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By Feng Liu

"With seven new applications for plans of work for exploration in the international Seabed Area approved by the Council during its twentieth session of the International Seabed Authority, 26 total approvals have been made by the Council up to date. Among them, three contracts were made with COMRA. On 8 August 2014, China Minmetals Corporation submitted another application to the Authority for approval of a plan of work for exploration for polymetallic nodules in the Area, which is also sponsored by the Government of the People’s Republic of China.China is one of the main contributors to the international seabed regime. The Presentation will describe China’s activities in the Area, such as exploration, technology development, environmental protection and policy making.JIAOLONG is a submersible with capacity of 7000 meters. JIAOLONG’s sea trials were carefully made in 4 years, from 2009 through 2012 and it successfully dove to a depth of 7062m in June 2012 at Mariana trench. A so called "Test Application Phase" started thereafter, and is planned to last for 3-4 years. Two cruises and 4 legs have already been made since then. A wide-range of findings were obtained during dives in South China Sea, and in COMRA’s Exploration Contract Areas for polymetallic nodules and cobalt-rich ferromanganese crusts. This presentation will reveal the colorful findings."

Sep 1, 2014

By T Burns, P Savory

In 2013, Rio Tinto Iron Ore (RTIO) produced 251 Mt from 15 mines in Western Australia. Throughout the mines, Ore Reserve models are used for long-term and medium-term mine planning. Grade control data aids the accuracy of short-term planning. Reconciliation of models with grade control data is important for maintaining confidence in predictions from the models, understanding the limitations of the models, and identifying issues that may require further work.There are a large number of sites and models, with more than 200 professionals involved in different parts of the reconciliation process. Regular meetings of all involved and enabling effective communication are important in the reconciliation process.Reconciliation data is gathered and processed through a web-based system; Grade Block Reconciliation System. This system cuts each grade block against the required model, stores the results, and allows users to view and analyse the data. Development of this system has occurred over a number of years and all Rio Tinto Iron Ore mine geologists and resource geologists now use it as standard to report reconciliation results. The results can be viewed in many ways including by different time periods or benches. Graphing the results assists identification of trends. Centralising and standardising reconciliation has allowed easier comparison between sites. Flexibility in the system allows users to customise reports to manage issues unique to their particular site.In parallel with system development, substantial effort has been put into ensuring mining professionals get together to discuss and understand reconciliation issues. To facilitate this there are now regular sessions, including site visits. Issues are assessed on a case-by-case basis and decisions on how best to address the issues are made by the relevant stakeholders. Reconciliation reports and action plans are revised each quarter.CITATION:Burns, T and Savory, P, 2014. Reconciliation of orebody model predictions – system and people, in Proceedings Ninth International Mining Geology Conference 2014 , pp 367–376 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By F Clark, J T. Carswell

Ore definition for final stope planning is often a challenging prospect in underground (UG) gold mines which exhibit high geological and grade variability. Unlike the grade control (GC) scenario in an open pit (OP), the ability for the mining geologist to plan a sampling campaign which effectively characterises the underlying mineralisation is fraught with difficulty. UG sampling patterns are strongly clustered and typically not dense enough to characterise the spatial and statistical properties. Very commonly, sample volumes are not large enough to provide a reliable grade estimate of the surrounding rock. These factors critically affect our ability to accurately map out ore positions and estimate metal quantities.At Sunrise Dam, traditional UG sampling and modelling techniques have proven to be an unreliable strategy for successful stope planning and extraction. The problem was first observed during the final cut-back in the open pit for which the mineral resource model was constructed from UG diamond drilling. Open Pit grade control reconciliations were strongly positive for both tonnage and grade compared to the resource model. Underground workings missed significant quantities of ore which was laterally defined by open pit reverse circulation (RC) GC drilling. Upon examination it was realised that the cause of the problem was one of inadequate sample density and sample support, the implications of which potentially affected the entire UG mine.As part of a broader study into underground grade control procedures, detailed reconciliation of initial stope production from the GQ domain also pointed to inadequate sampling as a major constraint to effective grade control and reserve conversion.To overcome this deficiency, dense 115 mm wet RC grade control drilling and conditional simulation modelling has been successfully implemented with the intent to replicate the grade control process in the open pit. The increase in sample density and sample volume has proven to be a very effective tool for mapping out highly complex mineralisation. A marked improvement in stope definition, reserve conversion and Mine to Mill reconciliations has been demonstrated on the back of an innovative approach to UG grade control.CITATION:Clark, F and Carswell, J T, 2014. Using reverse circulation drilling to improve sampling in a complex underground gold operation – an innovative approach to underground grade control at the Sunrise Dam Mine, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 143–152 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Coombes

