improving mining geologists’ inter-disciplinary and broad knowledge.CITATION:Sykes, J P and Trench, A, 2014. Resources versus reserves – towards a systems-based understanding of exploration and mine project development and the role of the mining geologist, in Proceedings Ninth International Mining Geology Conference 2014 , pp 243–270 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By A N. Kusnanto, D Sims, L Henim, S Crispin, J Hertrijana

The high sulfidation Purnama Au-Ag deposit located on the Indonesian island of Sumatra entered production in mid-2012 following a two-year program of construction and development. Discovered in 1997 following a regional stream sediment geochemical sampling program by the Normandy Anglo Asia joint venture, it is the first and largest deposit in G-Resource’s Martabe Project to enter production and is the centrepiece of a series of six deposits totalling 8.1 Moz Au and 73.8 Moz Ag in Mineral Resources (G-Resources, 2013a).In 2011 investigation into the controls of high-grade mineralisation in isolated parts of the deposit identified a potentially significant mineralisation style which had not been previously recognised or accommodated in the resource model. An extensive investigation of core and logging data followed to confirm the distribution of the somewhat unusual mineralisation style – a sedimentary-like cavity infill of very high-grade auriferous pyrite within the steep hydrothermal breccia feeders to the system. With the bulk of mineralisation located within the adjacent volcanic sequence and sandy-matrix phreatomagmatic breccia surrounding the feeders, the lack of constraint for high-grade intersections in the hydrothermal breccia zones had potential to significantly impact the mine plan in the lower sections of the planned pit through overestimation of local gold grade. Combined with new data emerging from grade control drilling and infill resource drilling in the pit, a program of reinterpretation of the deposit was initiated to update the geological and alteration framework underpinning the resource model. The result has improved the economics of the project and added metal to the Ore Reserve for Purnama.CITATION:Sims, D, Henim, L, Hertrijana, J, Kusnanto, A N and Crispin, S, 2014. Remodelling the Purnama deposit – an interpretation case study from G-Resources Martabe Project, Indonesia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 229–236 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By P F. Hodkiewicz

"Our understanding of mineral resources relies on three basic steps: data capture data interpretation model construction. Until recently, all three of these steps required significant time and manual effort to produce a single resource model for mine planning, typically taking more than a year to progress from drilling to the final block model. Over the past several years, BHP Billiton has been developing innovative workflows in rapid resource modelling projects to significantly reduce these time constraints and make the process more productive by replacing manual activities with automated ones. Rapid resource modelling is the process of combining recently developed off-the-shelf technology with internal technology developments to fundamentally change the way we collect, interpret, model and evaluate geoscience data. Initiatives include automated systems and standardised workflows to make it safer, faster and cheaper to continuously update multidiscipline resource models. Specifically, rapid resource modelling workflows combine: real-time analysis of drill holes and drill samples with downhole tools and hyperspectral scanning systemsautomated interpretation of drill hole intervals based on pattern-recognition algorithmscontinuous modelling workflows using implicit modelling software. This paper outlines technology developments and workflows that provide a more thorough understanding of mineral resources to support faster and more informed strategic, planning and production decisions.CITATION:Hodkiewicz, P F, 2014. Rapid resource modelling – a vision for faster and better mining decisions, in Proceedings Ninth International Mining Geology Conference 2014 , pp 183–188 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By E J. Sellers, A Cocker

