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

Effective domaining is fundamental to geostatistical modelling for grade control. Through analysis of lithological, structural and alteration logging data, effective groupings (domains) can be identified and employed for estimation or simulation purposes.The poor definition of domains can adversely affect the grade control model resulting in a misinterpretation of the optimal ore-waste boundary and ultimately reduces the quality of recovered ore. The implementation of an appropriate domaining strategy is therefore expected to improve recovery and reconciliation.A thorough understanding of the geology of the deposit and adequate sample data is required for selecting domains. For new deposits, a resource drill database and resource model may be the only information available. Where extension to a previous operation is taking place, historic grade control, mapping and exposed geology may be used to improve domain selection. Preconceptions about domains, should they exist, need to be re-evaluated and tested to ensure they are fit for the purposes of grade control.While mining progresses, the domain model is re-evaluated to ensure that the previous interpretation is still suitable for the present configuration and geology. The grade control process, being iterative, lends itself to regular review and continuous improvement as further data is collected during the grade control cycle. Regular updates to the geology model, mapping, geostatistical data analysis and review of variography will provide indications of a changing domaining environment.Narrow vein gold deposits, which may have several factors influencing mineralisation, present considerable domaining challenges. By scrutinising the data, sample populations can be grouped into domains, which not only improve ore recovery, but help assist in the development of a mine geology model.CITATION:Matthews, G D, Haylett, M E, Weeks, A and Khosrowshahi, S, 2014. Effective domain selection for grade control in narrow vein gold deposits, in Proceedings Ninth International Mining Geology Conference 2014 , pp 191–196 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Loeb, D Thornton

Blast movement measurement is a key component of grade control, enabling mines to carry all of the precision involved in locating ore blocks, through a chaotic blast, to production. A monitoring system was developed about ten years ago so that mine operation personnel can measure three dimensional movement in every production blast. Research has shown that blast movement is always highly variable with a significant non-deterministic component. The consequence is that modelling will be inaccurate and therefore optimal ore recovery can only be achieved by direct measurement of blast movement.Three dimensional movement vectors are measured at discrete locations in the blast. If blast movement is only measured at one location in a blast pattern, data is severely limited and has all of the inherent inaccuracies of modelling a variable population. It is intuitive that the accuracy of defining the post-blast ore block mark-ups are proportional to the number of movement measurement locations, however increasing the number of monitoring locations causes increases to the direct operating costs of the mine.A cost-benefit analysis is used to explore the optimal number of monitoring locations. Using the method described in this paper, an automated selection of the number and location of blast movement monitors are analysed against the value of recovered ore compared to the control, for each trial.CITATION:Loeb, J and Thornton, D, 2014. A cost benefit analysis to explore the optimal number of blast movement monitoring locations, in Proceedings Ninth International Mining Geology Conference 2014 , pp 441–450 (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 M G. Millad, M Zammit

The Kipoi Central (KPC) copper project is located in the Katanga Province in the Democratic Republic of the Congo and is presented here as an example of an operating mine where the Mineral Resource was initially estimated by uniform conditioning (UC) and subsequently updated to localised uniform conditioning (LUC). This paper discusses the implementation of an estimate run using LUC and compares the results based on resource definition drilling to those obtained by close spaced grade control drilling and actual mill production.UC is a nonlinear geostatistical technique designed for recoverable resource estimation, typically using wide spaced exploration and resource definition drilling. The primary output of UC is the grade, tonnage and metal above a series of user-defined cut-off grades for a particular selective mining unit (SMU) block size. The UC approach is considered to provide a more accurate representation of the recoverable grade and tonnage at SMU support for non-zero grade cut-offs than would typically be achieved by a traditional linear estimator such as Ordinary Kriging. LUC is a relatively new approach involving the post-processing of a UC estimate and is used to spatially present the grade distribution predicted by UC at the SMU scale.This study demonstrates that the calculation of a more accurate and realistic grade-tonnage relationship for small SMU sized blocks is possible at the exploration stage using LUC, provided that the necessary theoretical and practical conditions for implementation of this technique exist.CITATION:Millad, M G and Zammit, M, 2014. Implementation of localised uniform conditioning for recoverable resource estimation at the Kipoi Copper Project, Democratic Republic of the Congo, in Proceedings Ninth International Mining Geology Conference 2014 , pp 207–214 (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 J Paradis, K Dudgeon, M Topping

