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By R M. Arellano, D M. W Harney, M Makhuvha

Mineral resource and ore reserve estimates are founded on two sources of data: tonnage and grade. The tonnage is a product of volume and density; both of which are estimates. Density impacts numerous operational factors, which include, but are not limited to, mine design, mine planning, equipment selection and operational performance. Hence, density is a significant parameter and its determination requires similar care as the measurement of grade. Selecting an appropriate method to determine density, and ensuring its rigorous application, thus reduces risk and can improve operational performance, which in turn increases profit margin.Different Anglo American sites use a variety of practices and protocols to determine density, which is highly dependent on the physical characteristics of the orebody, local conditions and historical practices. Also, individual sites sometimes execute the same method in a slightly different way, which may also affect the outcome of the measurements. In order to gain a better understanding of how density is determined at Anglo American projects and operations, a review of these techniques was undertaken. The objective of the study was to identify and share good practices across the company, as well as to look for improvement opportunities, where applicable. Ten different methods of measuring density, applied to nine different commodities, were identified and described. An additional technique was recently developed by Anglo American Technical Solutions. The core pycnometer is a large gas displacement pycnometer capable of measuring density at high accuracy on full pieces of intact core.This paper provides an overview of methods used to determine density within the Anglo American Group, including quality control and quality assurance aspects. It is not the purpose of this paper to identify a preferred method, but to highlight the importance of choosing the best suited practice for a project or mine site. In addition, a case study comparing two different density determination methods applied to the same rock samples from the Los Bronces Copper mine was undertaken and the results of that study are presented here.Selecting the most appropriate method to determine density and comparing results from two or more techniques against each other, together with other suitable quality control procedures, is considered to be of utmost importance for all mining operations and exploration projects.CITATION:Makhuvha, M, Arellano, R M and Harney, D M W, 2014. Determination of bulk density in Anglo American plc, methods and impacts, with a case study from Los Bronces Mine, in Proceedings Ninth International Mining Geology Conference 2014 , pp 85–96 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By A J. Cornah

"The mine geologist’s role in classifying ore from waste during grade control represents a critical link in the mining value chain. Any improvement in the ore/waste selection success rate (thus reduction in misclassification) which can be delivered by the mine geologist represents a value proposition. Improvement achieved without additional operating cost (for example extra drilling and sampling) will directly and immediately add value to the mining operation and therefore clearly must be pursued. Such improvement may be leveraged from existing resource drilling data which are typically less numerous but better quality than the grade control data. They are usually excluded from grade control estimates (termed the ‘base case’ approach here) because of the differences in quality.Various specialised geostatistical tools are available to account for differences in precision and accuracy between data sources during spatial estimation. This paper uses a conditional simulation (CS) case study to assess the benefit of integrating resource data into grade control estimates through ordinary kriging (OK) of pooled data sets, cokriging (CK), and ordinary kriging with variance of measurement error (OKVME) when the grade control data are:unbiased but increasingly imprecisebiased and increasingly imprecise. The premise assumed is that the resource data are unbiased and precise.The paper demonstrates that, if appropriately handled, resource data may be used to improve grade control estimates and thus improve ore/waste selection success without additional operating cost. Where grade control data are imprecise but unbiased it is recommended to integrate resource data using OKVME. This re-appropriates kriging weights from less precise to more precise data locations and improves the grade control estimation precision compared to the base case; it consequently provides an improvement in the grade control selection success rate. If grade control data are associated with significant bias, integration through CK is recommended as the biased data are zero sum weighted. CK consequently provides an unbiased estimate with some improvement in estimation precision compared to the base case and consequently improvement in the ore/waste selection success rate.CITATION:Cornah, A J, 2014. Incremental improvement of grade control models using resource data, in Proceedings Ninth International Mining Geology Conference 2014 , pp 387–396 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By M Zengerer

The Basil Cu/Co deposit comprises a 26.5 Mt Inferred Resource of copper and cobalt, grading 0.57?per cent Cu and 0.05 per cent Co. It lies in the Harts Range, Central Australia, within the Riddock Amphibolite of the Irindina Province. Analysis of drilling within the mineralised zone of the deposit determined a spatial association between pyrrhotite with high magnetic susceptibility and chalcopyrite, following a strong magnetic trend as determined from airborne geophysics. A study was commissioned to examine if geophysical inversion could predict the distribution of sulfide mineralisation based on pyrrhotite from drill hole intersections, as well as predicting further mineralisation at depth or in the vicinity of the deposit. Petrophysical and geostatistical analysis of drilling susceptibility and mineralisation provided a basis of property distribution inside the model. This was followed by 3D geological modelling of mineralisation based on domain kriging of drill hole susceptibility sensitivity testing of signal to source depth, and distribution was performed using 3D forward modelling. Stochastic inversion generated alternative 3D geological models, which were tested for behaviour and adherence to observed drilling data and geostatistical limitations using GeoModeller software. Predicted mineralisation distribution was compared with conventional geostatistical modelling and found to be in agreement in planar behaviour but exhibiting possibly isoclinally folded trends, with reliability increasing closer to the surface. Predictions of mineralisation at greater depth and beneath weaker anomalies were more diffuse due to small model cell size having limited influence on the signal at depth.The Blackbush uranium deposit comprises a 64.5 Mt Inferred Resource, grading 230 ppm U in the Pirie Basin south of Whyalla, South Australia. It directly overlies the radiogenic Samphire Granite and is considered a tertiary unconformity deposit. Sensitivity modelling was performed using high-resolution ground gravity to see if a deposit signature could be detected using gravity. This required 3D implicit modelling of the geology and mineralisation from drill hole data and characterisation of an associated physical property model using domain kriging in GeoModeller. Density models relied on exploiting an observed relationship between logged density and measured uranium oxide percentage. The residual gravity response of the background geology model identified the location of the uranium deposit. Stochastic inversion of the litho/property 3D model has refined the known distribution of uranium from drilling and provided structural insights into the deposit.These projects have become excellent case studies for exploiting the relationship between mineralisation and potential fields and for testing the applicability of using domain kriging of properties determined from drilling to build robust 3D geological models for stochastic geophysical inversion, leading to robust methods for exploration targeting and mineral deposit prediction.CITATION:Zengerer, M, 2014. Use of geostatistically-constrained potential field inversion and downhole drilling to predict distribution of sulfide and uranium mineralisation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 281–290 (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 H Stedman

