Search Documents

By A Galli

Traditionally pit optimisation and scheduling is carried out assuming that the resources, the commodity prices and production costs are all known. Once the pit contour and the mining schedule have been determined, geostatistical simulations can be used to assess the impact of the uncertainty in the resources on the pit design and the schedule, and likewise stochastic simulations can be used to test its robustness to fluctuations in costs and prices. But it would be more interesting to have a dynamic procedure for optimising the pit as the resources become better known and as economic factors such as commodity prices and costs evolve over time. This paper presents a novel approach for doing this. Rather than working with millions of small selective mining units, it was decided to work with large blocks, called macro-blocks. Mining sequences are defined as the quantities to be extracted from each macro-block in each time period. Feasible mining sequences are mining sequences that respect the accessibility constraints, and also the geometric constraints on the amounts that can be extracted from any one block over time, or from all the active blocks at a given time. Having defined feasible mining sequences, their mathematical properties were studied. It was found that natural breakpoints occur in the sequences when one set of blocks have been completely mined out, thereby opening up access to others. It was discovered that families of sequences exist, and that they are convex and closed under certain types of row permutation operations. Convexity is an advantage when optimising. The closure property opens up the possibility of mixing and matching subsequences of rows in the sequences. Another interesting property is that the sequences form branching families, rather like the binomial and trinomial trees used to model prices in finance and in real options.It is easy to generate large numbers of feasible mining sequences randomly. A two-step procedure is used to find the best one (or the best few) using three economic criteria: expected NPV,the probability of a negative NPV, and the percentage of years when the cash flow is negative. The procedure was tested on a synthetic gold mine based on the characteristics of the Essakane mine in Burkina Faso. The results were encouraging.

Sep 26, 2011

By E M. Wightman, C L. Evans

A recent survey of mineral processors undertaken as part of the International Mineral Processing Council (IMPC) Education Commission identified mineralogy as one of the key skills required for mineral processors (the other key areas being comminution, flotation, physical separation, sampling and extractive metallurgy). Past experience in a number of operations has shown what can be achieved when the data outputs from mineralogical tools are coupled with people with the right skills who can transform the data into actionable information. This paper reviews what has been done successfully in plant operations over a period of more than four decades and gives examples of a range of applications with both long and short-term objectives. The examples demonstrate the usefulness of mineralogical data – both basic and complex – in optimising mineral processing operations, whether the data are applied in a simple analysis or in more complex modelling. Similarly, the examples show the range of options available for operations to access the mineralogy information they need – through in-house experts and equipment based in centralised technology centres, through on-site equipment and experts or through external laboratories and consultants.The examples from industry highlight the huge potential benefit of including mineralogy as an integral part of operational best practice and raise the question of why more operations do not utilise what should be readily available data. Successful application of mineralogical data requires skilled people to generate relevant data of the required quality, together with skilled people to interpret the data (this may be the same person). And, as in any project, corporate recognition of the value of this approach to best practice is required to ensure continuing support. With fewer university courses providing courses in process mineralogy to undergraduate mineral processing engineers and chemical engineers, there is an increasing lack of knowledge about what mineralogical information is needed, how to get the required data and, equally importantly, how to turn the data into useful information.CITATION:Evans, C L and Wightman, E M, 2018. Understanding minerals in mineral processing – the basics and beyond, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 363–376 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