At Newmont’s Jundee Operation, exploration and resource geologists collaborated to produce an open pit resource model. Using a variety of modelling and estimation techniques but no new data, an uneconomic underground target was converted into a potentially economic open pit evaluation. During an industry downturn, it is more important than ever to efficiently share expertise, ideas and resources to problem solve and produce meaningful project outcomes. The two departments brought together different methods and ideas, and the process showed that certain methods worked better than others in different situations, thus the appropriate method was applied to each part of the evaluation. The results were used to create new procedures and improved lithology modelling and resource model estimations. Adaptability of the geology departments and collaboration such as this are key to ongoing improvements and future mine life at Jundee.CITATION:Dudgeon, K, Paradis, J and Topping, M, 2014. Cook open pit model – the hurdles: how we leapt, lunged, stumbled and overcame them, in Proceedings Ninth International Mining Geology Conference 2014 , pp 169–174 (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 G Love, S Maher

In Victoria’s onshore Gippsland Basin, geology is driving brown coal developments, and geologists are key decision-makers. Prompted by volatile energy prices and the likelihood of a carbon constrained future, significant work has been carried out on the next generation of technologies to be applied to this giant resource. These include new-generation gasification technologies, coal conversion processes yielding products as diverse as diesel and fertiliser, drying technologies producing thermal and metallurgical coals and in situ conversion processes. However, coals aren’t coals, and brown coal available for new projects will have different quality parameters and mining economics from that currently mined.New projects are likely to be developed on coals with moisture contents averaging 60 per cent and corresponding low energy values. Whilst ash values will be low, averaging just 5 per cent (dry basis), this will at times approach 10 per cent, which is a level that would challenge the installed-generation technologies. Sulfur values will average 0.4 per cent (dry basis), but at times exceed 0.6 per cent, requiring technologies that address the potential for sulfur dioxide emissions. Whilst localised high levels of the fluxes iron (>1 per cent dry basis) and sodium (>0.3 per cent dry basis) would increase fouling of installed technologies, they may be suitable for selected next-generation technologies.Project viability for this next generation of technologies will be strongly influenced by mining cost, and geologists are playing a role in identifying higher-value coal. At its simplest, this is being achieved for open cut mines through regional, vertical strip ratio assessments, which are considered a first-order proxy for mining cost. Follow up assessments are incorporating mining and processing cost, coal quality penalties and product revenues. At a regional scale, it is informing the likely location and relative timing of future mine developments, as well as thinking around rehabilitation strategies, infrastructure and land-use planning.For deeper coal, factors like macro permeability, the ability to isolate seams from aquifers, groundwater chemistry, pressure temperature conditions, connection with groundwater recharge and in situ biota are being used as vectors to in situ coal conversion opportunities.Matching coal to the next generation of technologies has benefited from regional-scale geological studies of coal quality and mining economics, and has benefited from early engagement between geologists, technology developers and project proponents.CITATION:Maher, S and Love, G, 2014. Matching brown coal to the next generation of Latrobe Valley projects, in Proceedings Ninth International Mining Geology Conference 2014 , pp 77–84 (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 L W. Palmer

"Evaluating the geological risk associated with ore deposits is becoming common practice in the mining industry. While geostatistical simulation is a useful tool for evaluating this risk, the effect of applying different types of simulation is less understood. For simulation of categorical variables like rock types, available methods perform simulation in fundamentally different ways. In this study, the geological risk relevant for informed mine planning is studied with two categorical simulation methods, PluriGaussian Simulation (PGS) and Sequential Indicator Simulation (SIS). Risk is expressed as a probability of repeated occurrence of lithological units in the same location across simulations. Significant differences are observed between the methods in terms of spatial distribution of risk. To identify the most plausible risk model, the input parameters at every step of both techniques are scrutinised. PGS and SIS inputs are classified as four parameters that are: fundamental to implementation of the methodfixed to enable comparison of PGS and SISdetermined by user interpretation, hence variablenormally optimised during application of PGS and SIS. The effect of parameter selection from categories 1 and 4 on the risk model is investigated using drill core data from a leucogranite deposit. A corresponding block model is created for assigning outputs from PGS and SIS. Risk models produced by either method are illustrated in a cut-out from the block model to enable bench-by-bench comparison. For PGS, risk associated with relatively rare lithologies is relatively sensitive to variation of parameters. Independent of the abundance of lithology, a location-dependent effect of variogram and vertical proportion curve parameter selection is observed, with risk increasing towards the deposit edge. Although SIS requires fewer inputs, single lithologies must be modelled in turn. Using small numbers of samples in the search neighbourhood, all risk models differ substantially. For larger numbers of samples, the risk models are similar. Overall it appears that the risk model produced using SIS is less sensitive to changes than PGS but further work is required to confirm this.CITATION:Palmer, L W and Glass, H J, 2014. Risk associated with rock type prediction using simulation techniques, in Proceedings Ninth International Mining Geology Conference 2014 , pp 217–228 (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

