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By S Warden, T Neville, P Leckie

At its simplest, the classification and characterisation of an orebody is a matter of Where, What and When. Where and with what spatial resolution are measurements taken, What properties are measured, and When are the data acquired, processed, and delivered to create the most value. This paper delves into how existing and near-term advances in measurement technologies, field automation, and whole-system-digitisation are combining to open new routes for mine and exploration productivity improvement. Commencing when the initial exploration hole is dug, the advancement in deployment of survey technology—from expert-operated, to driller-operated, to driller-integrated—is used to demonstrate a template for adoption of higher technology measurements. We then introduce and discuss the multi-use measurement as offering outsized returns from a single measurement run, highlighting two new technologies that acquire rock strength while drilling and downhole assay data as examples. For rock strength, we highlight a novel approach to determining Uniaxial Compressive Strength (UCS) while drilling, its relationship to and advantages over Mechanical Specific Energy (MSE), and how it offers utility to multiple downstream processes. For downhole assay, we detail how a back-tophysics approach to Pulsed Fast and Thermal Neutron Activation (PFTNA) analysis offers significant advantages over other measurement methods and earlier implementations of PFTNA, generating a rich data set that can significantly extend and improve the information on which mining decisions are made. Finally, we discuss the possibilities enabled via optimising data delivery, collection, and curation— noting a fundamental limitation of historical systems and exploring the possibilities that will be unlocked by soon-to-market solutions that better enable Orebody Characterisation data to (virtually) move in space and time with rock material post-blasting. Ultimately, the value of optimising the Where, What, and When from point of measurement to the moment it generates maximum value will create greater life-of-asset production for a lower cost and energy input.

Sep 1, 2024

By P Scott

Kaltim Prima Coal, an open cut coal mine located in Sangatta, East Kalimantan, Indonesia, operates two deep pits and two shallow pits with a truck and shovel operation. KPC produced 17 Mt of coal in 2002 by removing 120 Mbcm overburden. Geochemical investigations have indicated 20 per cent of total waste rock is potentially acid forming; ie it has the potential to create acid mine drainage (AMD). In the early years of the KPC operation, the presence of AMD had been observed in the mined out areas and in the waste rock dumps as a result of sulfidic waste rock exposure. A strategy for management of AMD from waste rock was implemented involving: sampling, analysis, modelling, selective handling and validation of final dump covers. Samples of the waste rock lithologies are collected from exploration drill holes for geochemical analysis to determine their acid generating potential. The geochemical database is used to develop the waste rock model for the life of mine pit areas. The acid forming and non-acid forming waste rock is delineated for each mining bench area for selective handling and placement within the waste rock dump during the operational stage. Each mining bench is sampled and assessed to validate the model predictions. The final dump cover is sampled to meet strict Quality Assurance requirements to ensure non-acid forming waste material is used in the outer cover of the dump. The geochemical investigation of the waste rock is integrated with mine planning to design and construct the waste rock dump to minimise the risk of generating acid. This process links the exploration stage, operation stage, and rehabilitation stage for each Pit area. The paper briefly reports the waste rock characterisation, waste modelling and strategies used for management of acid drainage by KPC.

Jan 1, 2003

By D Lucato, B Haase, R Saha, S Limberger-Forte, J Lishman

Cadia East Mining operations have employed geometallurgical techniques to advance the understanding of the in situ rock hardness variability across existing Panel Caves (PC). Geometallurgy advances the understanding of variability across an orebody through the integration of geology, mineralogy and processing response and therefore enhances spatial mapping of comminution or separation properties. Spatially extensive geometallurgical measurements are necessary so that continuous rock properties can be generated and used for the development of comminution and processing domains using geostatistical modelling. Standard testing protocol across geological and mineralogical domains is vital to understand the variability in deposit wide comminution and separation properties. The high cost and large sample requirements associated with metallurgical test work typically results in insufficient data density and distribution, making it difficult to model and map deposit scale variability. Quantitative hardness proxy tools are useful to measure in situ rock hardness, however this data is typically either sparse or missing within advanced mining operations. In recent years, mineralogy and multi-element assay data has often been collected as part of the standard geological data set and is generally coincident with metallurgical test work. In this paper relationships between mineralogy and comminution parameters have been applied to multi-element assay data with coincident measured Bond Work Index (BWi) data to generate a predicted BWi using linear regression. The predicted BWi is intended to supplement existing measured BWi data to enable better extrapolation across the deposit. Geostatistical Conditional Simulation methods have then used the predicted and measured BWi data to produce a BWi variable as a new input to the resource model. The simulated BWi can be used as an input for specific energy models to predict required grinding energy consumption across a deposit.