By R Berry

This paper looks at two ways to estimate the bulk mineralogy of the rocks for assay intervals. The aim is to find an efficient indicator of the most common minerals in the rock. Phase (modal) analysis has traditionally been done using visual methods such as point counting and image analysis. A modern version of this process is the X-ray point counting routine using the SEM-EDS based software. These methods are too slow and expensive for routine analysis of bulk sample mineralogy at the normal assay spacing.Two sources of data were considered that provide information that can be used to determine the mineral abundance in assay samples. The most widely applied method is (semi-) quantitative X-ray diffraction (QXRD). The QXRD method is most applicable to major minerals and has limited application to minerals at low abundance. The nominal detection limit is 0.5 per cent. Values below five per cent have large errors. A second, less common, method is calculation of mineralogy from chemical assay data. Conversion of chemical analyses to mineralogical analyses depends on the unique chemical composition of each mineral. Elements only found in one mineral are easily accounted for, but many compositions are ambiguous. Deciding on the actual mineralogy is not simple. Recalculation of mineral mode from chemical analyses is more accurate than QXRD when the correct minerals, and mineral compositions, are known.Where only a few QXRD analyses are available they can be used to setup a protocol for calculation of mineralogy from assay data. Linear programming works well in this environment. The best results are obtained when both H2O and CO2 are directly measured. Loss-on-ignition (LOI) should be included if these are not available.Where both QXRD and chemical analysis are available for all samples, the best results are obtained using the least squared method to merge the data sets assuming QXRD has much higher analytical errors than chemical assays. The combined method provides more robust results because the high abundance minerals are controlled by the QXRD measurements while the chemical assays improve the precision for low abundance minerals

Sep 5, 2011

By A K. Ghosh, J Chung, E Topal, M Asad

"Many open pit (OP) mines with considerable vertical extent are approaching the end of their life-of-mine; some of them are seeking the opportunity to make the transition from OP to underground (UG) mining. The decision on the best location for transition from OP to UG mining should be addressed at the strategic mine planning stage. Conservatively, the transition to UG mining is considered near or after the exhaustion of the reserve within the ultimate pit.However, if UG is evident and exclusively viable from the inception, defining the best location for the transition through a conservative approach may not be an optimal option to explore. This clearly establishes the need for a mathematical model that aims to maximise the project value and considers OP and UG mining with crown pillar (CP) requirement simultaneously. Underground mine layout varies from one UG mining method to the other, and consequently the variation in the location of transition is eminent. Thus, focus on the selection of UG mining method must be a part of this analysisThis paper presents an implementation of an integer programming (IP) based mathematical model that evaluates the changes in mining layout and the project value under possible variation in the transition point from OP to UG mining for stoping and block caving methods. An IP problem is a mathematical optimisation or feasibility method in which some or all of the variables are restricted to be integers. The outcome of the implementation reflects that mining strategies with OP transition to stoping and block caving methods generated higher values than OP-only mining strategy. The case study not only demonstrates the difference in mining layout for both stoping method and block caving method, but also reflects that a joint consideration of OP mining, UG mining and CP placement helps to achieve maximum project value and resource utilisation.Citation:Darbritz, J, 2016. Remediation of Wall Failure at Kalgoorlie Consolidated Gold Mines' Golden Pike Cut-back 2016, in Proceedings Ninth AusIMM Open Pit Operators' Conference 2016, pp 96–103 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 15, 2016

By P Church

What is the best method of splitting a sample from a reverse circulation drill rig? How important is it to obtain a correctly split sample? What is the impact of an incorrectly split sample? These are just a few of many questions asked daily in the mining industry with regard to sampling. Modern sampling theory is well described in the literature in texts and is taught in short courses throughout the world, however little has been published on the relative performance of sample splitting devices used in the field. This paper compares the performance of the Jones tiered riffle splitter with a cone splitter manufactured by SGS Metal Craft in Western Australia. The testwork was carried out at AnglogoldÆs Sunrise Dam Gold Mine, 55 km south of Laverton in Western Australia. Mineralisation at Sunrise Dam is hosted in a structurally complex framework of shear zones with dips that range from steep (70¦) to shallow (25¦). The deposit is characterised by significant amounts of coarse gold, which presents a challenge in sampling, analysis and grade estimation. The three major areas where sampling errors can occur are in drilling, sampling, sample preparation and analysis. Sampling errors attributable to drilling and sample preparation often far outweigh the errors made at other stages in the process, however historically most effort to identify sampling errors has concentrated on the laboratory and analytical procedures. Splitter design and cleanliness can have a large impact on sample collection and preparation. Splitter performance was tested with respect to sample weights, particle size distribution, and gold grade consistency. The aim was to determine if each particle has an equal probability of being sampled, the resulting sample has integrity, and if any segregation problems occurred. The cone splitter was found to provide the best split in terms of particle size distribution, with no apparent size bias. Duplicate samples had more comparable masses than those provided by the riffle splitter. Most importantly, the cone splitter gave less grade variability between duplicate samples than the riffle splitter. Testwork also confirmed that, like the riffle splitter, the cone splitter must be oriented vertically and the design of the rig or cone splitter trailer should accommodate this requirement.

