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By J Taylor, A Dubowik

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

Aug 18, 2014

By T Wellman, G Sternadt, R Hingston

The 335 000 oz Wilber Deposit is located within the Meekatharra-Wydgee Archaean greenstone belt in the Murchison District of Western Australia. The deposit comprises high-grade gold mineralisation hosted within a steeply west-dipping quartz lode, which lies within a broader (20–60?m) north-east striking shear zone envelope. Locally, the northerly-trending host rock geology includes greenschist facies high-Mg basalt (albite, actinolite, chlorite, biotite, calcite, zoisite, muscovite and titanate) intruded by at least two generations of felsic to intermediate porphyries (albite, actinolite, zoisite, chlorite, sericite, biotite, quartz and titanate). The Archaean rocks are cross-cut by a number of east–west striking Proterozoic dolerite dykes (biotite (50 per cent), albite, carbonate, epidote, titanate and actinolite) that are interpreted to have intruded pre-existing regional structures. The entire mine package is cross-cut by a system of shallow north-east-striking, north-west-dipping, barren quartz veins that commonly contain large (up to 30 cm), euhedral, smokey quartz megacrysts.The north-east-trending lode lies within a 3 m wide shear zone and varies from a single discrete 0.5 to 4 m wide laminated, massive or brecciated quartz-carbonate vein to multiple laminated veins up to 1 m wide within the shear. The veins exhibit strong boudinage, with cross-cutting quartz-carbonate seal veins in the boudin necks. The boudin necks often contain pink calcite. The shear zone fabric wraps closely around the boudin necks proximal to the vein, becoming more lode parallel distal to the vein. The lode is offset by a north to north-north-west trending fault.Mineralisation occurs as free gold within the quartz carbonate veins, with accessory sulfides including pyrite ± chalcopyrite, ± galena ± sphalerite. Fuchsite is observed in the veins, as laminar wall rock inclusions, with visible gold commonly associated with the wall rock laminations.Gold grades range from less than 1 g/t within the hosting shear zone, either at the margins or interstitial to the veins, to approximately 30 g/t in the single vein, and up to greater than 60 g/t in the multiple vein areas. Gold is commonly visible and disseminated throughout laminated, breccia and massive quartz veins, although laminations show the highest concentration of gold grains.CITATION:Hingston, R, Wellman, T and Sternadt, G, 2014. The geology of the Wilber Deposit, Andy Well Gold Project, Murchison District, Western Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 55–64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By R O’Sullivan, D Taylor, J G. McLellan, B Miller

The Mount Isa copper deposit is located adjacent to the city of Mount Isa, Queensland, and lies within a series of Palaeoproterozoic to Mesoproterozoic Superbasins. The deposit is hosted almost entirely within the Urquhart Shale (US), a unit of the Mount Isa Group sediments and part of the Isa Superbasin. The copper mineralisation is separated into two distinct orebodies: the X41 mine (1100 and 1900 orebodies) and the Enterprise mine (3000 and 3500 orebodies). The orebodies are situated in the hanging wall of the major controlling structures, the Paroo Fault, which has juxtaposed older basement Eastern Creek Volcanics against the younger Mount Isa Group sediments cf 1655 ± 4 Ma. Conjecture remains over the exact timing of this thrust event. However, it is clear that inflections on the Paroo Fault have a close association with the orebodies and are an important structural feature in the mineralisation of the Mount Isa copper deposit.The life-of-mine is reducing steadily and new geomechanical modelling techniques were employed to target structurally controlled mineralised zones in three dimensions. Following a structural review of the mine using underground mapping, structural data and core shed observations, a conceptual 3D mine model was constructed utilising existing data modelled in MineSight®. This conceptual model included all the main lithological units and structures. The conceptual model aimed to test the effects of deformation on the main lithological and structural components of the system and attempted to highlight areas of anomalous stress and strain that may indicate a higher likelihood of fluid focusing and mineralisation potential. This project was focused on testing the latter stages of a D3 event (NE–SW compression) and D4 event (SE–NW compression), which are considered to be responsible for the current location of the mineralisation.The fully coupled 3D finite element analysis models resulted in highlighting anomalous patterns of stress and strain and subsequent fluid flow as a result of the two deformation events. The NE–SW D3 simulation provided the best correlation with the known distribution of mineralisation. This event also indicated several areas on the Paroo Fault and within the US that have potential to host further areas of mineralisation. The SE–NW D4 simulation provided less of a correlation with known mineralised zones. However, this event may have been responsible for post mineralisation re-mobilisation of copper on a relatively small scale. Areas of maximum shear strain, shear stress, volumetric strain and fluid flow correlated well with areas of minimum principal stress and provided the best overall match with known mineralised zones. Furthermore, several additional highlighted areas provide a high potential for further discovery of copper mineralisation. Recent exploration drilling north of the Enterprise mine 3000 orebody, utilising geomechanical modelling as part of the targeting criteria, intersected copper mineralisation, providing further validation of the modelling results.CITATION:McLellan, J G, O’Sullivan, R, Miller, B and Taylor, D, 2014. Geomechanical modelling of the Mount Isa copper deposit – predicting mineralisation, in Proceedings Ninth International Mining Geology Conference 2014 , pp 197–206 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By I Treloar, T Elenbaas, E Isaaks