By J Taylor, A Dubowik

To increase the efficiency and improve the quality of diamond drilling at Olympic Dam, mine geologists have adapted and modified common practices in order to overcome the challenges imposed by such a unique environment. Mine geologists have to take into account both the complex geology during the diamond drill hole design phase, as well as incorporating diamond drilling into the larger-scale scheduling process already employed at Olympic Dam. This study seeks to explore how such modifications have evolved over time.The geology of Olympic Dam influences the design process of diamond drill holes, particularly due to the variation of lithology and alteration, as well as the presence of magnetite and major structures within the orebody. Exclusion zones are used to manage interactions with existing and planned mining activities, and their size is dependent upon the geology of the area. Specific deviation checks are used to monitor the deviation of diamond drill holes with respect to these?zones.The highly interactive environment of Olympic Dam requires unique planning for diamond drilling, resulting in the production and implementation of both long- and short-term schedules. Long-term schedules are targeted at determining drilling locations and ensuring drilling is completed prior to stope planning, while short-term schedules aid in enabling access to ensure timely set-up of drill sites. Estimated drilling rates, determined by expected lithologies and historical data, feed into the short-term schedule to assist in managing the operation and minimising the downtime of diamond drill rigs. A mine geologist is appointed as a diamond drill coordinator to organise and manage diamond drilling at a scheduling and operational level, streamlining the entire process.Analysis of historical data shows a strong correlation between implementation of the aforementioned practices and improved drilling rates. This study shows the importance of adapting universal tasks to particular environments and circumstances. Mine geologists at Olympic Dam continue to acquire knowledge to further improve the modified drilling practices as operational requirements, production pressures and economic factors change.CITATION:Taylor, J and Dubowik, A, 2014. The evolution of diamond drilling practices at Olympic Dam, in Proceedings Ninth International Mining Geology Conference 2014 , pp 271–280 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Channell, G Phillips

"The Chesney deposit, located 4 km south-east of Cobar consists of three copper-gold rich shoots that lie within a larger, copper dominant lode. A fourth gold rich shoot is located adjacent to the main deposit. The deposit exhibits a strong structural control on mineralisation, as brittle deformation during subvertical extension provided the requisite structural traps to precipitate sulfides from solution. It is postulated that the Great Chesney Fault acted as a fluid conduit, conveying fluids to the site of orebody formation. The continual supply of fluids resulted in cyclic brittle deformation when the fluid pressure exceeded the lithostatic pressure and the tensile strength of the Great Cobar Slate.Evidence supports the hypothesis that ore deposit formation was controlled by: a supply of mineralised fluids transported along the Great Chesney Faulta suitable location for the mineralised fluids to accumulate, accommodated by vertical extension and dilation in certain locationsthe creation of suitable structural traps to capture the sulfides. These traps formed as a result of fault-valve behaviour. Understanding the controls on mineralisation enables prediction of the location of other deposits with similar emplacement history, or extensions of current deposits.CITATION:Channell, J and Phillips, G, 2014. Understanding mineralisation controls – a case study of the Chesney deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 301–312 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By G Fahey, S Rose