Jan 1, 2003

By J E. Everett

When ore is being selected from a regularised block model, a common procedure is to accept as ore any block whose iron content exceeds a cut-off value, and whose content in each contaminant analyte is below an appropriate cut-off value. This method defines a quadrant within the multidimensional analyte space, such that any block lying within the quadrant is accepted as ore and any block lying outside the quadrant is rejected as waste. The cut-off levels can be adjusted to maximise ore tonnage at a target grade (or analyte vector). When the method is applied to a project comprising multiple pits with systematically differing grades, it is found that ore tonnage at target grade is maximised if different cut-off quadrants are used for the different pits. This is apparently illogical, because it implies that an ore block from one pit may be accepted as ore, but an identical block from another pit is rejected as waste, even when ore from both pits is to be blended into the same product and there are no production cost differences between the pits. The paradox is an example of the ætheory of the second bestÆ: if there are multiple conditions for optimality and one condition is broken, then obeying the other conditions may not be the best policy. The problem lies with the quadrant cut-off method, which is shown to be inconsistent even for selecting ore from a single pit. A criterion that is inconsistent cannot be optimal. It is shown that a linear composite cut-off function provides maximum ore tonnage, and that a single composite cut-off criterion is consistent and optimal over multiple pits. Further, it is shown that a composite cut-off function not only maximises ore tonnage at a specified composition, but also can be used to select ore so as to maximise project value, if marginal costs and values are available.CITATION:Everett, J E, 2013. Selection of ore from multiple pits, in Proceedings Iron Ore 2013 , pp 185-192 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 12, 2013

By I Cameron

Simulation is increasingly being used to analyse mineral processing operations and explore efficiency options. Engineers that use simulation are rightly concerned with the quality and applicability of the underlying models. However, many of these models have a significant empirical component, and the best structure for this component may not be apparent. There is an opportunity to improve the quality and application range of these models by exploring potential structures for this empirical element. One approach to this problem is the use of structural optimisation, which is a formalisation of the model development process. This method searches through a family or hyper-structure of candidate models for a model that is optimal with respect to some measure of model quality. This method has been applied to the modelling of an industrial flotation circuit. The result was a model that was a significant improvement over a number of standard models reported in the literature. Structural optimisation provides a method to compare potential models in a systematic and efficient way, and hence to improve the structure of process models.

Jan 1, 1998

By D T. Ribeiro, J F. C L Costa, J C. Koppe

Drilling and sampling are responsible for most of the costs during mineral exploration, especially in multi-elements and polymetallic deposits, such as iron, manganese and bauxite deposits. On these deposits, often it is necessary to estimate multiple attributes at several granulometric fractions, ie distinct particle sizes. This paper investigates the effect of sampling at a close spacing grid only the head grades for the multiple chemical species in iron ore deposits. The remaining required data at the various grain sizes are sampled at a sparse grid. The derived geological model is checked for precision and accuracy comparing the output obtained against a model obtained using a complete isotopic data set including head grades and chemical analysis at each granulometric fraction analysed at all sampled positions. Among the several tested alternatives, the best procedure for dealing with the posed problem involved utilising the correlation coefficients between the grades at distinct fractions to obtain an isotopic database prior to interpolation. Cokriging was the method used, based on the intrinsic coregionalisation model. Estimates were obtained with the quality needed for the proposal of the study. Results showed that at least 50 per cent of the blocks were estimated with errors less than ten per cent relative to the grades obtained at the reference model, using only 15 per cent of the granulochemical data employed to obtain the reference model. The methodology also preserved the correlations between the attributes in their several granulometric fractions on the estimated model.