Mar 22, 2022

By E T. Baker, J A. Resing, S L. Walker, V Ferrini, F Martinez, R Haymon

"An EXTENDED ABSTRACT is available for download. A full-length paper was not prepared for this presentation. Enumerating active sea floor hydrothermal sites has been a challenge since their discovery almost 40 years ago. High-temperature hydrothermal sites are readily discoverable, primarily by detecting mineral-laden plumes, but working at these sites poses severe environmental and operational difficulties. Low-temperature vent fields, which may represent waning of venting from high-temperature systems, may be more accessible but are more difficult to locate. Over the last decade, however, oxidation-reduction potential (ORP; aka Eh) sensors capable of detecting minute concentrations of reduced hydrothermal chemicals have been successfully used to pinpoint such fields. In this extended abstract, we use ORP anomalies observed during continuous (towed sensor) plume surveys to estimate site frequency along four intermediate- to fast-spreading ridge sections. From these data, we estimate site frequencies between five and 16/100 km for these ridge sections. Previous camera surveys on the fast-spreading East Pacific Rise support these frequencies. These rates are much greater than the frequency of ~0.5–5/100 km, generally increasing with spreading rate, derived from well-surveyed ridge sections in the InterRidge database (InterRidge, 2014). The higher frequencies arise because ORP sensors are able to distinguish between sites as close as ~1 km and identify sites with negligible or no optical plume signal.CITATION:Baker, E T, Resing, J A, Martinez, F, Haymon, R, Walker, S L and Ferrini, V, 2015. How leaky are oceanic ridge axes? A new assessment of the spatial density of submarine hydrothermal discharge, in Proceedings PACRIM 2015 Congress, pp 3–8 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Mar 18, 2015

When Matthew Flinders entered in his log `This land forms the South side of the large bight; and besides projecting beyond the coast line, and being a little higher than usual is remarkable for having some reddish cliffs in it, and deep water near the shore', he was commenting on the deposit of bauxite at a place now known as Weipa. This sighting took place on 9 November 1802, and probably represents the first direct entry in Australia acknowledging a potential mineral deposit. Flinders, of course, had no idea as to what he was looking at, nor did he land to determine its content. If he had, he probably would have had no idea of the substance, and even less knowledge of its use. Nothing further was done to this for about 150 years.

Jan 1, 1993

By W Zirima

A detailed, mine scale non-linear numerical model of Rosebery mine has been built for the purpose of simulating life-of-mine global deformations. The model was calibrated using observations of displacement and damage, and was then used to investigate the correlation between dissipated plastic energy (DPE) and seismic event occurrence. The study is unique because the seismic data was collected over a relatively short period using a temporary portable seismic system. It is the intent to undertake significantly more work, but the analysis of limited data shows that a very good, non-linear relation between DPE and event probability is present. The observed correlation is consistent with measurements from other mines where more data was available. With more data, the strength of the correlation will allow the DPE analysis to be used during the design and sequencing phase of planning to better design the mine to minimise seismic hazards.