"Mining geology as a defined profession is only about 100 years old. The successful modern mine geologist needs to be a multidisciplinarian, but also needs to maintain a focus on the key outputs of the role. The technical skills needed in the role have increased as mining methods move to increasingly mechanised techniques. As well as being the guardian of the orebody and ensuring minimal dilution to expected ore grades, the mine geologist should be competent in the 12-point mine geology process. The mine geology process should include:a statement of purpose (a ‘mission statement’)geological mapping/logging system that supports consistent and regular geological data collection, storage, and interpretationsampling system that can produce representative samples and fits in with the mining scheduleassay database with relevant controls to ensure only ‘clean’ data is loadedsimple quality assurance / quality control (QA/QC) system for samples and assays, with a response process to react to out of specification resultsconsistent method of exporting, visualising, processing and interpreting assay data to create mining blocksdevelopment sign-off system so that all development and stoping is controlledproduction tracking system to monitoring and reporting what ore and waste volumes have been moved from the face, to any intermediate stockpiles, the run-of-mine (ROM) pad and into the crusherreporting system for daily, weekly and monthly reporting of tonnes and gradesdocumentation so that the grade control system has simple, but effective descriptions of how it works, who has responsibilities, and authorities, and be easily maintainedreconciliation system to compare resource and reserve to grade control and to mined and milledtraining system so that the geology team can quickly become competent.In this paper, the authors discuss the requirements of each point, and comment on common shortfalls observed by them over several years’ experience on producing mines worldwide.CITATION:Rose, S and Fahey, G, 2014. Modern mining geology, in Proceedings Ninth International Mining Geology Conference 2014 , pp 461–466 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By R Sterk, B Reid

The Konongo Gold Project is located on the western margin of the 125 Moz Ashanti Gold Belt in Ghana, West Africa. It is situated 60 km along strike of the world-class mineral system at Obuasi and is interpreted to lie on the same controlling regional shear system.The project is operated by Signature Metals, a subsidiary of the Liongold Corporation, and is managed and funded by the Liongold Corporation.Historic underground operations at Konongo produced 1.6 Moz Au at a head grade of 11.8 g/t Au, from eight operations spread along 16 km of the shear system. Mining focused almost exclusively on free-milling gold in quartz, ignoring the gold-bearing sulfide mineralisation associated with the quartz veins. Underground mining ceased in 1986.In 2013, Signature Metals re-focused the program at Konongo to assess the viability of mining the sulfide ore sustainably. This led to the first campaign review of the historic underground data and resource potential since mine closure. The Obenemase mine was the first of the eight operations to be assessed as part of this campaign.Large amounts of legacy data have survived for Obenemase and several historic resource estimations have been completed based on these data. The data typically consisted of hand-drawn sections and plans, and ledgers of commonly incomplete drilling and sampling data. Some drill core have been lost over time, but a large amount of quarter-core and half-core as well as pulps and rejects are still available. Previous resource estimates had a low confidence value because all the available assay and geological data were integrated effectively with the estimates, resulting in a lack of understanding of both grade and geological continuity.This project built a new geological model for Obenemase that greatly enhances the understanding of the controls on mineralisation using a thorough approach of re-surveying, re-cataloguing and re-logging. This model led to an increased degree of confidence and a subsequent upgrade of resource classification, and created several previously unrecognised strong exploration targets. The resulting resource estimates increased the value of the project by 100 per cent.This paper emphasises and highlights the importance of a well-understood geological model on the confidence of a resource estimate and how this may directly impact on the project’s ‘bottom line’.CITATION:Sterk, R and Reid, B, 2014. The Konongo Gold Project, Ghana – an example of how geology makes all the difference to a resource estimate, in Proceedings Ninth International Mining Geology Conference 2014 , pp 467–476 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By K H. Esbensen

The Theory of Sampling (TOS) has contributed significantly to chemometrics by allowing data analysts to become more aware of total measurement uncertainty as total sampling error + total analytical error. This has allowed a new view on, for example, validation of multivariate data models and their performance. This keynote focuses mostly on the reverse perspective: how can chemometric multivariate data modelling be of help in an augmented sampling context? The basic principles of multivariate data analysis are presented and application examples are outlined from several areas in the geosciences to facilitate answers to the question posed, including a geochemical multivariate anomaly concept defined by a multivariate background model. Applications from geochemical prospecting, geochemical mapping, environmental chemistry and anthropogenic outlier recognition are outlined, as are the interdependent relationships between geostatistical modelling (variographics) of singular variables versus linear combinations of a multitude of variables, in chemometrics called scores. The potential synergy between chemometrics and TOS is far from exhausted at this time; much work remains.CITATION:Esbensen, K H, 2014. Theory of sampling in a multivariate perspective – what can chemometrics contribute?, in Proceedings Sampling 2014 , pp 7–10 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014