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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 A Melkumyan, M Balamurali

Geological domains describe the mineralisation state and stratigraphic location of different geological regions of mines. They play a very important role at the geological modelling stage as weight percentage of chemical elements information within each geological domain is assumed to be correlated while information coming from different geological domains is considered uncorrelated. Having correct domain assignments to both the chemical assays and the 3D space of modelling is critical for building a reliable geological model of the mine.As standard practice significant effort is invested into the interpretation of the deposit and identification of the geological domains for the chemical assays and the 3D geological space. Despite these efforts, there are some chemical assays with ambiguous geological domain where the exploration assay domain and the block domain do not match. Incorrectly including a sample in the wrong domain can cause a large change in the predicted weight percentage of chemical elements estimation for that block. Therefore, the major challenge of grouping the spatially correlating weight percentage of chemical elements is how to determine which of these domains best fits these misclassified samples.This work proposes machine learning based autonomous technique for identifying to which geological domain (the exploration assay domain or the block domain) the misclassified sample belongs. The proposed methodology is based on Gaussian Process (GP) classification. The GP machine learning approach consists of training and inference stages. At the training stage the GP automatically learns the properties of different geological domains using the chemical assays with unambiguous domain assignment. Then, at the inference stage the GP makes predictions for the geological domains of the assays with ambiguous initial domain assignment.We tested the proposed technique by conducting a case study for an iron ore deposit located in Western Australia. The results demonstrate that the application of the proposed GP technique removes statistically significant deviations in the assay values in many regions: mineralised ore region, unmineralised region, highly weathered region and intrusive material that is highly variable. In this case study the proposed methodology autonomously identified the geological domains for more than 50 per cent of samples which are initially ambiguously classified. For the majority of the assays the GP predicted domain agrees with the geological domain assigned by the exploration assay.CITATION:Balamurali, M and Melkumyan, A, 2014. Automated identification of geological domains for exploration assays with ambiguous initial domain assignment in an iron ore deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 99–106 (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 A Finch, C Pridmore

The Cosmo Project falls within the Archaean to Palaeo-Proterozoic Pine Creek Orogen, one of the major mineral provinces of Australia.The Cosmo Deposit is interpreted to be a series of steep north-west-plunging gold mineralised vein, breccia and shear systems within the tight Howley Anticline and hosted within interbedded siltstones, mudstones, banded iron, phyllites, dolerite sills and greywacke.A folded environment poses a number of technical challenges, particularly for estimation.Handling of tightly folded and in some cases narrow domains might include subdomaining for orientation, omni-directional three-dimensional (3D) estimation within constrained domains or software-enabled unfolding/un-wrinkling procedures (transformation of the data and estimate space into a two-dimensional environment). Each technique has its own unique set of advantages and disadvantages.A further method (one applied at Cosmo) is where the estimation parameters (specifically search and variography orientation) are modified in a frequent or ‘dynamic’ sense to suit the orientation of the domain whilst maintaining 3D space. Control of the resource estimation orientation can be done in several ways, including the use of sectional panels of a specific size or, alternatively, orientation sector divisions. The sector approach provides some significant reductions in processing time over the panel technique and could be applied in a number of software packages.Three-dimensional ‘dynamic’ interpolation reconciles well with production data from Cosmo, whilst the sector method provides a practical technique that can be executed without the complications of transformation or the need for labour-intensive orientation subdomaining and with acceptable resource estimation run time.CITATION:Finch, A and Pridmore, C, 2014. Dynamic interpolation – estimation in a folded environment at the Cosmo Deposit, Northern Territory, Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 107–114 (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 Howe, J Conn, J G. McLellan, K Gates

The Red October Gold Mine, owned by Saracen Gold Mines Pty Ltd, is located approximately 80 km south of Laverton, Western Australia. It is considered to be of a similar nature to many of the Archaean granite-greenstone deposits in the Laverton Tectonic Zone, and presents as an intriguing and relatively young deposit in terms of developed structural and genetic models. Regional deformation events have been proposed for the area, and are relatively well accepted. The most important of these deformation events in the region were the D4b (WNW–ESE sinistral transpression) and D5 (ENE–WSW dextral transpression) which have been attributed to the main Au mineralising phases. At the local scale there appears to have been a rotation of the regional stress field to provide the optimum orientation of maximum principal stress for sinistral movement on the main shear zone.Fully coupled 3D finite element analysis (FEA) was used to simulate the geomechanical response of the system based on structural observations. The geomechanical modelling resulted in highlighting anomalous patterns of stress and strain and subsequent fluid flow as a result of the two main deformation events. The D4 simulation provided a good correlation with the known distribution of subsidiary structures on the main shear zone, and furthermore provided several geomechanical targets that suggested locations of additional subsidiary structures. The D5 simulation provided a great insight into the response of the main shear zone and known subsidiary structures also highlighting additional targets indicating potential for further mineralisation. These targets have since been followed up with a 732 m deep surface reverse circulation (RC) drill hole, resulting in the discovery of two high-grade shoots, with follow up testing currently planned for mid-2014.CITATION:McLellan, J G, Conn, J, Howe, D and Gates, K, 2014. Structural controls and strain partitioning in the Red October Gold Mine, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 315–322 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

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 C Laming, S Staude, D Hammond, S Sheppard, J Griffith, S Stanfield, S Marriott

Long Operations is located on the eastern slope of the Kambalda Dome in Western Australia. Kambalda hosts nickel deposits that are modelled to have formed from an exsolving sulfide melt from a parental komatiite melt. The nickel deposit model predicts a stratigraphical relationship where massive Fe-Ni-Cu-sulfides are deposited in troughs at the base of komatiite channels. The basal contact of the sulfides is generally tholeiitic basalt. The Kambalda geological sequence form a dome structure with a granodioritic core and have undergone tectonic and metamorphic overprinting, resulting in the formation of upper greenschist to lower amphibolite-facies units.On the basalt-ultramafic contact, within the Long Operations, there are two separate channels hosting seven different orebodies. The Moran orebody is the most undisturbed orebody at Long Operations, with many primary magmatic textures preserved, making it ideal for studies to improve the existing nickel sulfide formation model. Detailed exploration and production infill drilling and systematic sampling indicates consistent nickel tenor variations over the entire Moran orebody. This was also observed in other deposits in Western Australia and was explained as metamorphic variations. Similar variations are observed with some trace elements that cannot be explained by metamorphic overprint but with gravitational segregation in the liquid sulfide. Other more complex trace element patterns (eg Cr) require additional explanations and are partly originated from incorporation of underlain basalt and sediment and partly from gravitational segregation.From a mining perspective, the Moran orebody can be used as an example of modern high-speed mining, but at the same time preserving samples for the future and allowing knowledge from the geological context and geochemical signatures to improve future exploration.CITATION:Staude, S, Marriott, S, Griffith, J, Laming, C, Hammond, D, Stanfield, S and Sheppard, S, 2014. Improvement of existing ore-forming models due to systematic sampling during mining – an example from Kambalda, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 341–348 (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