Jan 1, 2008

By N J. Potter, N W. Brand, J M. F Clout

The increasing demand for iron ore with low concentrations of trace elements, puts increasing pressure on iron ore producers for high-quality material. Understanding the mineralogy, petrography, chemistry, and mineral association of iron ore deposits is becoming increasingly important to provide iron ore products that meet the ever-increasing standards of steel mills. Limited attention has been paid to documenting new orebodies beyond bulk RC drill chip assays and product specification data. Therefore, limited information is known about the spatial distribution of minor and trace elements at the hand specimen scale, and elemental deportment within different ore and gangue minerals. In this study, samples from high-grade microplaty hematite, supergene-enriched martite-goethite and hematite iron ores are examined for their elemental and mineral associations. These samples contain distinctive minor and trace element distributions, with the mapping of deleterious elements (eg Zn, As, Cu) enabling the deportment and abundance within the ore and gangue minerals to be assessed. Results from this study show a diverse range of minor and trace mineralogy that are present in typical iron ore samples, in abundances below the detection limit of routine XRD scans, that host the deleterious elements, including but not limited to, sphalerite (Zn and S), chalcopyrite (Cu and S), xenotime (P and Y), apatite (P and Ca), cryptomelane (K and Mn), barite (Ba and S), alkaline feldspar (K, Al and Si) zircon (Zr and Si) and chromite (Cr and Al). The presence of these minerals and associated deleterious elements, even at low concentrations, has implications for producers, with the ongoing restrictions and tightening of environmental constraints in shipped iron ore products. By understanding the distribution and location of these elements within the iron ore, steps can be considered to maintain increasingly higher quality iron ore supply around the world.

Nov 8, 2021

By M E. Karmis

Traditional coal mining planning seldom considers key æsustainability factorsÆ such as: societal impacts in the area; jobs (both created and lost); dislocation of towns and residences; impact on neighbouring communities and individuals; infrastructure concerns; post-mining land use (except when limited by law or other factors); habitat disruption and reconstruction; long-term economic impacts in the community; and net long-term community benefit. This paper presents a systems engineering approach based on the premise that systems can only be optimised if all factors are considered at one time. In theory, coal mine designs can be optimised for return on investment, environmental protection and sustainability. Using this approach, the permitting process may be quicker and less costly, relationships with neighbours, communities, environmental groups may be improved, the mining industry may be seen as a positive for the short-term and long-term and the mining industry may increase profits. This paper discusses geographic information system (GIS) tools that may be used to incorporate ecological and other sustainable development concerns into models of coal mine sustainability performance. Along with coal production cost and value information obtained from past and present coal mining operations, GIS data are used to develop mathematical cost and equation models. By analysis of on-the-ground data, the parameters to be included in these models are identified, the relationships between these parameters quantified and the models developed. The paper also discusses the next phases of the work to be completed once the data is obtained and the models are adjusted and validated. At that time, site-specific information will be input into the models and the approach to mining a particular property evaluated and optimised for financial rate-of-return and other desired outcomes, such as preservation or enhancement of sustainability values. Finally, the paper will examine how this approach can be combined with traditional mining engineering considerations in order to develop an optimised mine plan for a specific mining property.

Jan 1, 2009

By B Lumsden, R Smiles

Independence Group’s Jaguar Mine treats a polymetallic ore producing a copper concentrate and zinc concentrate. Effective separation of the sulfides requires relatively fine grinding with flotation feed P80 of about 75µm. Zn losses to final tails are greater than 60 per cent and <32 µm. When magnetic conditioning was first installed in 2010 it showed about an 8 per cent reduction of zinc in final tail and on some ores a similar benefit for silver as well. Current testwork is showing about a 12 per cent reduction in zinc and silver in final tail, consistent with the original testwork. Sizing of the final tail during the tests showed that the reduction of zinc and silver losses were only in the <32 µm fraction, as would be expected from an aggregation process. However, the most surprising result was about a 4 per cent reduction in zinc and silver in the plant feed with a >99 per cent statistical certainty. The reduction in zinc and silver in the feed is also only in the <32 µm fraction. Therefore, because the magnetic conditioning of Zn flotation feed cannot impact plant ore feed grade the hypothesis is that the magnetic conditioning is reducing the fine mineral from downstream processes, like filtering and thickening, returning to the plant feed in the recycled process water. This hypothesis is consistent with plant observation of dirty concentrate thickener overflow and measurements of solids in the overflow, as well as the average % Zn grade in cyclone overflow that correlates with the magnetic conditioning ON and OFF days. This paper presents these plant test results.CITATION:Smiles, R and Lumsden, B, 2018. Improving fine sulfide mineral recovery in Independence Group’s Jaguar Mine zinc circuit, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 433–440 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

