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By K G. van den Boogaart, M Lehmann, U Mueller

Geometallurgical parameters are descriptions of the mineralogy and microstructure of the ore determining its mineralogical and microstructural characteristics. From a conditional geostatistical simulation of such properties, a processing model can compute recovery, equipment usage, processing costs, and thus the monetary value for mining and processing a block with certain processing parameters. The output can be used for optimising mining sequences or finding optimal processing parameters by solving the corresponding stochastic optimisation problem.The approach requires two properties of the simulation not provided by established geostatistical techniques:Many relevant geometallurgical parameters are from non-Euclidean statistical scales such as (mineral) compositions, (grain size) distribution, (grain) geometry, and (stratigraphic type) categorical, which might produce nonsensical values (for example, negative proportions, negative facies probablities, planar grains) when simulated with standard geostatistical techniques.Due to the nonlinearity of processing, the entire conditional distribution of the geometallurgical parameters is relevant, not only its mean and variance. The geostatistical simulation needs to reproduce the joint conditional distributions of all the geometallurgical parameters.The multipoint conditional geostatistical simulation technique discussed here allows for jointly simulating dependent spatial variables from various sample spaces. The technique combines an infill simulation, similar to the one used in multipoint geostatistics, with a new form of distributional regression to estimate conditional distributions of arbitrary scales from different information sources, including training images, training models and observed data. The distributional regression is based on a generalisation of logistic regression and is related to both Bayesian Maximum Entropy geostatistics and high order cumulants.The method ensures that simulated data reside in the set of possible values and honour the characteristics of the joint distribution to be reproduced. The computational effort is substantial, but affordable for a useful application with standard problems: from processing-aware block value prediction and block processing optimisation as shown in the test application to a mathematically completely defined simulated model situation with a complex processing model.CITATION:van den Boogaart, K G, Tolosana-Delgado, R, Lehmann, M and Mueller, U, 2014. On the joint multipoint simulation of discrete and continuous geometallurgical parameters, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 379–388 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By C V. Deutsch

"Geometallurgical variables often cause problems to conventional geostatistical workflows. There are many variables; some are compositional and some are non-additive. They often show: complex multivariate relationships undersampling relative to conventional grade variables unequal sampling; that is, all variables are not available at all data locations.A variety of approaches have been developed over the years, but geostatisticians remain mostly focused on modelling rock types and a few grade variables with an abundance of data. The problems are reviewed and a chained workflow is presented where appropriate techniques are employed in sequence to permit reliable spatial prediction of geometallurgical variables. The spatial models may be used to assess the value of additional data, for prediction of process performance, for improved mine planning and other optimisation tasks. The chained workflow will include data transformations such as ratios and normal scores that make the variables amenable to geostatistical modelling. Data imputation techniques to account for missing values are considered with special consideration to spatial correlation with the available data. Decorrelation techniques such as the principal components, min/max autocorrelation factors and projection pursuit multivariate transformation are employed to manage massively multivariate modelling. Full distribution modelling must be considered to avoid biases in the prediction of non-additive variables. The post-processing of geometallurgical models must be streamlined for robustness and efficiency. The precise workflow varies according to the specific purpose of the study. Guidelines and thoughts on best practice are presented.CITATION:Deutsch, C V, 2013. Geostatistical modelling of geometallurgical variables - problems and solutions, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 7-16 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By R D. Morri, D J. Alexander

The design and optimisation of mineral flotation circuits is currently performed using a combination of laboratory, pilot plant and full scale testing. Owing to the variable nature of flotation circuits and the complex nature of the flotation process, it is difficult to interpret the data collected from flotation testwork. JKSimFloat is a computer modelling package which is being developed to interpret flotation testwork data collected at the various stages of the mining cycle. The parameters derived from the program can be used to assess potential circuit configurations in both the design of new flotation circuits and in the refinement of existing operations. The aim of this paper is to outline the modelling methodology used in JKSimFloat and to outline how it can be used effectively to model data collected from either the laboratory, the pilot plant or the existing flotation circuit. The use of flotation model parameters in circuit evaluation will be demonstrated via the use of a case study based on data collected from ComincoÆs Red Dog lead flotation circuit.