Movement of the fragmented rock mass is an inevitable consequence of open cut blasting. Uncontrolled, unaccounted movement from blasting commonly causes ore loss and dilution from waste mixing. Therefore, the prediction of the post-blast location of both ore and waste is vital in grade control and of direct interest to mining geologists. Direct measurement techniques have matured significantly over the past decade, but their use remains expensive and labour intensive. Access and safety issues are further disincentives to regular movement monitoring. What is needed is a combination of direct measurement to establish baselines and reliable predictive modelling.The W H Bryan Mining and Geology Centre of the University of Queensland has pioneered 3D blast movement modelling using ‘physics engines’ to handle in-flight collisions and predict the final resting place of blasted material. Open cut metalliferous mines are a demanding environment for this style of modelling as they can involve complex geometries and variable buffering, which leads to inconsistent confinement. A version of the model designed to deal with these complexities is under development. A well-controlled field trial was needed to validate this new version.A validation trial was completed at a gold mine in South-East Asia. The aim was to increase throughput by increasing the blast powder factor without losing grade through dilution and mixing with waste. Four blocks were blasted to identify the effect of bench height and face confinement on ore movement, fragmentation and process throughput. The powder factor and blast timing were kept constant. Movement of the broken rock was measured by placing blast movement monitors at known positions in the block and then locating them after the blast. The majority of sensors were recovered, providing a unique insight into blast movement dynamics and generating a substantial data set for model validation.The model (called ‘MetaMove ‘) was calibrated for one blast and applied to investigate the extent of grade loss and possible mitigation strategies. Conventional mining techniques that involved firing across the strike of the orebody, and no post-blast boundary adjustment of the ore/waste boundaries prior to digging, were found to cause up to 44 per cent loss of high-grade ore, depending on the grade distributions. Post-blast adjustment of the ore/waste boundaries can negate this loss. The model indicates that altering timing and ensuring that the block boundaries are well confined can further constrain the movement of ore/waste boundaries. Thus, the model can be successfully applied to minimise grade dilution and limit misclassification of ore as waste whilst using higher powder factors to increase mill throughput. Application of a calibrated model to move ore/waste boundaries prior to digging will enable the production geology team to add significant value to the mining operation.CITATION:Cocker, A and Sellers, E J, 2014. Modelling blast movement for grade control at an open cut gold mine, in Proceedings Ninth International Mining Geology Conference 2014 , pp 377–386 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By G D. Matthews, M E. Haylett, S Khosrowshahi, A Weeks

In narrow orebodies the use of ordinary kriging (OK) may pose certain limitations when used for grade control modelling. The smoothing effect of kriging, by its very nature, cannot retain or accurately characterise the dispersion (variability) that is inherent in gold deposits. This dispersion is a critical component of determining the desired level of ore loss and dilution.Fixed block model positions used in OK, and all estimation approaches, within a grade control process may never align with the ‘true’ ore boundary. This may lead to excessive ore loss and dilution, especially within narrow lodes.Using a risk-based approach to ore block design based on the geostatistical method of conditional simulation (CS) can highlight the differences achieved when an alternative method to OK is used for grade control modelling. By using a mesh of nodes and the application of a ‘transfer function’ to the simulation models, the position for ore contacts can be better assessed than when using fixed blocks in OK. Therefore, the value of various ore block boundaries can be better analysed by objective assessment of ore loss and dilution for a given minimum mining selectivity (selective mining unit or SMU), even in narrow lodes.A case study of a narrow vein gold deposit, comparing the results from an OK model and a CS model shows that whilst both models show similar trends – waste, low-grade, and high-grade regions are the same in both cases – the simulation model can provide greater insight for optimal definition of the mineralisation boundary.CITATION:Haylett, M E, Weeks, A, Matthews, G D and Khosrowshahi, S, 2014. Ore block design in narrow vein gold deposits – estimate or simulate?, in Proceedings Ninth International Mining Geology Conference 2014 , pp 421–424 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J P. Sykes, T C. McCuaig, J E. Vann

Resources added to the global metal inventory through exploration over the past 15 years have been generally of poor quality (declining grades, recoveries and lack of acceptable financial return). Similarly, companies opting for an acquisitions-based strategy have had to pick from a group of poorer quality resources left from previous exploration booms, and will struggle to deliver this metal to market economically. Increasing difficulty in obtaining sufficient social and community acceptance of mining projects and potentially an energy-constrained future may exacerbate this problem, redefining what is considered ‘ore’. There will need to be more focus on deposit quality, defined as sustainable margin in the future business environment.Traditionally there has been a lack of translation of ‘mineralisation quality’ back to mineral project design and mineral exploration. This disconnect is due to two main factors: the first is technical – inherent deposit variability; and the second is organisational and socio-psychological –the mindset of explorers and project managers themselves.There are four elements to value realisation for a mineral deposit: (1) social licence to operate; (2) geological factors (depth, geometry, water and geotechnical, and geometallurgy – influenced by texture, mineralogy, chemistry and grades); (3) financial engineering (capex, opex, future commodity prices, future energy prices), and (4) operating factors (production rate, recovery, energy consumption). These elements are strongly interdependent, and geology underpins and drives linkages between them. A quality deposit addresses all of these elements and thus can be developed in a time frame that allows acceptable returns to the owners of the invested capital.Geological drivers of the above elements can be measured and mapped throughout a deposit. Moreover, when viewed in the context of mineral systems, a predictive understanding of the common causative processes of quality (despite deposit-scale variability) is emerging, and with it the ability to target quality of mineralisation, not just quantity of mineralisation.The second factor is a ‘heuristic software problem’. Current lines of education (and consequently organisational and professional structures) are discipline-based, producing ‘silos’ that do not speak each other’s language and work with different ‘mental models’. People who effectively recognise systemic links between these silos are called ‘boundary spanners’, of which we propose two distinct types: outside-insiders and inside-outsiders. Outside-insiders are people who are within a community, but recognise advances in outside fields and effectively integrate them into the community. Inside-outsiders start outside of a community, and successfully bring new ideas into it. Common traits in boundary spanners are: they seek exposure to (and embrace) key ideas that are outside of the framework of their own specialisation; they have high mental processing ability (MPA) – the ability to connect systems that are currently not perceived to be connected; and they introduce ideas from outside a field into a new context in a way that re-frames the field.The challenge is to identify and nurture potential boundary spanners that can build critical links, in particular between the (largely geoscientific) mineral exploration mindset and the (largely non-geoscientific) project development mindset. Critical linkages to be built are between mineral system science, targeting science, and whole of value chain modelling.CITATION:McCuaig, T C, Vann, J E and Sykes, J P, 2014. Mines versus mineralisation – deposit quality, mineral exploration strategy and the role of ‘boundary spanners’, in Proceedings Ninth International Mining Geology Conference 2014 , pp 33–42 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By P F. Hodkiewicz, J de Lacey, M Stewart, R Lane

