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By J Channell, G Phillips

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

Aug 18, 2014

By 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 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 Airong Zhang

El presente texto señala los elementos importantes de una licencia social para realizar operaciones mineras en un determinado territorio. En ese sentido, el desarrollo de este proceso permitirá que las comunidades dialoguen con los inversionistas y a su vez les otorgará confianza en el camino de la exploración minera. Para ello, se muestra un ejemplo aplicado a una comunidad minera denominada Queensland, Australia donde a través de doce encuestas desarrolladas durante 12 meses, se percibío la trascendencia no solo de la gestión, sino el contacto de las comunidades y las compañías mineras y evitar conflictos sociales.

Aug 1, 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 P Minkkinen, J Lohilahti, T Korpela, B McPherson

Concentrator plants intake the ore from the mine and produce concentrates by extracting valuable minerals in a succession of process steps. Controlling the extraction process and detecting changes in the process requires updated information on a minute basis. Moreover, due to economical reasons, one must also collect metallurgical samples on a daily basis for monthly reporting.In this paper, we present how slurry samplers were installed in a Cu-Ni flotation plant to accomplish the aforementioned tasks. An on-stream elemental analyser at the plant is used for flotation process control by taking samples from selected process streams. Two process streams, the flotation feed and tail, are also equipped with metallurgical samplers. The metallurgical samplers were designed to have low head loss, be robust and easy to maintain and to collect slurry samples in a reliable way for the metallurgical accounting.Samples were collected by different sampler types and we discuss the uncertainty arising from sampling in the assays. Variographic analysis was carried out on the process data in order to find periodic components in the process, and estimate the correct number of shift sample increments and measurement error components. The metallurgical samplers were proven to be reliable devices with zero downtime and no sanding issues in the main process flows. In addition, we show that the tail measurement is the most important one for the plant recovery calculation, which emphasises the importance of the sampling accuracy in the tail stream.CITATION:Lohilahti, J, Korpela, T, Minkkinen, P and McPherson, B, 2014. Analysis of slurry sampling arrangements at a froth flotation plant, in Proceedings Sampling 2014 , pp 91–98 (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 R Minnitt

Two methods of calibrating the parameters K and Alpha for use in Gy’s formula for the fundamental sampling error were investigated. Approximately 480 kg of broken ore from Harmony’s Target gold mine in South Africa was used to compile the replicate samples for two experiments. The duplicate series analysis (DSA) and segregation free analysis (SFA) methods differ in terms of their approach to recovering the sized materials required for the calibration procedure. In this experiment the DSA method split off six more-or-less equal masses of material from a 75 kg lot that was successively crushed to finer and finer fragment sizes. The sublots so formed were split into 32 samples and fire assayed for gold. The SFA method used approximately 250 kg of broken ore crushed to 95 per cent passing 2.50 cm, which was then passed through successively finer screens until a sublot of less than 0.0075 cm was obtained. Each of the 15 sublots obtained in this way were split using a riffle splitter into 32 samples that were fire assayed. A total of 672 fire assays were used in these experiments. The sampling parameters K and Alpha were used for the compilation of a nomogram and to calculate the gold liberation size of the ores. While there are no definitive results in terms of the actual gold grain sizes against which the calculated sizes can be compared, it appears that the DSA method produces more acceptable results.CITATION:Minnitt, R, 2014. A comparison of two methods for calculating the constants K and alpha in a broken ore, in Proceedings Sampling 2014 , pp 165–178 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By M Graham, R Brunning, C Andringa-Bate, S Westergren

In 2010, Rio Tinto Iron Ore’s operations commenced the planning and design of a sampling and analysis system for the new 50 Mt/a Cape Lambert Port B (CLB) facility. Current sampling systems at the ports consist of automated robotic, mass-based sampling protocols employed at Dampier, and semi-automated, time-based sampling systems operating at Cape Lambert Port A.The new sampling system at CLB has brought together a fully automated sampling and analysis system utilising time-based sampling, with the capacity to sample ore products of medium quality variation as defined in ISO 3082 (ISO, 2009). The CLB system is required to sample at shiploading rates from 6000 t/h to 13 440 t/h and provide full load-port analysis. The sampling approach is to proportionally extend primary increments (of varying mass relative to shiploading rate) to a standard length using variable speed aero-belt conveyor systems. This enables a fixed number of secondary cuts to be achieved for all primary increment masses and to be delivered to the automated cell. The cell is required to be capable of concurrently processing four individual shipments, each containing multiple cargoes.Achieving the target sampling precision for all export cargo sizes has culminated in the planning, design and construction of the largest automated iron ore port laboratory in the world. The CLB sampling and analysis cell was commissioned in Q3 and Q4 2013. This paper discusses the sampling philosophy and commissioning outcomes.CITATION:Brunning, R, Andringa-Bate, C, Graham, M and Westergren, S, 2014. Cape Lambert Port B shiploading, sampling and analysis, in Proceedings Sampling 2014 , pp 79–90 (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 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 J T. Carswell, K Sutton