Sep 26, 2011

By S McKinley, S Juras, E Uludag

More and more, today’s mining geologists are asked to identify and create 3D value domains for multidisciplinary usage: grade definition, geometallurgical performance and geotechnical characteristics, to name a few. Often, that domain shape is the result of an assumed or conjectured value as a surrogate to a set of conditions (eg kaolinite-rich, sericite alteration). Would it not be instead better to create the respective domain through identification of a consistent quantifiable geologically-based pattern as its basis?Critical to the identification of patterns is the transformation of 3D point data into a model by a method that uses few, if any, preselected thresholds. Too often we complicate the reviews of the modelled data by prejudging the value range of interest. And when we do revert to 2D views (ie sections and plans), we tend to only examine numbers or line traces. These hinder and obscure identification of geological patterns particularly in deposits of complex geology. Instead, these data should be looked at with minimal prejudgment and interrogated in 2D space by one of the best and most eye-catching display types: filled contour plots.Here we present two different processes that transform data with minimal preselection into formats that allow for pattern recognition by filled contour plots. These are: probability assisted constrained kriging (PACK) and multiple interval interpolant formation (Aranz Geo’s Leapfrog® software). The former creates a 3D model of probabilities on a threshold value; the latter creates numerous (=10), regularly-binned 3D interval interpolants. The results of each method are examined as filled contours over numerous sections or plans. Any distinct patterns are quickly discerned thereby readily identifying the best value to base the creation of a domain. These processes therefore provide a way to marry recent advances in software tools with what is supposed a geologist’s core skill: pattern recognition.CITATION:Juras, S, McKinley, S and Uludag, E, 2017. Pattern recognition in transformed data – the search for domain shapes in mine geology data, in Proceedings Tenth International Mining Geology Conference 2017, pp 37–42 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

This paper presents an overview of a program PC-BC developed for application to the design and evaluation of block cave operations. Conventional mine planning software tools are not well suited to the evaluation of this type of deposit. The paper looks at the modelling approach as applied to a block cave mining project. The following steps are described:Initial preparation of data including block models, draw point footprint geometry and draw cone geometry. Computation of individual draw point reserves. Procedure for modelling of vertical mixing of material within each draw point and subsequent determination of the best height of draw for each draw point based upon an economic cut-off value. Smoothing of draw heights amongst neighbouring draw points to produce a realistic draw envelope. Mineable reserves within the envelope are then computed. Tools for preparation and evaluation of various production schedules. This includes definition of draw rates, and rates for commissioning new draw points. In an operating mine, the capture and analysis of daily draw tonnages is important. How PC-BC accommodates this is described as well as the processes for depleting the draw column reserves. In the 12 years since the program was first developed, it has been used on a number of projects for feasibility studies and operating mines. Some practical examples of the use of the program in these projects are presented. Finally, some commentary on the sensitivity of various parameters is presented. Particular emphasis is placed on the overall footprint design.

Jan 1, 2000

By K Ehrig, V Liebezeit, E Macmillan

The results from metallurgical test programs are used in feasibility studies for design of new plants and brownfield expansions, in long term mine plans, and to make decisions in an operating plant. There are many elements which contribute to a well-constructed test work program. Ultimately, understanding the accuracy and precision of the test work results is critical to ensuring good decision-making at various phases of a project.Every resource drilling and associated assaying program will have a quality assurance / quality control (QA/QC) component, however this often seems to be overlooked in metallurgical testing programs. The principles of “international standard” or “certified reference material” samples and replicate/duplicate testing can be applied to metallurgical programs, although there are metallurgical-specific considerations in both generating and analysing the data.This paper will describe the QA/QC program carried out within the Olympic Dam geometallurgy program. It will present results in the form of case studies from ten years of testing of replicates and bulk reference samples for industry-standard comminution tests as well as laboratory flotation and leaching tests. The Olympic Dam geometallurgy quality control program has enabled quantification of the precision of metallurgical testing and improved our understanding of the best possible modelling results given the underlying dataCITATION:Ehrig, K, Liebezeit, V and Macmillan, E, 2017. Metallurgical QA/QC – who needs it? The Olympic Dam experience, in Proceedings MetPlant 2017, pp 31–44 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 11, 2017