"Implicit modelling is an approach to spatial modelling in which the distribution of a target variable is described by a unique mathematical function that is derived directly from the underlying data and high-level parametric controls specified by the user. This modelling approach may be applied to discrete variables such as lithology (after converting the discrete codes to numeric values) or to continuous variables such as geochemical grades. This paper discusses the estimation of continuous (grade) variables using implicit modelling.One of the underlying engines of implicit modelling for producing this mathematical function description is the radial basis function (RBF). In essence, the RBF is a weighted sum of functions positioned on each data point. A system of linear equations is solved to derive weights and the coefficients of any underlying drift model coefficients. Once derived, the RBF may be solved for any unsampled point or averaged over any volume to provide an estimate of grade. It is possible, for example, to query the RBF on a regular grid to derive an estimate of block grades. Given the ease of creation of an RBF, and its ability to predict grade, the question arises as to how the grades derived from the solution of an RBF compare with grade estimates derived from conventional geostatistical interpolation methods (eg ordinary kriging (OK)).The purpose of this paper is to describe in lay terms: the basic structure of an RBF the role of parametric choice in the solution of RBFs and how this influences the character of the solution the fundamental similarities and differences between RBFs and conventional geostatistical estimators.Using a high-resolution conditional simulation, we show that in many situations RBF and OK estimates are very similar.CITATION:Stewart, M, de Lacey, J, Hodkiewicz, P F and Lane, R, 2014. Grade estimation from radial basis functions – how does it compare with conventional geostatistical estimation?, in Proceedings Ninth International Mining Geology Conference 2014 , pp 129–140 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By K Ehrig, C Lower, V Liebezeit, M Smith, E Macmillan

"Minerals, minerals, minerals. Elements occur in the earth as minerals. If local physical, chemical and structural conditions are conducive to concentrating these minerals to sufficiently high abundances in the earth’s crust, a mineral deposit will form. If technology is available to extract metals from the minerals economically, then you have a mineral resource that will be mined and processed. Determining which minerals are present and quantifying their abundances, textural characteristics (grain size and shape) and how they are intergrown with each other is the realm of the mineralogist. Geologists use this mineralogical data to understand how the mineral deposit formed, how to find high-grade zones within the deposit and where to find other mineral deposits. Metallurgists use this data to design, operate and optimise processing facilities to extract metals from the minerals. The types, quantity and precision/resolution of the mineralogical data required by geologists and metallurgists are different, but are not mutually exclusive of each other. Fortunately, measurement technology is available that is relatively rapid, high volume and low cost, thus enabling ore and gangue mineral characterisation at a historically unprecedented scale of a mineral resource.CITATION:Ehrig, K, Liebezeit, V, Smith, M, Macmillan, E and Lower, C, 2014. Geologists and the value chain – how material characterisation by modern mineralogy can optimise design and operation of processing facilities, in Proceedings Ninth International Mining Geology Conference 2014, pp 5–14 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By R Hargreaves, C Morley

