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By J Vann, S Dunham, M Job

Two-dimensional (2D) estimation approaches have significant advantages over three-dimensional (3D) approaches when dealing with a narrow vein- or layer-like geometry. The main motivation for 2D estimation is that bias due to non-additivity of grade is avoided. The various aspects of 2D estimation are illustrated by use of a case study from the 1A Shoot Nickel deposit at Leinster, Western Australia. The width of the 1A mineralisation is variable, and so are the angles of drilling intersection. Consequently, the variable of interest (in this case nickel grade) is not suitable for direct kriging because it is defined on non-uniform support. However, grade can also be defined as the ratio of two variables that are suitable for direct kriging: thickness and accumulation. In the 2D approach, tonnage equates to thickness and metal equates to the product of grade and thickness, also called æaccumulationÆ. In the simplest approach we can independently krige accumulation and thickness and derive the grade by the ratio of the two resultant estimates. The thickness and accumulation variables must be in a consistent projection orientation, for example a horizontal projection in the case of steeply inclined mineralisation like 1A. Because the density is not constant across the 1A (and most other) deposits, the issue of density weighting is also discussed. The impact of the correlation between grade and length, or grade and density are important issues in implementation of 2D estimation. The circumstances under which these correlations need to be taken into account (by co-kriging) are reviewed. Finally some comments are made on the final use of the resultant 2D estimate for mine planning purposes.

Jan 1, 2003

By G N. Musafer, M H. Thompson, R C. Wolff, E Kozan

The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when non-linear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bßrdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.CITATION:Musafer, G N, Thompson, M H, Kozan, E and Wolff, R C, 2013. Copula-based spatial modelling of geometallurgical variables, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 239-246 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

Physical model testing at Bergbauforschung is done in two rigs, a roadway rig and a longwall rig. The loading of such models, in scale relation to the con- ditions in the collieries provides valuable guidance to the probability and nature of failures, and thus to support requirements, in structural, roofbolts and self- auvancing supports. The success of such modelling when related to subsequent underground designs put to use suggests that such methods of investigation could be extended to pillar extraction problems also.

Jan 1, 1974

By M Akop, G Phillips, L Elliott

An estimation geologist has many tools in their kit and using the correct one for the job is vital for creating a useful model. Reconciliation is a key step to monitor the performance of a resource model and to ensure the correct tools have been selected and appropriate parameters are set. This paper presents an example of refining the estimation methodology for a Channel Iron Deposit (CID), resulting in an improved model. Rio Tinto Iron Ore (RTIO) CIDs are unique iron ore deposits located in the Pilbara region of Western Australia and contribute a significant volume to the world’s seaborne iron ore market. A problematic feature of these deposits is the irregular dispersion of clay pods that cannot be delineated with confidence within the resolution of the exploration drilling. Resource to grade control reconciliation showed an over-prediction of high-grade material in the resource model. A fresh approach was required to improve grade and tonnage predictions. Historically, clay pods were delineated using traditional wireframing techniques and estimated using ordinary kriging with hard boundaries. The new method utilised indicator kriging to estimate the probability of clay. Probabilities generated from the indicator kriging estimate were used as an additional weighting following the ordinary kriging of grades. Results showed indicator kriging improved global high-grade tonnes reconciliation, however, as expected, it did not improve the spatial prediction of clay. Based on improved reconciliation results indicator kriging has now been adopted as a suitable alternative for analogous CIDs at RTIO. These improvements benefit the mine planning process, but do not replace grade control models.

Mar 22, 2022

In this paper is given a description of the flotation plant recently erected by Broken Hill South Limited at the South Mine, Broken Hill, N.S.W. It has been built on the site of the old flotation plant, which was described in a previous paper published by the author. The present paper is supplementary to the former paper in that it replaced the following sections thereof, namely, those from end of the second paragraph, page 269, to the end of the first paragraph page 282, and from the end of the second paragraph, page 284, to the end of the third paragraph, page 302.The roll crushing, fine grinding, gravity concentration, filtration, disposal of products and sampling in the new plant are the same as described in the above mentioned paper.The reconstruction of the flotation section, described herein, completes the reconstruction and modernisation of the treatment plant which was begun in 1928. A description of these earlier alterations has already been published in the Proceedings of this Institute.