Critical reviews of grade control generally focus on blasthole sampling and the estimation of ore control block model (OCM) grades, with little or no attention given to dig-line design. For example, the estimation of block grades is deemed important as estimation errors lead to the misclassification of ore types and subsequent dollar loss. Recognition of the problem that the underestimation of block grades may be more or less costly than overestimation led to the application of loss functions to the classification of individual OCM blocks by ore type. The method is known as maximum profit selection (MPS). However, each OCM block may be misclassified a second time by dig-line design. Although each block may initially be assigned an optimum ore type by MPS, OCM blocks are seldom individually mineable by ore type. As a result, a common solution to this problem is the design of mineable polygons or dig lines loosely constrained by a minimum mining width. All material within a properly designed dig-line polygon can be mined and sent to a single destination such as the mill, stockpile or waste dump. These dig lines are often designed manually or by simple variations of computer-generated contour lines. They are generally suboptimal and result in additional misclassifications of ore types. This paper provides an algorithm for constrained optimum dig-line design where dig-line misclassifications are also evaluated through loss functions or MPS. Constrained optimum dig-line designs minimise the dollars lost by dig line misclassifications for a given minimum mining width constraint. A case study is provided illustrating constrained optimum dig-line design and subsequent benefits.CITATION:Isaaks, E, Treloar, I and Elenbaas, T, 2014. Optimum dig lines for open pit grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 425–432 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By G Fahey, S Rose

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

Aug 18, 2014

By R Sterk, B Reid

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

Aug 18, 2014

By J Ta’ala, M Handyside

Mechanical sampling from conveyors has historically been a staple in the iron ore industry when information related to chemistry, sizing and moisture is required. In order to comply with ISO 3082:2009, samples can be taken either on a mass or time basis provided no bias is introduced by periodical variation in quality or quantity. With the introduction of mechanical sample carousels, you also have the opportunity to collect samples on a mass or time basis. In order to optimise automatic sample stations in a changing production environment, BHP Billiton Iron Ore (BHPBIO) has developed a simulation model that enables the various combinations of mass–mass, mass–time, time–time and time–mass to be investigated.The sample station model can utilise actual (variable) feed rates to achieve high resolution and enables the simulation of sample size variation. Cutter speeds and other settings can then be adjusted to better optimise the performance of the sample station with regards to optimal sample size as well as ensuring the sample station is in compliance with ISO 3082. The model can also assist process engineers in adjusting settings to better optimise the sample station and reduce unwanted events such as blockages. The model can be easily modified to conform to various sample station designs. This paper demonstrates the use of the model and the benefits that can be achieved.CITATION:Handyside, M and Ta’ala, J, 2014. Simulating time versus mass basis?sampling, in Proceedings Sampling 2014 , pp 155–164 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By G J. Halstead, R C. Steinhaus