By B Laidens, D Souza, W Bielefeldt

The CaO-MgO-SiO2-Al2O3 system, characterised by its intricate phases and thermodynamic properties, plays a pivotal role in steel secondary refining processes, encompassing desulfurisation, non-metallic inclusion capture, and refractory protection. Accurate predictions for diverse industrial applications, including metallurgy, ceramics, and materials science, are imperative. To address this challenge, a combination of machine learning techniques will be specifically applied to model the liquid fraction of the slag and the solid fraction of MgO. The development of an artificial intelligence (AI) system, leveraging various machine learning techniques, has gained momentum in this project. The focus of this work is on constructing an AI model, based on machine learning techniques, within the CaO-MgO-SiO2-Al2O3 system, utilising simulation results from FactSage™, version 8.1 (by GTT Technologies). The primary objective is to train the AI model using these simulation outputs to predict the percentage of liquid fraction and MgO saturation based on chemical composition parameters. The AI model will undergo training with a comprehensive data set of simulations within the CaOMgO- SiO2-Al2O3 system, covering a diverse range of compositional at 1873 K. These simulations, conducted through FactSage™ 8.1 software, provide a robust foundation for AI model training, ensuring generalisability and precise predictions for the liquid fraction of the slag and the solid fraction of MgO, the solid fraction of MgO in this case is determined by the difference between the total MgO and the MgO in the liquid fraction, so it is not the objective of this study to determine which phase of MgO is in the solid state.. The predictive capabilities of this AI model hold significant implications for process optimisation, quality control, and decision-making in CaO-MgO-SiO2-Al2O3- dependent industries. Precise estimations of the liquid fraction and MgO saturation empower researchers and engineers to enhance operational efficiency and quality. This paper explores the methodologies employed for AI model creation and training, achieved results in terms of prediction accuracy, and potential applications in the field. The development of this AI system signifies a notable advancement in utilising machine learning for better comprehension and control of complex chemical systems. Furthermore, to align the study with real-world steel production, we introduce FeO and MnO at concentrations of 2 per cent and 1 per cent at 1873 K, respectively, following the validation of model results using the CaO-MgO-SiO2-Al2O3 system. This adjustment aims to bring the study closer to the observed reality in steel mills globally.

Jun 19, 2024

Safe, efficient production is a common objective for all large open pit mines. Despite comprehensive policies, procedures and regulations aimed at protecting workers, several people die each year in mining equipment-related collisions. The limited sightlines of heavy equipment operators coupled with difficult operating conditions are major contributing factors to the majority of mining equipment collisions. Off road haul trucks are the most common type of machinery involved in surface accidents. These vehicles represent the primary target for improving safety performance by mine operators. Although several commercial products have been introduced to address these issues, none have achieved significant market acceptance. The current collision avoidance solutions lack integration with onboard fleet management and equipment health systems. To achieve acceptance in industry, any collision avoidance system must offer high reliability, minimal false alarms, and value for money. With these criteria in mind, this paper will examine the pros and cons of the various technological approaches to collision avoidance in an open pit mining environment. The unique global positioning systems (GPS) and camera-based proximity detection solution on offer from Modular Mining Systems will be described. This solution uses intelligent filters to minimise false alarms. Tight integration with fleet management provides context information to enhance warnings and enable back-office near-miss analysis. Available today, this combination creates a practical solution to improve the situational awareness of heavy equipment operators, at a compelling price point. Future directions for maximising heavy equipment operator situational awareness will also be examined.