Quality control (QC) of reverse circulation drill sampling commonly involves regular duplicate subsampling to monitor the extent of imprecision or random error in the subsampling system. In gold mining in Australia, the subsampling tool is usually a cone splitter.Other sources of error, including delimitation error and bias (systematic error) in the subsampler are often assumed to be negligible or ignored for being too difficult to QC.This paper describes actual sampling errors and error mitigation based on quality assurance and quality control (QA/QC) of surface and underground reverse circulation drill sampling at a high-nugget gold mine at Sunrise Dam, Western Australia.CITATION:Carswell, J T and Sutton, K, 2014. Sources of sampling error and implications for quality assurance and quality control in surface and underground reverse circulation drilling, in Proceedings Sampling 2014 , pp 65–70 (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

By J Chan, T Baumgartl, A Plante, C Peltre, P D. Erskine

Mine soils are often organic matter and carbon poor due to disturbance, topsoil stockpiling and mixing with spoil. They present an opportunity to observe the accumulation of soil carbon arising from rehabilitation or ‘green carbon’ through organic matter inputs and may be considered for carbon credits. Soil carbon is known to improve multiple soil characteristics and is viewed as an indicator of soil health.When attempting to estimate soil carbon levels in the Australian coal mining regions, both coal and black carbon (BC) need to be quantified. Coalmine soils contain coal particles that are difficult to distinguish from organic matter using standard carbon analyses. BC, a material arising from the incomplete combustion of organic matter and fossil fuels, displays some similar characteristics to coal and is ubiquitous in Australian soils due to bushfires. The presence of coal and BC complicate the determination of green carbon levels in mine soils.A method to quantify coal and BC in mine soils from the Bowen Basin using thermal analysis and multivariate curve resolution is presented. By determining BC and coal contributions it is then possible to calculate green carbon levels in rehabilitated mine soils. Calculated green carbon levels are compared with bulk density as soil quality indicators.CITATION:Chan, J, Baumgartl, T, Erskine, P D, Peltre, C and Plante, A, 2014. Distinguishing carbon fractions in coalmine rehabilitated soils, in Proceedings Life-of-Mine 2014 , pp 491–498 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By I H. Wilson

After decades of turmoil, Rwanda launched its Vision 2020 in 2000 aimed at reconstructing government and addressing poverty. Implementation focused on the agricultural sector, infrastructure and education. Later economic development and poverty reduction strategies recognised that expansion of tantalum, tin and tungsten mining could potentially diversify Rwanda’s economy and improve the balance of trade. In 2005, comprehensive environmental legislation requiring environmental impact assessment for all new mines was introduced. Since 2006, government-operated mines have been privatised and illegal artisanal miners encouraged to form cooperatives. The government passed a new Mining and Quarry Exploitation Law in 2008 and approved a new Mining Policy in 2010. This policy was influenced by the Africa Mining Vision (AMV), which the African Union approved in 2009 to ensure African countries obtain reasonable benefits from exploitation of their mineral wealth. The Rwandan mining industry has grown significantly over the last five years and the second economic development and poverty reduction strategy, released in September 2013 forecasts a further three-fold increase in production in the next five years. The strategy prioritises the mining industry and proposes new legislation, better information, greater transparency, encouragement to investment and use of best environmental and technical practices. It also proposes that Rwanda develop a ‘green’ mining sector featuring a ‘model’ mine that is fully funded through green investment and incorporates renewable energy systems, water treatment systems, forestry schemes and local training. Many international development partners have contributed to the current legislative framework and are monitoring environmental and social performance of mining in Rwanda. Local communities have generally benefited from mining and the new mines show improved environmental performance. The major challenges are dealing with the legacy of past haphazard mining practices and establishing linkages between the mines and local industries to create broader economic development.CITATION:Wilson, I H, 2014. Rwanda and the Africa mining vision, in Proceedings Life-of-Mine 2014 , pp 427–438 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By J Harris, M Shi, S Vink, P A. Kirsch