The True Pipe® in-line sampler was developed in an attempt to address the need for a mechanically reliable and correctly designed sampler to suit one-dimensional pressurised slurry pipelines, often found in metallurgical process plants but for which no reliable and representative sampling solution as yet exists.The design, whose operation is based on the principle of symmetry, is described by Dominique François-Bongarçon (2005) with the synchronous opening and closing of relevant valves. It representatively isolates portions of the particulate material stream at predetermined intervals for effective extraction of primary increments for subsequent sample compositing.Theory of Sampling applicable solutions have proven elusive in flowing pressurised particulate material streams, with various attempts to date not having formulated a viable, mechanically reliable and acceptable design.Compliance to sampling theory is critical, and a number of tests were conducted where certain operating parameters were altered to determine their influence and sensitivity on sampling representativeness.The results of the initial series of tests performed on a carefully designed rig are presented, with additional work discussed for necessary investigation in the near future.Getting closer to a robust, economic and correct design for this challenging application in the minerals industry may now not be that far away. Plant management staff will see improved metallurgical mineral balances around their process plants and significantly reduced sampling discrepancies, particularly in tailings applications. Improved quality control is now possible where, due to plant head room constraints, classical cross stream sampling methods cannot be employed.CITATION:Steinhaus, R C and Halstead, G J, 2014. True pipe sampler – a correct design utilising the principle of symmetry in pressurised slurry particulate streams, in Proceedings Sampling 2014 , pp 127–134 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By D Laskovski, T Nguyen

Flotation surveying can be an extremely powerful means of determining opportunities for circuit optimisation and benchmarking. The type of survey employed depends heavily on the nature of the information required from the survey. It follows then that the type of survey determines the type of samples required; however, regardless of the type, the success or failure of a survey is often dependent on the correct used of appropriate sampling techniques at each sampling point. For a successful flotation plant survey it is vital that the correct samples be collected at the correct time in respect to the feed and each other. This paper discusses the current best practice sampling methods used in flotation surveying and discusses in detail the ideal sample masses based on theoretical analysis. Comparisons with JKTech’s database of real plant operations will then be made.CITATION:Laskovski, D and Nguyen, T, 2014. An investigation of current flotation survey sampling, in Proceedings Sampling 2014 , pp 99–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By D François-Bongarçon

The theory of sampling (TOS), and therefore representative sampling, is based on three fundamental principles: sample correctness, which handles the search for non-bias; segregation, the effects of which must be eliminated or minimised; and variance control to help achieve the desired reproducibility. After briefly reviewing these very few, albeit essential first principles of Gy’s TOS, the state-of-the-art in TOS is examined through the prism of these principles and the prospects for the future are explored, with suggestions for further research where relevant. Regarding segregation, which is currently the focus of much research, new orientations are proposed. For correctness, which takes on a major importance when it comes to sampling devices, some new, important principles that have been put forth by recent research, are described in details.CITATION:François-Bongarçon, D, 2014. State of affairs and current research trends in theory of sampling fundamentals, including segregation and correctness, in Proceedings Sampling 2014 , pp 11–16 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By J E. Powalisz

"The application of automated sampling techniques can help to provide a representative sample of process fluids and slurries that provide data for controlling process, custody transfer and quality assurance and quality control purposes.The automation of sampling provides a more consistent and reliable sampling process and eliminates many of the human-induced errors. Automated sampling can also provide a higher degree of safety in the plant/processing environment as well as better bottom-line results.Automated, fixed volume samplers can provide a very representative sample by integrating many small ‘grabs’ of sample from a process. Automated samplers can be controlled in a variety of ways to optimise the sampling process, including:cycle ratedwell timetotal volume.Properly selected and applied, an automated sampler can effectively isolate the operator from the process fluid during sampling and, to a great degree, during sample container collection.A variety of materials of construction, including seals, are available to handle demanding mining applications. Alloy 625, alloy 2205, AL6XN® and even certain plastics are used successfully in mining slurry applications.This paper explores the application of automated, fixed volume, batch style samplers in copper/nickel and gold processing, specifically pregnant leach solution and extraction fluids.Several specific field applications are discussed, including process installation details, hardware and operation.CITATION:Powalisz, J E, 2014. The application of automated samplers in copper/nickel processing, in Proceedings Sampling 2014, pp 35–42 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014