The authors often see problems on mine sites that are due to insufficient feedback between technical discipline silos as the realities on the ground fail to inform the models and plans used to drive resource exploitation. Resource modelling, reserve definition, life-of-mine planning, short-term mine planning and scheduling, mine operations and beneficiation operations are all processes that inform each other, but in many instances feedback between these processes occurs in an ad hoc way and only after problems have come to light.Universal reconciliation uses a multidisciplinary approach across the entire mining value chain to identify both opportunity and loss of value and to maximise operational performance. This paper will look at the operational effectiveness of universal reconciliation and will outline the important elements that make it successful, including how to map out the detail underpinning modelling, planning and execution processes. We do this by documenting the physical processes, logical work practices, organisational roles and responsibilities, data origin and quality, working assumptions and information management practices at an operation. The results quickly show how misinformation and assumption causes suboptimal decisions to be taken, where inefficiencies exist and what the opportunity is to remedy these issues.A universal reconciliation study opens up an opportunity for stakeholders to reassess how the operation should be run and how operational effectiveness should be measured. Clear envelopes for reconciliation become obvious and questions about the practicality and data quality can be addressed.A reconciliation code of practice is a key element of a successful universal reconciliation project and the authors outline the important aspects that will provide an operating model, showing the effectiveness of the resource and reserve modelling, the practicality of the mine planning and scheduling practices, how well the mine operations team are executing these schedules and how effective the processing area is given what it is fed. Most importantly, a system that allows operations time to react before the losses become systemic and that is based on identifying early warnings from hard data when these processes start to wobble is outlined. Finally as a case study, the revenue and cost benefits resulting from universal reconciliation diagnostic projects for nine mine sites is documented.CITATION:Hargreaves, R and Morley, C, 2014. Universal reconciliation – a multidisciplinary approach across the entire mining value chain to identify loss of value and maximise operational performance, in Proceedings Ninth International Mining Geology Conference 2014 , pp 411–420 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By T Goldsmith

The mining industry is cyclical, but those are more than normal business cycles. In the early 2000s the industry saw the start of China as a game changer for the mining industry which lead to catch phrases like ‘stronger for longer’ and even ‘stronger forever’. Enter the global financial crises and the more recent slow-down in the Chinese economy and confidence that the future is bright has dimmed! This paper looks at the long-term forces that are likely to impact the global mining sector and explain why the industry has an excellent future. However, the industry is not without its many challenges and while demand may be in a prolonged step change, the ability to generate profits will depend on the fitness of each asset and company.The author also discusses the hated terms of ‘boom’ and ‘bust’ and considers how the industry can reduce them, but normally exacerbates them. The ability of the junior sector to raise funds being a primary example and one that remains closed to all but the very best exploration assets. There is also consideration of Australia’s position as a mining country in the future world.CITATION:Goldsmith, T, 2014. The future of the global mining sector, in Proceedings Ninth International Mining Geology Conference 2014 , pp 15–20 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By M Creech

During the 1990s, wider and more productive longwall panels were being introduced into the Newcastle Coalfield. The strata of the Newcastle Coalfield incorporate numerous massive sandstones and conglomerates, some of which formed the immediate roof of the coal seams being mined. The unexpected implications of introducing wider panels into this geological environment included more variable and increased subsidence, severe periodic weighting (with associated mid-face falls) as well as windblast.Subsidence prediction at the time was based on empirically derived data essentially relating subsidence to the width/depth ratio of the panel without accounting for actual widths, nor the impacts of variable geology. This approach required modification as locally derived data was gathered and reinterpreted.The interaction of massive strata located close to the roof of the mined seam resulted in dramatic implications for some of the operations. When associated with longwall goaf geomechanics severe periodic weighting events and crippling mid-face roof falls were the consequence. When associated with narrower panels and shortwall goaf geomechanics, mines in the region experienced aggressive windblast events. The relationships between the overlying massive strata, longwall panel geometry and the various risks encountered during this period is in the author’s opinion, the most concise still documented.As the extensive coalfields of Queensland turn to underground mining operations the relevance of these experiences cannot be underestimated. This paper will discuss recent developments as well as incorporating diverse subjects such as microseismic monitoring, low frequency radio emissions and ‘electrophonics’ as they relate also to the topic.Like Moriarty, massive strata can be disguised and can offend when you least expect. This paper documents a trail of crimes committed by conglomerate in the Newcastle Coalfield that were inflicted on the general public, miners and mining equipment. Although this paper concentrates on the criminal behaviour of conglomerate, this story is also relevant to other massive units such as coarse sandstones that may be more difficult to identify and apprehend. Currently Moriarty remains at large and able to reoffend at any time, once again taking advantage of the unwary.CITATION:Creech, M, 2014. Moriarty was a conglomerate – experiences and implications of coal mining under massive strata in the Newcastle Coalfield, in Proceedings Ninth International Mining Geology Conference 2014 , pp 47–54 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By S Coward, S Jackson, S Moayer, J E. Vann