Across the life-of-mine, water is both an essential commodity to mining, and one of the most significant hazards. In Australia, a land of drought and floods, availability of water is a critical strategic risk for mine sites and neighbouring stakeholders, with both insufficient water leading to curtailed operations and contested space, and extreme water closing operations through flooding of mine sites, transportation infrastructure and unplanned regulatory restrictions. In addition to these major strategic risks, water must be addressed in operational risk management activities in many different ways.This paper develops a set of categories for classification of water risks based on academic papers from the water in mining literature. These categories are applied to media content analysis of articles in International Longwall News (ILN) (an online coal industry news site) obtained with the search terms ‘water’, ‘rain’ and ‘flood’. Identified risks are discussed within the context of the life-of-mine. The paper uses these same categories to analyse the treatment of water risks in a new coal industry risk management body of knowledge called RISKGATE (http://www.riskgate.org, Minerals Industry Safety and Health Centre, The University of Queensland). The discussion of water risks in both INL and RISKGATE is compared and contrasted to pinpoint opportunities (and a roadmap) for further development of a specific RISKGATE water module for site-based operations. The media review also identifies areas for development of RISKGATE expansion topic(s) that would address other strategic water risks, eg severe weather events.CITATION:Shi, M, Kirsch, P A, Vink, S and Harris, J, ?2014. Water as risk in mining – media analysis and the RISKGATE body of knowledge, in Proceedings Life-of-Mine 2014 , pp 205–218 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By P A. Kirsch, A Hine

Mining is a major global industry that requires the moving of considerable volumes of earth and rock (overburden) to win the valuable ore prior to mineral extraction and processing. As a result of this process, new landscapes are created, both extracted voids and overburden piles, as well as infrastructure for management of mine operations, wastewater, tailings, other raw materials, transportation and extreme rainfall events. Resource companies must develop and obtain regulatory approval for detailed plans that manage this displaced material through all phases of the life-of-mine and rehabilitate the site at the time of closure (including landform stability, revegetation and ongoing management).Individual mine sites operate in long time frames (ten to 50 years), with several mines often operating in the same region, generating cumulative overburden volumes and heavily altering the original landscape. These impacts are universally framed as a negative consequence of the industry, especially by modern society that values natural (and some agricultural) landscapes as pristine and almost sacred. Overburden and tailings are also seen as a problem, and are a significant business cost to mining practice.This paper looks to investigate perceptions of mining and post-mining landscapes, questioning the aesthetically driven emphasis on the ‘natural’. It proposes instead an opportunity to reframe the way we look at overburden and landscape impacts from mining, exploring the possibility of imagined post-mine landscapes unburdened by traditional aesthetic expectations. These landscapes, to be conceived by regional stakeholder roundtables, have the capacity to be built by regional mining consortia as a foundation for sustainable post-mining economies.Post-mine regeneration offers both the motivation and the basic materials to create an altogether new environment from a blank slate. Few circumstances allow the opportunity to truly explore a re-envisioning of the land on a huge scale, and the possibilities merit serious consideration.CITATION:Hine, A?and Kirsch, P?A, 2014. Dreams of futures past – curating post-mining landscapes, in Proceedings Life-of-Mine 2014 , pp 121–138 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By G Hancock, A Kemp, I Taylor

The mine site is situated south east of Port Hedland in the Pilbara region of Western Australia. A detailed engineering design was undertaken for six irregularly shaped waste rock dumps at the site. The design was undertaken to ensure long-term stability of the dumps and optimise material movements for closure construction. The Watershed Erosion Prediction Program (WEPP) and SIBERIA landscape evolution modelling was undertaken for the landforms using regional and site-specific material characteristics to provide an indication of the maximum allowable slopes and corresponding slope lengths for long-term stability.The majority of the waste materials present in the waste rock dumps are considered likely to be subgrade banded iron formation (BIF) and chert, which is generally competent material. The presence of a large number of dolerite dyke swarms indicates appreciable volumes of dolerite were produced as waste from the pits. Geological records also indicate that the dolerite is logged as being heavily kaolinised in the geological logging, hence kaolinite is very likely to be present within the waste dumps on-site. This material has an elevated risk of being highly erodible/dispersive. Clays and shales are also likely to be present in the dumps and are considered to be less competent material (relative to the BIF/chert).The final design configuration of the largest existing ‘unplanned’ waste rock stockpile is compared to a hypothetical continuous ten degree outer embankment alternative. This paper will present a brief description of the alternatives for closure of three waste dumps in close proximity to each other and how the detailed design based on site-specific materials and conditions compare to an alternative approach blankly assuming that most materials will be erosionally stable at less than ten degrees.CITATION:Kemp, A, Taylor, I?and Hancock,?G,?2014. Landform design for Pilbara mine site – why plan and design waste rock dumps for closure based on site-specific conditions?, in Proceedings Life-of-Mine 2014 , pp 47–54 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014