Jan 1, 1935

It would be a good thing when reviewing the challenges to be faced by the Australian gold industry to set the backdrop and scene for them, by briefly examining the history of this vital and dynamic industry in the Australian context. Gold mining in Australia had its official beginnings in 1851 when John Lister and William Tom discovered gold at YorkyÆs Corner, later renamed Ophir by Edward Hargraves. From that first tentative beginning, the ensuing rush of prospectors into New South Wales and Victoria meant that the annual gold production in those early years surpassed that of the next 40 years. This early rate of production was only eclipsed when AustraliaÆs production was once again lifted by the discovery of gold on the other side of the continent, in Western Australia. (Figure 1). The years leading up to the First World War saw Australian production peaking once again at over 115 tonnes of gold, a production rate that would not be surpassed until 1988. This renaissance in production at the beginning of the 1980s was achieved by the application of technology. The advent of bigger trucks and shovels meant that earth-moving costs dropped dramatically. This, coupled with the highly effective and efficient carbon-in-pulp processing route, stimulated the Australian gold mining industry into a state of frenetic activity. These two innovations were the principal factors that enabled the economic exploitation of the lower grade haloes left by the æold-timersÆ around the deposits exploited at the beginning of the last century-no high finding costs here. AustraliaÆs production through the 1980s and the early part of the 1990s was largely supported by the exploitation of these haloes. As these were depleted, the aggressive exploration effort stimulated by the strong cashflows of these early oxide deposits resulted in new æblindÆ discoveries which are now emerging as the backbone of the Australian industry (Figure 2). Gold production is a major contributor to the Australian economy. In 1998/99 the Australian gold industry accounted for approximately 16 per cent of the value of all mineral exports, which in turn accounted for over 35 per cent of AustraliaÆs total exports. As such, the Australian gold industry, by itself, accounts for just under six per cent of AustraliaÆs total exports (Figure 3). Consequently, the industry is responsible for over one per cent of AustraliaÆs gross domestic product. These statistics are all the more compelling when we consider that, at the beginning of the 1980s, goldÆs contribution to exports and GDP was insignificant (Figure 4). Within the Australian resources industry, gold mines and associated infrastructure account for ten per cent of all capital expenditure (Figure 5). From an employment point of view, in 1997/1998 the industry directly employed (excluding contractors) about 7700 people, approximately 15 per cent of all those employed in the minerals industry. Just under nine per cent of the workforce in the minerals industry are female, whereas in the gold industry over 16 per cent are female.

Jan 1, 2000

By D Fargher

BHP BillitonÆs Cannington operation began production in 1997 and is presently the largest tonnage and lowest cost single mine producer of both lead and silver in the world. The original design capacity was 1.5 Mtpa and this has progressively increased via a series of debottlenecking projects in both the mining and milling operations. In 2003, 2.39 Mt of ore was mined, whilst 2.31 Mt of ore was milled. In February 2003 Cannington received approval to expand the project to a sustainable capacity of 2.4 Mtpa. This resulted in underground development into the northern zone, upgrades to the concentrator, increased accommodation at site and power station capacity. The Cannington project development team implemented a partnership approach to the project. Fraser Osborn Engineering and Outokumpu Technology worked closely together with the Cannington team to meet all of the project constraints.