Jan 1, 1998

By G McCullough, J Bassan, d P. Knights, C T. Farrelly

By 2045, carbon-neutral mines will be economically producing products that are vital for the world’s transition to renewable energy. After overcoming significant technical challenges (and the investment of significant capital), leaders have successfully eliminated the use of diesel and other fossil fuels by introducing a wide range of new decarbonisation technologies. These leaders will be reaping the benefits of lower production costs (resulting from elimination of diesel), stable and predictable operations, and easier access to capital for their future projects. This paper describes a future scenario of how a net zero carbon and zero-entry mine could operate by taking maximum advantage of technologies in development or already proven in other industries. Some miners have been unsuccessful in their efforts to reach decarbonisation targets. Instead, they have been forced to close or offload their assets to be acquired by operators with better sustainability credentials, or, in some cases, to indigenous or community-based enterprises with vested interest in making operations viable and sustainable. Regardless of ownership structure, all successful mining operations will have fostered strong and positive community relations that bring education, health, security and economic development opportunities to the communities while respecting their traditions, land-uses and culture. As shallow, easy to mine deposits have become scarce, the majority of new mines are underground. Advancements in electric underground technology and the feasibility of ‘zero entry mining’ (with no personnel in active mining zones) has made it increasingly possible to economically operate underground mines, even at shallow depths. The newest mines have a near zero footprint on the surface, produce no harmful by-products, and are employing in-place or in situ methods of extraction that are efficient and low impact. Surface land-uses, such as agriculture and renewable energy generation, continue in the immediate vicinity of the mine, with no significant ground disturbance, community impact or environmental footprint.

Sep 1, 2024

By R Dimitrakopoulos, R Goodfellow

One of the primary objectives when optimising a mining complex is to maximise its value for the primary stakeholders. In order to achieve this objective, it is necessary to holistically optimise all aspects of the mining complex, including decisions of when to extract materials from the available sources, how to blend or stockpile these materials and how to best use the available processing streams to satisfy customer demand. Existing methods for global, or holistic, optimisation ignore the compounded effects that risk has on the performance of a mining complex. Over the past decade, several stochastic optimisation approaches have been proposed to integrate various forms of uncertainty into the open pit mine design and production scheduling. These methods, however, are limited in their ability to simultaneously optimise the production schedules for the portfolio of mines, material destination policies, the use of the available processing streams and the various products that are produced at each location of the mining complex.This paper aims to discuss a new method for the global optimisation of open pit mining complexes with geological uncertainty. The proposed generalised methodology is capable of modelling and holistically optimising mining complexes, including aspects related to production scheduling, blending, stockpiling and non-linear interactions that often occur in practice, but are over-simplified in existing models. Two case studies are discussed to highlight the need for these complex, stochastic optimisers. First, a case study for a nickel laterite blending operation highlights the need to integrate geological uncertainty into the optimisation in order to ensure product quality constraints are respected. Second, a case study for a copper-gold mining complex highlights the added value when simultaneously optimising the production schedule and the stockpiling and treatment of extracted materials.CITATION:Goodfellow, R and Dimitrakopoulos, R, 2014. Stochastic optimisation of mineral value chains – developments and applications for the global optimisation of mining complexes with uncertainty, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 13–22 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By P Knights

This paper examines the process and specialised skills required to extract insight from data routinely collected by mine operations, maintenance, engineering and environmental departments. Typical insights include: enhanced understanding of root causes; recommendations for next best actions; and simulation of likely scenarios. The skills required for advanced analytics are not currently the domain of mining engineers. The professions required by tomorrow’s mines are likely to be diverse and multi-disciplinary, and will include control engineers, software engineers, mathematicians and statisticians. A case study is presented that correlates mobile equipment production delays with rainfall events across three mines on the east coast of Australia. One mine is shown to have significantly more rain related downtime than the other mines, providing compelling evidence to improve productive performance.