By L Lachance, F Flament, D Leroux, S Gariépy

The pervasiveness of poor sampling practices in and around mineral processing plants could seem intriguing in view of the various documented evidences both for causes and consequences. To this extent, this paper revisits the well-documented but lesser-known fact that failure to care sufficiently about how samples are selected and managed is the mother source of almost all sampling biases. The authors believe that the potentially huge leverage between causes and consequences as well as the diversity of people involved in sampling call for a globally integrated solution rather than for a point solution. Such a globally integrated solution has already been put forward by the AMIRA P754 Metal accounting – code of practice and guidelines (AMIRA, 2007) that inherently requires accuracy to be targeted, measured, reported and managed. Furthermore, always in order to avoid a point solution, several layers of protection against biases must be put in place with each one involving a different ownership whenever possible. This is exactly the role intended by the supervisory bias detection method described in this publication. It is based on the continuous monitoring of the expected value of reduced residuals obtained from statistical data reconciliation conducted in a metal accounting context. This supervisory bias detection method is developed in full details after which Monte Carlo simulations are done on a mineral processing plant example for showing how it can be successfully applied for detecting hidden biases.CITATION:Lachance, L, Leroux, D, Gariépy, S and Flament, F, 2014. Detecting sampling biases in metal accounting, in Proceedings Sampling 2014 , pp 109–120 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By F F. Pitard

The optimisation of a metallurgical plant requires two kinds of sampling systems. The first provides samples to follow process changes, so in due time actions to maintain key parameters within pre-established specifications can be applied. The second provides composite samples at the end of a working shift to demonstrate that valuable constituents sent to the plant went to either a final concentrate or to the tailings in a logical, expected proportion. Contrary to what many experts may claim, these two kinds of sampling requirements are incompatible and cannot be fulfilled using the same sampling systems; this is because the required samples have completely different objectives. A process control sample is an instantaneous sample with increments taken at short intervals, and the objective is to know where the process is at any given time. Excellent accuracy is not a must, however good precision is recommended since a possible process correction may need to be made. Online analysers fed with in-stream stationary cutters or other kinds of in-stream or by-stream probes can do well for such a mission. A composite sample for metallurgical accounting with increments collected over a long period of time, for which excellent accuracy and good precision are both required, must be generated by sophisticated and extremely well-maintained cross-stream sampling stations. The use of process control sampling systems to achieve good metallurgical accounting has been promoted by several manufacturers of sampling equipment around the world; it is a grave mistake that is misleading top management and a practice that should be scrutinised and preferably eliminated. Furthermore, bias tests used to prove otherwise are often based on insufficient data to draw valid conclusions; a guideline is provided.CITATION:Pitard, F F, 2014. Sampling systems for process control and metallurgical accounting, in Proceedings Sampling 2014 , pp 25–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By D W. Stevens

Mechanical sampling provides a definitive value for the product sampled but the results are not instantaneous, meaning that decisions on process control can only be made hours after the sample is taken. Chemicals are added, tailings are sent to waste, stockyards are laid and the data for the decision-making is historical. Online analysers provide instantaneous information, allowing operators to make immediate and cost-saving decisions on the process. However, pending the specific online analysis application, there is a need for reference sampling for dynamic calibration/bias updating of the analysers so that they can deliver the desired precision and accuracy. What would be the economic justification for combining mechanical sampling with online analysis to reduce laboratory costs and provide immediate process control with certainty of accuracy? Approved sampling according to the Theory of Sampling, with immediate process control information.CITATION:Stevens, D W, 2014. Justification for integrating mechanical sampling with online analysis, in Proceedings Sampling 2014 , pp 135–138 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By J E. Powalisz