Jan 1, 2004

By Wang S

Fragmentation is the basic concern in rock blasting and serves as the main measure of blasting effectiveness. A good estimation of fragment size distribution before blasting is very useful and helpful for selecting the proper equipment for loading, transporting, and crushing rocks. A fragmentation model is presented that is based on a hole by hole analysis and correlates the rock properties, burden, spacing, and explosive column with the blasted volume and fragmentation obtained. The drill bench is divided into three separate areas corresponding to different breakage mechanisms. They are: 1) a main breakage or casting area, 2) a secondary breaking area, and 3) an overbreak area. The boundary of the main breakage area is found from the magnitudes of strains in the stress waves and the tensile strength of the rock. The secondary breaking area is determined by stress wave reflections at discontinuities and interactions between colliding stress waves from adjacent boreholes. The overbreak area is that beyond the main breakage area "where the reflected tensile waves no longer break the rock. This analysis is applied on a hole by hole basis to locate the breaking points. Then connecting the breaking points on each side of a borehole forms the triangle of the main breakage area. This is repeated for the next hole and the remaining area is the secondary breakage area. After the angle and area for each hole are found the Kuz-Ram model is used to predict the fragmentation size distribution for each hole. Then summing up the size distribution for each hole gives the total fragmentation distribution. This analysis has been successfully applied to field tests performed in a limestone bench where the entire spoil pile was screened to determine the fragment size distribution. Knowing the explosive and rock properties the breaking area was found for each hole, the strain and stress values, the breaking point, and angle of breakage (104 degrees). The fragmentation size distribution was then calculated and compared to the field data with excellent agreement.

Jan 1, 1990

Batterham and Algie began their paper on: `The role of technology in the minerals industry' (1995) by noting that while: it is often stated that innovation is central to the economic survival of mining and minerals processing in the face of global competition, .. . technology is often far from a core strategy in our industry. This point is correct. Throughout the world, as a broad generalisation, mining companies do not value technology development as a principal means of gaining competitive advantage. It is important to understand why this is the case. Batterham and Algie address this question by making distinctions between innovation, technology and research. They note that while: all successful (mining) companies are good at innovation . . . that innovation can proceed without any research and development and that it is innovation that generates the competitive advantage, not research and development per se. In this paper we accept these arguments. However, our focus is somewhat different. Whereas Batterham and Algie took a mining company's perspective on the technologies of mining and processing, we take a broader view of the opportunities for technology development for company Australia but, in order to focus the argument, we restrict our discussion to the area of mining (rather than processing); we focus particularly on mining systems and mining equipment. We begin by looking at the motivation of companies operating in any industrial sector to invest in research and development. Figure 1 recognises four levels of industrial maturity. For companies in the embryonic and growth stages R&D often is essential to initiating and developing the business. Mining, on the other hand, is a mature industry. In mature industries the conventional roles for R&D are to reduce costs, to extend product differentiation, or to develop new technology with the aim of rejuvenating the business. Next we ask whether these general-industry arguments apply to the mining industry. If they do then the mining industry should value R&D more highly; after all cost reductions and business rejuvenation are goals that are worth achieving. On the other hand if, for whatever reason, these general arguments do not apply to mining then this may lead the mining industry to invest only modestly, or not at all, in R&D. In this event, while this may be a rational decision for the mining industry, it may not be in the best interest of a nation like Australia where revenues from the sale of mineral products represent an important part of the country's economy.