May 1, 2010

By J Foo, T Kleinschmidt, B Reynolds, K Kennewell

The consideration of complex supply chains often highlights multiple system bottlenecks that are localised and dynamic – they shift depending on what variability last influenced the system. Using the understanding of a dynamic system model, synergies between items that tackle localised bottlenecks can be understood to generate a suite of solutions. These can be simple solutions, such as a couple of new conveyors placed in series, or more complex ones, including buffer dynamics (capacity, location, behaviour, etc).Each solution in the suite will have an associated uplift in system performance and an associated cost of implementation. Dynamic simulations can address each situation in turn and estimate the projected improvement it would offer. However, these solutions will have different benefits when implemented together, and each solution will give different uplift depending on what other solutions have already been assumed. If the number of solutions is numerous, traditional dynamic simulation analysis becomes the bottleneck, limiting options analysis to the processing power available.This paper will illustrate the use of a new technique applied as part of a capital growth optimisation project with a major iron ore producer. Metamodelling is the creation of a model of a model; in this case study, the focus is on developing a response surface representing the suite of solutions. This can be achieved through a combination of dynamic modelling and an appropriate mathematical process called design of experiments. The result is an approximation surface of the outcomes of the dynamic model, encapsulating interactions between key elements of the value chain.This modelling approach provides a number of advantages compared to traditional dynamic modelling approaches, including but not limited to:early and rapid evaluation of a large range of potential solutionsaccommodation of multiple initial states of the value chainoptimisation of the overall suite of upgrades (down to route-level upgrades) based on business objectiveseasy re-evaluation of outcomes when key inputs such as costs change.CITATION:Kleinschmidt, T, Foo, J, Reynolds, B and Kennewell, K, 2015. Case study of iron ore value chain optimisation, in Proceedings Iron Ore 2015, pp 605–612 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By A Fern, A Hawkes, o

This presentation will cover: the importance of high-quality safety leadership; insights from a Safety Climate Survey that includes responses from 7903 employees working at 19 Australian mining organisations; the results of a critical control verification (CCV) coaching intervention; and recommendations for improving safety leadership in high-risk work settings. Safety climate is a representation of the deeper culture that exists in an organisation. Safety climate is predictive of behaviour, performance and reporting in organisations. Leaders play an important role in the establishment and maintenance of culture. Perceptions of safety climate were collected from 19 Australian mines (n = 7903 employees). These results indicate that the Australian mining sector is doing well in team support for safety and supervisor safety commitment. There were negative perceptions of willingness to report errors, employee involvement in safety initiatives, psychological safety and emergency readiness. Perceptions of safety leadership were in the fair range, with recognising behaviours perceived lowest, falling in the poor range. The underreporting rate was at 25 per cent indicating that 1 in 4 incidents are not being reported. Analyses exploring climate, leadership, safety behaviour and well-being will also be discussed. The integrity and success of critical risk management systems is often determined by the quality of safety leadership. Leaders need a mix of technical safety knowledge and interpersonal skills to be able to support the workforce to build critical control knowledge that invites open and collaborative discussions to find new or improved solutions. Forty leaders at a major mining operation completed training and 5-weeks of coaching focused on developing critical control verification competencies. The follow-up evaluation demonstrated significant improvements in relationship building, observation of controls and overall capability. Overall, insights from multi-organisation climate data and a prepost coaching intervention will be discussed and recommendations and practical guidance for leaders will be provided.

Apr 16, 2024

By Salehi M. R

Although inherent mineral matter appears to have no effect of the reflectivity of inertinite in the reflecting light microscope, it has a marked effect on the grey levels resulting from the backscattered electron response in the scanning electron microscope. Inertinite with a high inherent mineral matter content has a high grey level response but not as high as that of mineral matter. The highest grey level response is with inertodetrinite which at times could be mistaken for mineral matter. Fusinite has a higher grey level response than semi-fusinite. The backscattered electron grey level response corresponds to average atomic number and hence approximately to density. If a porous structure develops and becomes filled with mineral matter such as S, Cl, Ca, Si, and Al the grey level will be higher. Micrinite has an unusual response in that it behaves like an exinite maceral in the SEM rather than an inertinite maceral. It either has a low grey level when relatively free of inherent mineral matter, or a low grey level background with high level granules corresponding to Si and Al dominantly. Similar structures have been found in exsudatinite and resinite. It is thought that micrinite results from the migration of hydrocarbons out of exinite giving a porous structure which usually accommodates inorganic matter.