Nov 22, 2011

By J Whittle

This paper describes what is involved in carrying out a comprehensive optimisation of a long-term operating schedule for a mining complex. It details the data that must be assembled and discusses the different approaches to optimisation and what limitations they put on the variables and constraints that can be handled.CITATION:Whittle, J, 2014. Not for the faint-hearted, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 3–6 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

A variety of algorithms and methods are being used by the mining industry today to map mineral resource for reserve estimation. The traditional methods including Polygonal, Sectional and Inverse Distance methods are relatively easy to understand and implement. They have served industry well for several decades and should continue to do so for the large bulk mineable deposits with very regular geometries with relatively small variation in grade.

Jan 1, 1992

By X Yang, T Zhang, Z Li, Z Yan, M A. Williams, S Qin, P Wilson

Continuous development of complex new steel grades to meet the ever-increasing demand of high performance causes recurrent issues in steel continuous casting such as surface quality defects (eg cracks, depressions, deep oscillation marks) and productivity challenges (eg faster casting, near-net shape casting). Continuous casting of steel is a highly successful metallurgical process. Much of this success can be attributed to the performance of the casting powder that is added to the top of the mould, creates a liquid slag pool as it is heated, and forms a slag film between the watercooled copper mould and steel shell during its passage down the mould. Mould powder selection is a compromise between the conflicting requirements of heat transfer and lubrication. In an EU RFCS (Research Fund for Coal and Steel)-funded project, various techniques are developed to offer the opportunity to adapt the slag film to meet the conflicting needs in different parts of the mould such that mild cooling can be generated in the meniscus, mid-broad face or corner areas whilst maintaining lubrication and offering higher cooling rates in other areas of mould. This has significant potential to address the industrial issues in product quality and productivity of continuous casting. This paper reports, as part of the EU RFCS project, the determination of crystallinity and porosity in slag films for casting challenging and innovative steel grades using new methods. In comparison with the methods such as X-ray powder diffraction (XRD) analysis and optical microscopy / scanning electron microscopy (OM/SEM) analysis that are currently adopted by the industries, EBSD (electron backscatter diffraction) has been employed to determine the crystallinity of the slag films taken from industry casters. X-ray computed tomography (XCT) plus 3D image reconstruction has been used to determine the slag film % porosity with pore volume, pore size distribution, and pore location, which can be linked with the performance of the slag films during casting different steel grades.

Jun 19, 2024

By A Melkumyan, M Balamurali

Geological domains describe the mineralisation state and stratigraphic location of different geological regions of mines. They play a very important role at the geological modelling stage as weight percentage of chemical elements information within each geological domain is assumed to be correlated while information coming from different geological domains is considered uncorrelated. Having correct domain assignments to both the chemical assays and the 3D space of modelling is critical for building a reliable geological model of the mine.As standard practice significant effort is invested into the interpretation of the deposit and identification of the geological domains for the chemical assays and the 3D geological space. Despite these efforts, there are some chemical assays with ambiguous geological domain where the exploration assay domain and the block domain do not match. Incorrectly including a sample in the wrong domain can cause a large change in the predicted weight percentage of chemical elements estimation for that block. Therefore, the major challenge of grouping the spatially correlating weight percentage of chemical elements is how to determine which of these domains best fits these misclassified samples.This work proposes machine learning based autonomous technique for identifying to which geological domain (the exploration assay domain or the block domain) the misclassified sample belongs. The proposed methodology is based on Gaussian Process (GP) classification. The GP machine learning approach consists of training and inference stages. At the training stage the GP automatically learns the properties of different geological domains using the chemical assays with unambiguous domain assignment. Then, at the inference stage the GP makes predictions for the geological domains of the assays with ambiguous initial domain assignment.We tested the proposed technique by conducting a case study for an iron ore deposit located in Western Australia. The results demonstrate that the application of the proposed GP technique removes statistically significant deviations in the assay values in many regions: mineralised ore region, unmineralised region, highly weathered region and intrusive material that is highly variable. In this case study the proposed methodology autonomously identified the geological domains for more than 50 per cent of samples which are initially ambiguously classified. For the majority of the assays the GP predicted domain agrees with the geological domain assigned by the exploration assay.CITATION:Balamurali, M and Melkumyan, A, 2014. Automated identification of geological domains for exploration assays with ambiguous initial domain assignment in an iron ore deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 99–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