Jan 1, 1997

By J Q. Shi, M Karakus, Y Liu

Predicting the spatial distribution of rock mass properties in cave mining is a critical challenge. In this study, we introduce a novel machine learning-based model to advance our comprehension of rock behaviour. This model specifically focuses on the spatial distribution of rock mass and mechanical properties, a crucial aspect of our understanding of rock mechanics. Our model is inspired by the recognition that neighbouring information serves as crucial prior knowledge for predicting the spatial distribution of these properties, wherein closer neighbours are likely to exhibit similar characteristics. To effectively capture and model these neighbour relationships, we design a neural network-based model to map the spatial locations within the data set into a new highdimensional space. Within this transformed space, we utilise Euclidean distance to identify N neighbours. Leveraging these neighbours, we introduce a straightforward yet highly effective approach—label propagation—to construct a graph that illustrates neighbour relationships. This graph not only facilitates the prediction of the spatial distribution of rock mass properties but also offers a measure of uncertainty for these predictions. We validate the proposed method using a real rock data set and showcase its efficacy in capturing intricate relationships and distributions within rock properties, enabling precise predictions across diverse spatial scales. Our results underscore the potential of machine learning-based approaches to revolutionise the field of rock mechanics, providing valuable insights applicable to geotechnical engineering, mining, and other sectors where an accurate understanding of rock properties is paramount. This model has direct practical implications, offering a new tool for geotechnical engineers and mining professionals to enhance their understanding and prediction of rock properties, thereby improving safety and efficiency in their operations.

Sep 1, 2024

By T Craske, J Sykes, T C. McCuaig, M Jessell, A Trench

The prevalent strategic approach in the mining industry is one of planning. However, it is widely recognised that planning does not work in complex and uncertain situations (Mintzberg, 1994), such as those associated with ‘above ground’ non-technical orebody complexity (Trench, Packey and Sykes, 2014). Mintzberg, Ahlstrand and Lampel (2009) suggest the focus instead should be on strategic ‘thinking and doing’ and using the many ways to think about strategy to make sense of complex, uncertain, and unique situations. They therefore place great value in cognitive flexibility. Scenarios development utilizes several different thinking styles and thus assists with this type of flexible strategic thinking (Figure 1). The ‘Centre for Exploration Targeting (CET) Scenarios’ were developed with the ‘Oxford Scenario Planning Approach’ (OSPA) (Ramírez and Wilkinson, 2016). The OSPA aims more to improve the thinking skills of decision makers, rather than forecasting per se (Wack, 1985a, 1985b). As such, this paper focuses less on the content of the scenarios and instead on the practical value of scenarios in strategizing. CITATION: Sykes, J, Trench, A, McCuaig, T C, Jessell, M and Craske, T, 2018. Strategic thinking about long-term ‘above ground’ orebody complexity using scenarios, in Proceedings Complex Orebodies Conference 2018, pp 60–64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 21, 2018

The sinking of the new No. 3 Shaft being mainly concerned with providing for the continuation of mining operations north of the existing workings, requirements for the shaft and haulage equipment were assessed, having in mind the anticipated needs of the Company in future years, the .available knowledge and probable future trends of the orebody, and also that the shaft would be required to act as a downcast airway for the ventilation system associated with the northern underground workings.

Jan 1, 1957

By D Hope, D K. Mukhopadhyay, J D. Harvey

South32 (S32), a globally diversified mining and metals company, is listed on securities exchanges around the world (ASX, JSE, LSE), with its primary listing being on the Australian Securities Exchange (ASX). Chapter 5 of the ASX Listing Rules (Australian Securities Exchange (ASX), 2019b) requires a mining entity to provide a summary of governance arrangements and internal controls with respect to its estimation processes, estimates and reporting of Mineral Resources and Ore Reserves annually. As a global company, it is also important to design and implement all governance processes and internal controls which can be used consistently across the organisation. The three lines model (previously known as the ‘three lines of defense’ model) is employed across South32 to manage risk where the first line (Practitioners) designs, implements and executes processes and controls to manage risk; the second line (Stewardship) identifies material gaps and improvement opportunities in the first line by monitoring conformance with the group requirements, legislative and regulatory obligations. Second line also assists with the development and improvement of core fundamentals based on industry good practise. The third line (Group Assurance) provides independent and objective assurance over the Group’s system of risk management and control. The estimation of resources and reserves for most of the operations within South32 is managed by the Planning function. The estimation process is part of the annual Life of Operation Plan (LoOP). The LoOP identifies and assesses the strategic alternatives for the development of an operation and recommends the preferred pathway based on value and risk. The LoOP starts with opportunity framing and the updated resources as an input and ends with the short-term plan and annual budget (the outputs). Ore Reserves estimates are one of the outputs from the LoOP. All the inputs and outputs follow internal standards and procedures which includes peer review and performance reconciliation. Stewardship (Second line) which is a centralised function has standards in place to ensure compliance to internal controls and external regulatory requirements. This includes assessment of the competence of Competent Persons, technical reviews, independent audits and training in the relevant chapters of the ASX Listing Rules, Guidance Notes and Appendices. Group Assurance (Third line) which reports to the Risk and Audit Committee of the Board of Directors ensures the design and operating effectiveness of the processes, standards and procedures associated with the estimation and reporting of resources and reserves. While the level of scrutiny has a different intent for each line in the three lines model, the overall purpose is to achieve a consistent outcome across the organisation