Jan 1, 1991

By P Allum

This paper presents a case study to reduce the operational cost on the secondary ball mill circuit in the Lead/Zinc Concentrator at Mount Isa Mines. The circuit includes two five-metre diameter ball mills each closed with a cluster of ten 15-inch cyclones. The operating cost for both ball mills is about six million Australian dollars per annum.The concentrator achieves 75 per cent of the plant design capacity with one ball mill operating, but will have to use two ball mills when 100 per cent plant capacity is required. The optimisation study on the circuit identified a new flowsheet that enabled the concentrator to reach 100 per cent of the capacity by using one of the two secondary ball mills. The success of the project utilised the existing equipment rationally and saved the operational cost for one ball mill at full concentrator capacity. A further simplified secondary circuit is proposed using the IsaMill for the secondary grinding duty. Performance of the IsaMill circuit and the potential cost savings are predicted.

Jan 1, 2002

By S N. Donaldson, B L. Hollis, K Wynn, L Potts, M Evans

A real-time load-haul-dump (LHD) dispatch optimisation tool has been deployed at Panel Cave 1 and Panel Cave 2 at Newcrest’s Cadia Valley Operations. The tool, known as ORB, is the first known successful implementation of an optimisation-based, autonomous, real-time dispatch tool, custombuilt for underground mining operations. ORB can co-ordinate the optimal dispatch of LHD’s in a block cave to achieve a range of objectives while adhering to draw compliance and geotechnical constraints. It is an example of highly automated short-term interval control. This paper starts by outlining the pre-existing business planning process, detailing the simple logic that produced the daily draw order. Next, the motivations for a real-time dispatch tool are presented, drawing comparison to the limitations in existing planning processes and how these can be overcome through an optimisation-based, autonomous, real-time dispatch tool. Subsequently, the paper details the Ratio Bogging Draw Strategy, through which tonnes targets are expressed continuously on draw bells or draw points as a ratio of total cumulative cave draw. This signifies artificial planning boundaries are removed and that draw targets are linked within a cave; such that tonnes are unlocked by bogging other parts of the cave, instead of as a function of time. This creates incentive within the target mechanism for fixing and bogging struggling draw areas whilst allowing uncapped progress if all draw targets are progressing within compliance. Furthermore, the optimisation tool developed is outlined, including the data it uses and the objectives it optimises. Finally, detail on the improvements to operations the implementation of this tool has brought, and the business process change it has facilitated are presented using Newcrest’s Cadia Valley Operations as a case study.

Mar 15, 2021

This study examines the application of Landsat TM data to the identification of hydro- thermal alteration in the arid terrain of the El Salvador region of north Chile. Numerical reflectance values were extracted from the digital Landsat TM data for a variety of rock surfaces, including four parts of the El Salvador gossan, for each of six spectral bands. These reflectance values were analysed statistically in order to select the three spectral bands, combined as a colour composite image, that are most efficient in discriminating different varieties of alteration and for general geolog- ical interpretation. The most cost effective com- posite image for this area is a combination of bands 1,4 and 7 as the blue, green and red components respectively, with simple contrast enhancement. This image is superior to some much more expensive enhancement techniques and allows unambiguous identification of areas of hydrothermal alteration larger than about 50m. The display includes a practical guide to the use of Landsat TM imagery for volcanic gold Exploration.

Jan 1, 1987

By M Davis

Increasing growth in the minerals industry over the past decade has raised the question of whether the standard of training for new geologists has been negatively impacted. This hypothesis was tested by means of a survey. Factors considered included the quality of training and whether it has changed over the past 50 years, preferred styles of training compared to styles of training received and whether the quality of training provided by a company changed with the type or size of company. Data from 435 survey respondents showed a consistent standard of training, but a significant increase in the level of responsibility allocated to new geologists. Those with increased responsibility also had reduced access to additional support and were often asked to perform tasks for which they had little or no training. New geologists were more likely to receive better quality training in a large company (over 100 employees) that owned the mine or exploration lease. A more structured training program was more likely to provide a higher quality result than those with minimal or no structure.