By P Card

Some project managers accept unsatisfactory economic evaluation modelling because they are unaware of what constitutes good practice. They tend to leave it to the evaluation specialist or others to decide. The AusIMM has published on its website a draft set of guidelines for technical economic evaluation which will allow these project managers to take control and demand worldÆs best practices.The style of the guidelines is described and the source of a worked spreadsheet example in Excel is given.Economic evaluation in project management is described. A simple test for the acceptance or rejection of evaluation work is offered. The nature of modelling and evaluation in each of the three study phases of concept, prefeasibility and final feasibility are described. Suggestions on the selection of specialists for each phase are given. The three levels of evaluation thinking are described, namely, modelling, valuation and evaluation. Finally the meaning of æfinancial analysisÆ is explained.The conclusion is that æthe role of an economic evaluation specialist is to create models and evaluations for the whole project team to readily understand and use: it is not to create models for his/her own useÆ.CITATION:Card, P, 2012. What project managers must demand from an economic evaluation!, in Proceedings Project Evaluation 2012 , pp 173-176 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

The mining industry has recognised for some time the importance of supporting programs which serve to educate the Australian public about the socio-economic benefits of mineral resource development. More recently, industry leaders have realised that the future development of the industry will depend on attracting sufficient young people to commit to a career in the industry. Apart from lending support to the traditional education institutions in Australia, the industry now has the opportunity to participate in the development of education programs in museums. Whilst historic, mining-related theme parks such as Sovereign Hill and Coal Creek in Victoria serve very effectively the objective of relating past mining activities to the socio-economic development of Australia, there still exists the need to provide a facility which, under the same roof, excites interest in geology, mining, mineral processing and the role of minerals and energy in modern society. The redeveloped Geological and Mining Museum (the "Mining Museum"), which is located in The Rocks area of Sydney, meets this objective. With the central themes of formation and transformation this new Museum, which aims to be the best of its type in the world, will use modern museum exhibit techniques and the resources of the Minerals and Energy Information Centre to educate the community including teachers and school children. In the best tradition of museums, outstanding mineral and other collections will complement a comprehensive range of interactive, high technology exhibits which will include a number of exploratory "hands on" facilities. Australian companies are joining with Government to fund this exciting new museum. There is still a need for industry professionals to realise that a modern "mining" museum is no longer just a repository for objects of mining heritage but is also an important centre which serves as an important educational and public relations interface. The Education Section of the new "Mining Museum", which is linked closely with the new Minerals and Energy Information Centre, will be working closely with appropriate mining-related Tertiary institutions to develop specific career programs aimed at secondary students who wish to pursue a career in the mineral resource industries.

Jan 1, 1989

The importance of the accurate determination and interpretation of the bulk density and porosity of a given iron ore deposit is very often disregarded or neglected. Large amounts of time and money are spent on delineating and testing orebodies, and yet one of the most important factors in resource evaluation is sometimes estimated or, at best, determined from existing data from similar deposits. The Thabazimbi and Sishen South iron ore deposits are two well-known economical occurrences of high-grade iron ore in South Africa. Both these deposits formed as secondary enrichment of banded iron formation lithologies. Ongoing density studies on both these deposits are underway and results thus far proved very effective and necessary. Small-scale methods are used to determine average values for different ore types on both deposits. These values are used in resource estimation and geophysical interpretation.