May 24, 2023

Two characteristics of the modern mining industry are that there is a skill shortage and that young professional people rise rapidly into highly responsible supervisory positions. With this responsibility comes the burden of identifying and managing health and safety risks. Without the benefit of a comprehensive health and safety training program, these young professionals may be putting both themselves and those under their supervision at risk. The Moura Mine explosions and the asbestos health disaster should not be just artifacts of history, but highly valued lessons that impress the need for comprehensive health and safety risk management strategies on young professionals. From the perspective of the former secretary of the Committee to implement the findings of the Moura (Disaster) Inquiry and as the former coordinator of the Coal Workers Health Scheme, key issues in occupational health and safety management systems are explored.

Jan 1, 2005

By Beamish B. B

In this study, a systematic examination of the scale and variety of micro-structures in coal using Scanning Electron Microscopy (SEM) has been carried out, using coal samples of differing stages of coalification from the Bowen Basin and New Zealand. SEM provides detail of various micro-structural features and shows that a variety of micron-sized fractures and cavities are present in coals. These are differentiated into three pore types: fracture porosity, phyteral porosity and matrix porosity. Fracture porosity is generally associated with bright coals (although it has been shown that micro-fractures are present in maceral fragments from the dull coal layers). Characteristically the macro- and micro- fractures form a continuous structural fabric through the bright coal layers and thus make a significant contribution to overall permeability. The macro- and micro-fractures appear to have been formed during the process of coalification rather than being formed due to shrinkage during methane extraction, as most of them are infilled with secondary minerals. In contrast, phyteral and matrix porosity is associated with the dull coal layers that are composed of plant fragments or a heterogeneous mixture of macerals. Like the macro- and micro-fractures, the continuity of the observed cavities suggest that these too are a significant contribution to overall permeability, and therefore play a major role in the transmissibility of methane at a level between diffusion at the micropore level and laminar flow at the macro-fracture level. Due to different spacing, orientation and persistence of individual fractures and cavities, the rate of methane transmissibility through a coalseam will vary according to coal rank, coal type and the organic precursors from which the coal was derived. This is important as a knowledge of the micro-structure system and its relationship to coal type and coal rank, plays an important consideration in: a) gas drainage modelling, b) enhancing permeability by inducing fractures and c) predicting the occurrence of outbursts.

Jan 1, 1991

By H Stedman

Integrating exploration and operational blastholes into one database significantly enhances geological modelling. Benefits include: improved coal predictions, stronger interpretation of structurally complex areas, detailed mapping of heat affected coal aureoles and additional roof accuracy for blast designs that deliver better coal protection.CITATION:Stedman, H, 2014. Integrating blastholes into exploration data to improve coal recovery and modelling, in Proceedings Ninth International Mining Geology Conference 2014 , pp 237–242 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

Process mineralogy is an inter-discipline in the fields of mineralogy and mineral processing. As a predicting and trouble-shooting tool, process mineralogy helps address all mineralogical issues and problems related to mineral processing. It provides useful information on process design and optimisation, flow sheet development and cost reduction. As more and more complex and refractory ores are being discovered and processed, it is believed that process mineralogy will gain more attention and play a more important role in process design and optimisation. This paper will first discuss the scope of process mineralogy and mineralogical factors that may affect mineral processing of various ores, and then focuses on the application of process mineralogy in process design and optimisation through case studies.