By N Anderson

With traditional grade control processes, geological models are created by geologists at the completion of the data collection stage and wireframe construction is closed off at a set date to allow for time to complete the estimation process. Any issues identified at earlier stages or the addition of new data requires the estimation process to be started again. Alternative interpretations are explored only if time allows and often in a limited fashion. An alternative workflow has been developed at the Waihi Underground Gold Mine utilising Leapfrog Edge and Seequent Central. Geological and grade control models are created, dynamically linked, and saved as separate branches. A project geologist is able to work on the grade control model and a mine geologist on the geological model simultaneously. This allows for a non-linear modelling workflow with continual review and feedback. The introduction of new data can occur right up to the model due date, with data collection, validation, alternate interpretation, and review happening incrementally. Models are categorised and stored in Seequent Central according to project status. An approved version of the geological model and grade control estimate are uploaded at the time of release and transparently capture all data used at a point in time, as well as the review process. Dynamically updating models for grade control has reduced turnaround time while increasing accuracy and quality. Estimates of individual domains are vastly improved from being able to rapidly evaluate the effects of model parameter changes in real time and 3D. Development and stope design directly benefit from these streamlined processes, with higher quality, timely production occurring as a result.

Mar 22, 2022

By A Finch, C Pridmore

The Cosmo Project falls within the Archaean to Palaeo-Proterozoic Pine Creek Orogen, one of the major mineral provinces of Australia.The Cosmo Deposit is interpreted to be a series of steep north-west-plunging gold mineralised vein, breccia and shear systems within the tight Howley Anticline and hosted within interbedded siltstones, mudstones, banded iron, phyllites, dolerite sills and greywacke.A folded environment poses a number of technical challenges, particularly for estimation.Handling of tightly folded and in some cases narrow domains might include subdomaining for orientation, omni-directional three-dimensional (3D) estimation within constrained domains or software-enabled unfolding/un-wrinkling procedures (transformation of the data and estimate space into a two-dimensional environment). Each technique has its own unique set of advantages and disadvantages.A further method (one applied at Cosmo) is where the estimation parameters (specifically search and variography orientation) are modified in a frequent or ‘dynamic’ sense to suit the orientation of the domain whilst maintaining 3D space. Control of the resource estimation orientation can be done in several ways, including the use of sectional panels of a specific size or, alternatively, orientation sector divisions. The sector approach provides some significant reductions in processing time over the panel technique and could be applied in a number of software packages.Three-dimensional ‘dynamic’ interpolation reconciles well with production data from Cosmo, whilst the sector method provides a practical technique that can be executed without the complications of transformation or the need for labour-intensive orientation subdomaining and with acceptable resource estimation run time.CITATION:Finch, A and Pridmore, C, 2014. Dynamic interpolation – estimation in a folded environment at the Cosmo Deposit, Northern Territory, Australia, in Proceedings Ninth International Mining Geology Conference 2014 , pp 107–114 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By A G. L Pratt, J R. Grant

Mining companies face the ongoing challenge of sustaining and growing production. This paper outlines business investment concepts to grow reliable returns on investment from a portfolio of choices by:improved visualisation, diagnosis and tune up of the investment pipeline (pipeline management); good corporate decision making (governance) to select the right project mix, risks and sequence; and delivery strategies to enhance and reliably execute projects.