Jan 1, 2007

The Pilbara iron ore industry has seen rapid growth over the last five years and is now bracing itself for another expansion which will take its seaborne trade to beyond 500 Mt/a. To effectively utilise port capacities, port stockpile turnover will become extremely rapid and each stockpile built will have to be of a quality which is precise and unbiased.Sampling systems at the older Pilbara mine sites were generally designed during the 1980s and reflect the practices which were considered adequate at the time. Hence, the precision of measurement at production sites is generally unknown and quality assurance (QA) of sampling facilities falls short of what current best practice suggests. This paper suggests practical improvements in sampling practices and quality assurance, which will assist the industry in achieving quality objectives in times of rapid mining expansion.

Jan 1, 2008

Modern minerals projects face serious challenges in earning and maintaining acceptance by their key stakeholders. Factors which underpin effective response to managing these challenges include consideration of public affairs issues from the earliest planning stages, building robust alliances with a range of influential partners, developing a level of transparency in all operations and decision-making and integrating activities towards resolving key strategic issues. Effective community relations is vital and there are a number of elements common to the best approaches. These include senior management support and involvement, appropriate involvement in project decisions and activities by community members and company responsiveness to community expectations. The project's operations manager and executive team must fully commit to developing the capability and processes to meet these challenges. They require a whole of project response and it is not an option to manage them peripherally.

Jan 1, 1997

The Australian lead-zinc industry faces a future in which the world market is likely to show at best only minimal growth and in which there will be increasing competition. Its production facilities use mature technologies employing expensive labour and increasingly costly energy in a country which demands the highest standards of environmental performance. Returns on investment are already unsatisfactory.Technology for survival would appear to indicate a need not only for more efficient capital, labour and energy usage combined with improved environmental performance, but also flexibility to handle more complex materials than the traditional, virtually single metal concentrates. This offers the potential for improved overall economics from the mine onwards, but will demand efficient separation and by-product recovery processes.In the lead industry these problems are being addressed in several emerging technologies. With zinc, the situation is less clear.

Jan 1, 1985

By Trudinger J. P

Concern for the environment by the public and by mining companies, has led to many recent attempts to revegetate areas disturbed by mining activities. The problem of successfully revegetating disturbed areas and mine wastes is often difficult, even under favourable conditions. Under the severe conditions that prevail in and and semi-arid parts of Australia, such difficulties may be extreme. An approach is described in which field trials are used to investigate factors which adversely affect revegetation and to evaluate optimum methods and treatments..A wide range of methods suitable for use in and situations is described. These include grading and cultivating operations, topdressing with natural soil materials, selection of suitable plant species, mulching and the use of fertilisers and supplementary irrigation. It is concluded that such a programme provides the best approach to this complex and expensive problem.

Jan 1, 1976

IF lead be heated with concentrated sulphuric acid two distinct actions will usually be observed. In the first, bubbles begin to be evolved more or less rapidly from the lead, and in the second, which occurs at a higher temperature than the first, hydrogen and sulphur dioxide are evolved, free sulphur is liberated, and leadsulphate is formed. The second action may be violent and usually continues till the lead is all consumed.Attempts have been made to apply these reactions, by means of a standard procedure, as a "Flash test" for the acid resisting qualities of chemical sheet lead. The purpose of this article is to comment on the best method of performing the test, on the various phenomena which may be observed during the course of it and on the interpretation of the results when obtained.PREVIOUS WORKIn 1919, Barr...

Jan 1, 1930

By Merritt RR

The equilibrium phase relations in the Fe- Mn-Ti-0-S system were established at 1380 and 1485 K. The elemental distributions between the equilibrium phases were obtained by chemical- ly analysing selected samples from the phase study. The results are considered in relation to the coal reduction process for upgrading ilmenite. The beneficial effect of adding sulfur to a kiln that uses a manganese-rich feed is ex- plained by the formation of a metal-sulfide solid-solution phase that removes part of the manganese from the oxide system. The optimum conditions for operating the reduction kiln are determined, and the practical need to operate the kiln at other than optimum conditions is explained. It is shown how the experimental data can be used to predict the best compromise conditions for reduction and the resultant purity of the product.

Jan 1, 1980