The variability and uncertainty of mineralisation, coupled with subsequent uncertainty in mining and processing, is often paid scant regard or overlooked during the evaluation of mining projects. In many instances, when the project transitions to the operational phase, the reality of feed or product variability and the consequences of unquantified uncertainties throughout the value chain become obvious. The outcome is the familiar picture of frequent ramp-up underperformance and failure to deliver on planned targets and objectives.Both mine and exploration geologists are expected to generate mineral deposit models that are based on an integration of diverse sources of data. These multifaceted deposit models already play a pivotal role in the design, development and optimisation of mining project value, and the trend to a fully digitally engineered future means that this importance is increasing. It is therefore vitally important that tools be made available to the geologist (as well as mining engineers and metallurgists) that enable them to characterise and assess variability and uncertainty via appropriate deposit models and thus articulate their impact on potential project configurations and decisions. Scenario-based project evaluation (SBPE) provides a framework for full and proper analysis of the downstream impacts of inherent deposit variability and uncertainty on project performance.SBPE has been developed by the authors over several years and aims to propagate geological uncertainty and variability through the mining value chain. The outcomes of SBPE can be tested against future external scenarios capturing financial, economic and socio-political factors that also drive project performance. Stochastic representations of the orebody (via conditional simulation (see Chilès and Delfiner, 1999)) that explicitly incorporate variability and represent uncertainty are propagated through the value chain on a block-by-block basis (ie on a much more granular basis than traditional project evaluation approaches).Conventionally, metallurgical processes are modelled with deterministic equations (eg regression models) based on limited data. The SBPE approach allows for the modelling of process performance uncertainty using geometallurgical sampling fully. Multiple outcomes of SBPE are passed through financial modelling, which can also incorporate stochastic components, thus allowing full quantification of the risks and opportunities of a set of project alternatives. The value of the SBPE system is that once a base case has been established, multiple engineered alternatives coupled with external scenarios are easily evaluated and compared in terms of incremental value.A new case study of SBPE is presented that shows how, by analysis of the various aspects of variability and uncertainty, project managers are able to focus on the areas that have the greatest ability to reduce risk and/or add significant value. This can lead to sufficient flexibility being built into operations that allow operators to cope with the real orebody delivered to the plant.CITATION:Jackson, S, Vann, J E, Coward, S and Moayer, S, 2014. Scenario-based project evaluation – full mineral value chain stochastic simulation to evaluate development and operational alternatives, in Proceedings Ninth International Mining Geology Conference 2014 , pp 21–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By T Berryman, C Adams, L Griesel, C Buxton

The Kalgoorlie Consolidated Gold Mines (KCGM) schedule model is used for short- to medium-term planning and scheduling at the Fimiston Open Pit Mine (the Superpit). The model bridges the gap between grade control models, which are generated one to seven days prior to mining, and the annual Resource and Reserve model update that is used for budget and life-of-mine plans. The schedule model uses close-spaced grade control data (up to 20 000 m drilled each month) as well as resource definition drilling to estimate production volumes three to six months ahead of current mining. From this, a rolling 12 week mining and processing schedule is generated on a monthly basis. As the KCGM operation is mill and sulfur constrained, the schedule model needs to be an accurate predictor of ounces as well as tonnes, gold and sulfur grades. The process must also be time efficient in order to meet monthly planning and reporting deadlines. Due to the large amount of new data generated each month, model updates using conventional interpretation and estimation techniques have proven to be impractical and too time consuming. This paper will examine the evolution of the Superpit schedule model process over time, recent improvements and the effect of different model outcomes on short- and medium-term mine planning.CITATION:Griesel, L, Buxton, C, Adams, C and Berryman, T, 2014. The superpit schedule model – A time-efficient data-driven estimation for short- and medium-term planning, in Proceedings Ninth International Mining Geology Conference 2014 , pp 397–410 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014