Jan 1, 2008

An automatic control system of a longwall roof support is dis-cussed. Hydraulic automatic control systems for longwall roof support have not met all requirements for such systems. Utilization of standard hydraulic elements to form a system that would-comply with all demands leads to a very complicated structure with a large number of hydraulic hoses within and between adjacent supports. So, only simplified systems have been made. This paper describes the multifunctional valve that per-mits realization of any desired logic functions, while maintaining a com-pact form, and analyses its application as a fully hydraulic automatic control system of a roof support.

Jan 1, 1985

By A Giyose, V Malysiak, K Davey

Batch flotation tests were conducted on a haematite-bearing Sishen iron ore slimes sample from South Africa using reverse cationic flotation. The effect of grinding on flotation performance, the flotation response of various key impurities in the sample, and the feasibility of increasing metal recovery by refloating tailings in a scavenger flotation step were investigated. The test results indicate that reverse cationic flotation is effective in rejecting impurities from the iron ore sample tested. From a head grade assaying 6.4 per cent SiO2, 2.14 per cent Al2O3, 0.402 per cent K2O, 0.082 per cent P and 0.194 per cent TiO2, the levels of impurities were reduced to 1.83 per cent SiO2, 0.88 per cent Al2O3, 0.095 per cent K2O, 0.066 per cent P and 0.174 per cent TiO2 in the final concentrate at a Fe recovery of 74 per cent. The flotation response of SiO2, Al2O3 and K2O were found to be better than that of P and TiO2. The testwork demonstrated that grinding to 80 per cent passing about 49 microns is essential for upgrading the Sishen iron ore to produce >67 per cent Fe concentrate grade. This grind size corresponds to about 80 per cent liberation of haematite from the gangue minerals. Fe recoveries up to 76 per cent were obtained by refloating the rougher tailings in a scavenger stage, with little effect on the final concentrate grade. Size-by-size Fe recovery data obtained indicated that particles below ten microns were mostly lost in the desliming stage conducted prior to flotation whilst some reported to the froth by entrainment. Some of the coarser haematite-gangue composite particles reported to the froth product by genuine flotation.

Jan 1, 2009

By H Parra, D Zenteno

Fragmentation modelling has been in use in the mining industry for a long time; however, there are still some aspects to tackle with regard to its use for strategic/planning and day-to-day purposes.On one hand, an important amount of resources are allocated to the task of calibrating and validating a good fragmentation model. Nonetheless, errors during the implementation stage introduce uncertainty into the prediction.On the other hand, it is common practice in the mining industry to use only discrete values to represent the fragmentation from blasting (k20, k50, k80), which provides a biased interpretation of the situation as, for instance, the best and worst possible cases are not taken into account. This is particularly critical when a continuous improvement philosophy has been adopted and modelling is used to either modify the drilling and blasting designs or plan ahead.It is well known that every site has particular conditions (rock mass, equipment, drilling and loading practices, among others) that often define unique trends in implementation. These trends can be captured using statistic and probabilistic techniques and then used as proxies for further analysis.This paper explores the potential of including implementation data in the form of probabilistic distributions into the Swebrec model to improve the performance of this engineering tool during the decision-making process.The fragmentation results of four designs were modelled using three different degrees of accuracy in the implementation for the burden, spacing and explosive column length.The data analysis showed that the probabilistic approach helps to achieve a broader perspective regarding the fragmentation that it is possible to obtain and the implications for the subsequent processes. The analysis also showed that the likelihood of producing similar fragmentation with different designs (involving different powder factors and costs associated) increases with the variability of the implementation.CITATION:Parra, H and Zenteno, D, 2015. Evaluating the inclusion of the implementation variability into fragmentation modelling, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 121–126 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 24, 2015