Aug 22, 2011

It is recognised by the current JORC (1999) code that resource classification involves the interaction of numerous qualitative and quantitative criteria such as data quality, geological continuity and grade continuity. No prescribed criteria and rules will work for all situations or even between different ore types within the same deposit. Also these criteria and rules are sometimes applied without a clear understanding of their appropriateness, accuracy or correct implementation. For these reasons case studies are useful to evaluate and compare criteria commonly used to assist in resource classification. In this paper blasthole data from a selected area of Joffre Member hosted ore of the Brockman Iron Formation at the Mt Whaleback orebody are used as the basis of a case study for the above-mentioned purposes. Iron grade, in per cent, is interpolated from a blasthole dataset into a block model using ordinary kriging. Samples are then removed from this blasthole dataset to produce a random sample grid, a semi-random sample grid and a regular sample grid. Using nearest neighbour, inverse distance squared, ordinary kriging and sequential gaussian simulation, block iron grades are estimated using these three blasthole data subsets as inputs. This provides four groups of estimates with the ordinary kriging estimate based on the complete blasthole dataset being considered to represent the true estimate of iron grades. Also generated during this process are estimates of the error for each block. These error estimates range from the simple, such as drill spacing, through to more advanced methodologies such as kriging efficiency and simulation. These estimates of grade and grade estimation error are then compared to the true estimate using graphs and statistics. In order of increasing accuracy the block grade estimation and simulation methods were nearest neighbour, inverse distance weighting, ordinary kriging and finally conditional simulation. The simulation in some instances doubled the accuracy of individual block grade estimates when compared to nearest neighbour and inverse distance weighting estimates. It was found that many methodologies for estimating the error of individual blocks performed equally well with only methods such as average drill hole spacing and classification by search ellipse pass number performing poorly. An approach on how to convert the abovementioned error estimates of individual blocks into a meaningful JORC classification is also discussed. Although advanced non-linear resource estimates are applicable, most iron ore mines are still using relatively straightforward methods. The use of blasthole data and some simple linear interpolation methods and simple linear based error estimates makes this study repeatable for most iron ore sites and their resource geologists. This style of investigation is recommended as a useful approach for the Competent Person to apply to their deposit and thus better select, implement and understand the criteria used for resource classification and provide more consistency and confidence in the resource classification process.

Jan 1, 2002

By Heyer T, Wasmuth H-D

The concentrator plant of Fahrica Mine, that started production in 1977, was using nine Jones wet high intensity magnetic separators (WHIMS) of the standard type DP 317 with a 1.5 mm gap width for the production of pelletfeed concentrate. These WHIMS units were operating in parallel with a feed rate of 110 t per hour, with about 47 per cent Fe in the feed, and with a maximum of only 0.8 per cent magnetite. The field strength was about 1.2 Tesla. From 1986, the mine has adapted its production facilities to mine and concentrate larger amounts of lowgrade itabintes to maximise the use of the available iron ore reserves. An increase of up to three per cent magnetite in the magnetic separator feed, resulted in a reduction of capacity. This was due to partial clogging of the separation boxes at high field intensities, which were required for the recovery of the very fine hematite. Even by lowering the feed rate and the field intensity the problem could not be resolved. After extensive testwork in a pilot plant, with a Jones separator model DI' 90, the commercial WHIMS plant was modified into a two stage process using the existing nine Jones separators. The gap of the first stage with four machines was increased to a width of 3.5 mm, corresponding to a maximum field intensity of 0.7 Tesla. This first 'medium intensity scalping stage' is followed by a second 'real' high intensity WHIMS step with five machines operating at the original settings with 1.5 mm gap width and 1.0 Testa maximum field intensity. Feed rates of up to 320 tons per hour in the first and up to 240 tons per hour in the second stage could be achieved. The design concept of the concentrator at Fabrica mine is described using the old and new flowsheets. Details of the pilot plant testwork as well as actual performance data of the new plant section are presented.

Jan 1, 1993