There is much debate on the Competent Persons qualifying criteria for providing classified resource estimates for public reporting. The CRIRSCO family of codes including the JORC Code, SAMREC, PERC and NI43–101, require Competent Persons to have at least five years ‘relevant’ experience and belong to professional bodies. These codes provide further, albeit vague, guidelines to assist individuals with their personal decision to take on the mantle of ‘Competent Person’. There is a risk, however, that these qualifying criteria can result in ill-prepared Competent Persons whose actions and recommendations would undermine their own reputation and that of the organisations that employ them; the integrity of the profession and the principles based reporting systems; as well as the stability of stock markets that rely on these estimates.Based on doctoral study on the development of professional competency within the mining industry, this paper presents an evaluation of the suitability of the current qualifying criteria as well as an analysis of alternative criteria. The research included a series of interviews with industry experts and an online survey of resource geologists. Semi-structured interviews provided a sense of experts’ expectations and interpretation of the current definition of ‘Competent Person’. The comprehensive online survey included a self-assessment, a series of situational questions designed to evaluate responses to typical resource geology scenarios and a set of open-ended questions relating to factors contributing to competency development.A summary of the data analysis, interpretation of the results and a set of recommendations for revised ‘Competent Person’ qualifying criteria are presented. This paper contributes to the conversation on what makes a person suitably qualified to report classified resource estimates and provides practical targets that can be used in the professional development of resource geologists.CITATION:Coombes, J, 2014. Redefining Competent Persons criteria for resource geologists, in Proceedings Ninth International Mining Geology Conference 2014 , pp 153–158 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By K Zunica, A R. Penney

The principles of three-dimensional geological modelling are well understood and routinely used. Sample data is collated and geostatistical tools used to ensure that sample data is suitable for its end use, which is typically a block model that is appropriate for mine planning. What has become increasingly apparent is that physical rock properties and geotechnical parameters need to be incorporated into the three-dimensional geological model to create an integrated mine model.The approach to the collection of geotechnical information is not as highly prescribed and controlled as collection of geological data. Commonly, the geotechnical data set is incomplete and inconsistent, with little consideration of what the end use will be by those collecting the data, or how the geotechnical data might relate to the geological data. In some cases, specific geotechnical investigation programs are completed, yet correlation between those programs and previously collected data is rarely undertaken to the same level of diligence as found in the geology field.There are some obstacles that need to be considered when attempting to incorporate geological parameters, such as grade, lithology, and geological domains with geotechnical information such as rock quality designation (RQD), rock mass rating (RMR), rock strength, and geotechnical domains into the same three-dimensional block model. Interpolation or geostatistical estimation methods used for grade estimates might not be appropriate for many components in rock characterisation, particularly search geometries. A number of examples are provided to illustrate issues underlying some of the data collection procedures, and their effects on three-dimensional geotechnical modelling.The example presented attempts to highlight generally observed shortcomings in the collection of geotechnical information, parameters which need to be considered when combining geological and geotechnical data into the same model, and the benefits of having a combined block model from the beginning of a project.CITATION:Zunica, K and Penney, A R, 2014. Integration of geological and geotechnical data for three-dimensional modelling, in Proceedings Ninth International Mining Geology Conference 2014 , pp 291–298 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J Ireland, S Rose

The main outcomes of mining grade control include defining the boundary between ore and waste and then categorising the ore according to which stockpile it should be sent. A typical workflow includes using general mine planning software (GMP) – such as SurpacTM, VulcanTM or CAE StudioTM – to create three-dimensional wireframes of mineralisation domains, which are used to flag the relevant samples of interest and constrain estimation during block modelling. Creating the wireframes is a time-consuming process, requiring reasonable software skills, patience and an eye for detail. The interpretations can be subjective; indeed, even the same geologist will give different shapes if presented with the same data at different times. The process can become particularly tedious when trying to carry out updates due to new data. It can also be difficult to test the effect of alternative interpretations or grade thresholds because of the time constraints in production.There are now several implicit modelling tools available, either as standalone programs or as add-on modules to existing GMP. In this paper, the authors develop a workflow using implicit modelling methods to show how grades and geology can be rapidly interpreted to provide effective domains for grade estimation. The paper includes case studies from open pit gold mines. The implicit modelling approach can save several days of interpretation work for each grade control drilling campaign.CITATION:Rose, S and Ireland, J, 2014. Implicit modelling applied to grade control data, in Proceedings Ninth International Mining Geology Conference 2014 , pp 115–122 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By O Handayani, R Barr, E Isaaks

The mining industry has focused a great deal of attention recently on the impact of blast movement on grade control. Although the problem of blast movement and its contribution to dilution and ore loss is well known, solutions to the problem are less than satisfactory. Perhaps the most recent innovation is the application of blast movement monitoring (BMM) devices to quantify blast movement. These devices emit an electronic signal and are planted at surveyed locations within the preblast material. Following the blast, their new locations are found using an electronic scanner. The magnitude and direction of the blast movement is given by the vectors between the pre- and post-blast BMM locations. However, it’s not clear how the BMM vector data can be best used to minimise dilution and ore loss. One common solution is to displace preblast dig line polygons by distances indicated by the BMM vectors. However, studies of BMM vectors show that blast movement not only displaces material laterally but also mixes material internally within the bench (Thornton, 2009a).This paper presents a method for modelling the post-blast muck pile that accounts for displacement and internal dilution using simulated annealing. The preblast ore control block model is re-blocked to 1?×?1?×?1?m sub-blocks. Each sub-block is displaced by simulated BMM vectors conditional to post-blast surface topography and blast initiation sequence data in addition to BMM vector data. The displaced sub-blocks are aggregated into new ore control model blocks whose grades are calculated from the contained sub-blocks. New dig lines are then designed on the post-blast muck pile model using the new ore control block model grades. A case study based on actual data is provided.CITATION:Isaaks, E, Barr, R and Handayani, O, 2014. Modelling blast movement for grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 433–440 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

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