Obtaining a representative sample of bulk materials in process industries is critical to providing valid data for process control and custody transfer (valuation). The accuracy of a sample, that is to say how well the sample represents the material in the process, is directly related to how well the process can be controlled and to how much a product may be worth. Sampling accuracy then is in fact related to bottom line profitability.Sampling theory offers information and equations on how to take a representative sample from a process, however, the actual practice of extracting a sample from the process can be more of an art.Key sampling variables include product specifications such as bulk density, particle distribution, material conveyance, practical sampler location, sampler type and sample frequency and volume/mass.This paper discusses basic sampling theory, sampling methods, types of samplers, how to develop a ‘real world’ sampling system and current manual and automated samplers.Key points include ‘practical precision and variance’, material properties, flow properties, direct sampling versus indirect sampling, sampler types and applications.CITATION:Powalisz, J E, 2014. Bulk solids sampling, in Proceedings Sampling 2014 , pp 179–188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By W P. Breytenbach

"The phased application of statistical process control (SPC) infers that processes are classifiable as pre-SPC (or phase zero), phase I and phase II processes, with different objectives being pursued in the different phases. Phase zero processes, defined as processes affected by assignable causes of variation, are characterised as follows: out-of-control with unknown autocorrelation structure having an unknown statistical distribution not performing consistently on target with minimum variability potentially incapable of conforming to the product specifications. The objectives of phase I SPC is to obtain estimates of the mean (µ), variance (s2), probability density function (f(X)) and the autocorrelation structure, as well as transforming the process into a phase II process (defined as a process conforming to specifications and performing on target with minimum variability). As in any other type of research or pragmatic improvement intervention, sampling is required is to achieve these objectives. The challenge of deciding a phase I sampling plan is multifarious since it has to cope with the aforementioned effects of assignable causes and provide for rigour estimates of the unknown parameters. Furthermore, deciding sampling plans in phase I invariably presents a classical catch-22 situation: appropriate sampling is required to determine the autocorrelation structure of a variable, but knowledge of the autocorrelation structure is required to formulate an appropriate sampling plan. This paper suggests, for random variables, guidelines to formulate sampling plans, and presents a methodology to estimate the inherent process parameters of process variables and an approach to identify assignable causes in phase I. CITATION:Breytenbach, W P, 2014. Rational sampling and standard deviations for random variables in phase i application of statistical process control, in Proceedings Sampling 2014, pp 141–154 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014

By G M. Jeffress, D C. Arne

There are two discrete aspects to collecting portable X-ray fluorescence (pXRF) data to obtain reliable results and to comply with reporting requirements under the 2012 edition of the JORC Code (JORC, 2012) – sampling method and quality assurance. A robust sampling program is required to obtain representative material for analysis. The appropriate method should be established for a particular project using a small orientation study. A variety of approaches to sampling soils, drill cuttings, rock faces and diamond drill core are discussed. These include using multiple spot analyses, scanning using a single operating beam and the collection of cutting saw pulps. The operator must also be aware of the attenuating effects of analysing through sample bags of different material types for various elements as well as the limitations of current pXRF instruments in reporting reliable data for certain elements. The analysis of the samples must also be accompanied by a quality assurance program in order to generate data that are ‘fit for purpose’. This includes recording X-ray tube resolution on a routine basis, using matrix-appropriate standards for which total elemental concentrations are available, using silica blanks, capturing sufficient duplicate analyses to constrain data precision and obtaining check assays to calibrate pXRF data against laboratory data. Examples of quality control approaches and data are presented. Table 1 of the 2012 JORC Code also recommends that information on instrument make and model, reading times and calibration be provided in any reporting of pXRF data. To this should be added information on operating mode and temperature, software version and moisture content of the samples. A robust sampling methodology with a suitable quality assurance/quality control program should produce pXRF data of sufficient quality for public reporting purposes, provided that the data are presented using appropriate cautionary language and adequate supporting information.CITATION:Arne, D C and Jeffress, G M, 2014. Sampling and analysis for public reporting of portable x-ray fluorescence data under the 2012 edition of the JORC Code, in Proceedings Sampling 2014 , pp 57–64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By G J. Lyman