Integrating exploration and operational blastholes into one database significantly enhances geological modelling. Benefits include: improved coal predictions, stronger interpretation of structurally complex areas, detailed mapping of heat affected coal aureoles and additional roof accuracy for blast designs that deliver better coal protection.CITATION:Stedman, H, 2014. Integrating blastholes into exploration data to improve coal recovery and modelling, in Proceedings Ninth International Mining Geology Conference 2014 , pp 237–242 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By M K. Kapo, S C. Nzama

The success of a mining operation depends on the quality of data used in decision-making processes and the people involved in making operational decisions. At Olympic Dam, mine geologists form an integral part of the teams that make decisions at various key points in the mine operational value chain. Mine geologists are directly and indirectly involved in all stages of the mining process, namely, orebody definition and categorisation, mine design and planning, metallurgical processing, and reconciliation.Due to the sheer size and complexity of the Olympic Dam deposit, each mining stage has been divided into smaller units within which decisions are made in line with the overall mine operational plan. In each of these units, the decisions and inputs made by mine geologists has ensured that consideration of geological factors is made in the mining process. Over time, the mine geology team has demonstrated a systematic approach in the development and improvement of their processes in line with the mine’s operational needs, such as understanding the in-stope ore variability and maintaining a consistent ore feed to the plant. An understanding and interpretation of the mineralisation distribution, based on acquired data, has proven to be important in the definition of resource modelling parameters. These parameters in turn affect the quality of grade estimates and their downstream use in planning, production and subsequent reconciliation processes. The continual study of the geology of the deposit, and unravelling its complexity through research has been crucial to the metals extraction process. The involvement of mine geologists through each of the mine value processes places Olympic Dam in a favourable position to benefit from future opportunities that will take advantage of the increasing operational demands and production pressures, and the ever changing economic conditions.This paper reviews the role mine geologists play in the realisation of the Olympic Dam deposit, from ore to product, through their interaction and collaboration with other departments and stakeholders. This paper also highlights mining practices employed at the Olympic Dam mine.CITATION:Nzama, S C and Kapo, M K, 2014. Managing the giant – a mine geologist’s perspective to the mining of the Olympic Dam deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 451–460 (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 R H. Knight

Uncertainty in prediction and modelling of geological (physical) ore continuity in geometrically complex ore deposits is a key risk factor in mining. Reducing geometric uncertainty of hard-boundary ore/waste contacts and related geological features improves the efficiency of local mineral resource estimation and reserve calculation, mine/stope planning, ore control and in-mine exploration. Detailed underground mapping of serial-level drives provides a continuous record of the characteristics and contact configuration of ore, as well as crucial ore-related geological features that are required to resolve geometrical variability when closely spaced drilling proves inadequate or is cost-prohibitive. The mapping-based approach described in this paper re-establishes the focus on the geology of the orebody by incorporating high-value, detailed geologic mine mapping information. Mapped ore-related configurations and relationships, recorded on a succession of faces or on a series of levels, provide the basis for 3D interpolation and extrapolation of the local geologic continuity of an orebody. Correlative points representing locations of key ore-related geologic features on each face or level are linked by 3D polylines or trajectories forming a coherent geometrical framework. The coherent progression of geometric changes mapped by these trajectories reveals the overall ‘dynamic’ of the geometrical framework, as well as the spatial tendencies of its geological constituents. Distinct sets of ore control trajectories are selected from within the framework and are used in the construction of alternative geological ore continuity models. As mining proceeds, alternative models are evaluated, and are then either refined or rejected. The geometrical framework is used to evaluate theoretical models and practical heuristics, focus exploration targeting and inform and guide all aspects of mine geology in active mines. This approach also lends itself to analysis of global ore continuity in the re-evaluation of mature or abandoned mines. Its use is particularly effective in geometrically complex orebodies such as the West Branch orebody and the orebodies of No 2 mine of the Balmat-Edwards-Pierrepont zinc district, which are used to illustrate the method. CITATION:Knight, R H, 2014. A mapping-based approach to geological continuity prediction using examples from the Balmat-Edwards-Pierrepont Zinc District, St Lawrence County, New York, USA, in Proceedings Ninth International Mining Geology Conference 2014 , pp 65–76 (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 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 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 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 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 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