The theory of sampling has progressed slowly over the last century. The concepts of correct sampling were known to mining engineers such as D W Brunton in the 19th century. It was recognised early in the 20th century that the Poisson distribution of particles carrying the target analyte was the key to the uncertainties between samples of a given mass. However, no efforts were made until the 1980s to determine the entire sampling distribution as a function of sample mass. The variance of sampling was made clear by Gy and others, but none attempted to determine the entire sample assay density function until J H Venter in South Africa applied the method of characteristic functions to the problem.Venter applied the method to a specific case of very low analyte concentrations in samples of very fine particle size where his assumption of constant sample mass was justified. When his general methodology is applied to the more general problem, it can be shown that the assumption of constant sample mass is no longer justified and leads to some anomalous results for sampling variance. Venter’s method can be expanded to allow for a statistically variable sample mass and to take into account the size distribution of particles that carry no analyte.This paper presents the basis of Venter’s work and shows how the approach can be easily modified to yield results for the variance that are consistent, for example, with the work of Gy. It is also demonstrated that the entire sampling distribution can be determined without undue computational burden when sufficient information on the material heterogeneity has been collected.CITATION:Lyman, G J, 2014. Determination of the complete sampling distribution for a particulate material, in Proceedings Sampling 2014 , pp 17–24 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By R Shaw, T T. Neidel, C Adams

Sampling equipment manufacturers endeavour to ensure that the mechanical equipment installed in sampling systems are designed and manufactured to adhere to the requirements of the International Organization for Standardization (ISO) or other standards relevant to the application. The mechanical parameters necessary to achieve these standards can be well controlled and requirements such as constant speed can be met through good mechanical design and engineering. However, when the equipment is installed and put into operation, the ISO compliance of the system is out of the hands of the equipment manufacturer and handed to the operator, who may be a generalist control system integrator.Making a sampling system perform according to standards, and being able to monitor and report on compliance require that the sampling system knowledge and the control integration is combined and applied in an integrated approach. Using a dedicated library of control routines developed for sampling can change a system from having compliant equipment to being a compliant system. The library has to include monitoring of relevant parameters and control and reporting on sampling parameters.CITATION:Neidel, T T, Adams, C and Shaw, R, 2014. Control and monitoring of International Organization for Standardization compliance for industrial sampling systems, in Proceedings Sampling 2014 , pp 121–126 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By K M. P Singh, K M. K Sinha, G S. Jha, T Gouricharan, K K. Sharma

The majority of the powerplants in India are fed with non-coking coals, with the coals dispatched from their respective mines via wagons loaded by a rapid loading system or pay loader. The usual top size of coal is 200 mm and sampling is carried out manually from wagons. The manual method of wagon top sampling of large size raw coal is not only difficult, but also violates some of the fundamental principles of sampling. As per sampling requirements, samples are to be drawn from the full depth of the wagons, which is impossible to be done manually. Since the ash distribution in the different size fractions is not homogeneous, the results from the samples, which do not reflect the true size distribution of the lot, are likely to be biased. More importantly, sample collection by shovel from the top is a function of human discretion and not governed by the equiprobability rule. In another case, the sample has been collected by a cross belt-type auto mechanical sampler for 200 mm size coal at one of the super thermal power stations. Test analysis shows that coal collected using a cross belt-type mechanical sampler also has significant deviations from stopped belt coal samples of 200 mm size due to size segregation. Studies carried out on wagon top sampling through specially designed experiments reveal some interesting features. The presence of bias in wagon top sampling is apparent when compared with the ‘stopped belt’ sample. In this paper, a comparative study between manual wagon top sampling/auto mechanical sampling with respect to stopped belt sampling has been conducted for coal of size 200 mm. In addition, precision studies have been performed for wagon top sampling/mechanical sampling for Indian thermal powerplants.CITATION:Sinha, K M K, Sharma, K K, Jha, G S, Singh, K M P and Gouricharan, T, 2014. A comparative study of manual wagon top sampling and auto mechanical sampling of 200 mm size coal with respect to stopped belt sampling of thermal coal at Indian super thermal powerplants, in Proceedings Sampling 2014 , pp 43–48 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014