Jan 1, 2006

By R J. Hardy

The aim of this study is to examine the volumetric and mass movement characteristics of load and haul operations using statistical modelling of relatively large samples of bucket loads that are transported as small samples in the form of truck payloads. Generally, the factors influencing bucket load variability are random, difficult to predict and to control. In the process of loading trucks the underlying variability of individual bucket loads will determine the variability of truck payloads. Bucket loads of material prepared by drilling and blasting for loading into trucks are fundamental quantities in open pit mine production. A study of payload data from a large surface mining operation indicates that bucket loads and truck payloads that are a small sample of bucket loads are normally distributed. Truck payloads have a reduced dispersion compared with bucket loads that is an inverse 0.5 power function of the number of passes per truck payload. Comparison of statistical modelling results with the æ10/10/20Æ policy promoted by Caterpillar Global Mining Inc, indicate that compliance with the æ10/10Æ part of the policy, applying to truck overloading is facilitated, as the coefficient of variation of truck payloads decreases, as a result of the increasing number of loading passes. Compliance with the more stringent æ20Æ part of the policy, relating to safe steering and braking is also facilitated, albeit at lower coefficient of variation for similar reasons.

Sep 26, 2011

By M Dunglison, P M. Cameron

Simultaneous mass-balancing of a mineral processing flow sheet results in adjustments to each data point that reflects the accuracy and precision across the full set of data. In this way, all the good work that goes into designing the sampling and analysis protocol for each sample point is leveraged in order to produce a æbetterÆ set of balanced numbers for every sample point in the circuit. Few operating plants employ whole of circuit balancing techniques to produce reported operating results. This situation is changing with the application of mass balancing technology which utilises redundant data for production accounting and metal reconciliation from product to ore source across multiple phases and multiple time periods. Mine and plant data can now generate credible information to improve productivity. Mine and plant personnel can now use consistent data sets for review and planning. Decisions based on balanced data can be made quicker and with increased confidence.

Jan 1, 2005

By P F. Hodkiewicz, J de Lacey, M Stewart, R Lane

"Implicit modelling is an approach to spatial modelling in which the distribution of a target variable is described by a unique mathematical function that is derived directly from the underlying data and high-level parametric controls specified by the user. This modelling approach may be applied to discrete variables such as lithology (after converting the discrete codes to numeric values) or to continuous variables such as geochemical grades. This paper discusses the estimation of continuous (grade) variables using implicit modelling.One of the underlying engines of implicit modelling for producing this mathematical function description is the radial basis function (RBF). In essence, the RBF is a weighted sum of functions positioned on each data point. A system of linear equations is solved to derive weights and the coefficients of any underlying drift model coefficients. Once derived, the RBF may be solved for any unsampled point or averaged over any volume to provide an estimate of grade. It is possible, for example, to query the RBF on a regular grid to derive an estimate of block grades. Given the ease of creation of an RBF, and its ability to predict grade, the question arises as to how the grades derived from the solution of an RBF compare with grade estimates derived from conventional geostatistical interpolation methods (eg ordinary kriging (OK)).The purpose of this paper is to describe in lay terms: the basic structure of an RBF the role of parametric choice in the solution of RBFs and how this influences the character of the solution the fundamental similarities and differences between RBFs and conventional geostatistical estimators.Using a high-resolution conditional simulation, we show that in many situations RBF and OK estimates are very similar.CITATION:Stewart, M, de Lacey, J, Hodkiewicz, P F and Lane, R, 2014. Grade estimation from radial basis functions – how does it compare with conventional geostatistical estimation?, in Proceedings Ninth International Mining Geology Conference 2014 , pp 129–140 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

Problems caused by water discharge from surface mine ventilation shafts can be significant and are usually unforseen. The discharged water is often hyper-saline or acidic and can cause environmental degradation over a wide radius. It can also lead to recurring power pole fires and primary fan breakdowns. A range of solutions to the water discharge problem has been implemented in many Australian mines. In most cases the solutions have been ad hoc, with the overall cost and effectiveness varying tremendously. This paper reviews and contrasts the practicality and effectiveness of the various available remedial options.

Jan 1, 2002

By A Noack

Today underground infrastructures, like tunnels and especially wide spread underground mines, are often equipped with ethernet based communication systems. These networks are used for the unified communication of data, voice and video. As these networks stretch along the major tunnels and in increasing scale also into the production areas, a high degree of coverage can be reached. For wireless coverage, standard IEEE 802.11 WLAN access points are being used. In order to provide a maximum availability and reliability, the active components are equipped with battery backup power supplies and the network infrastructure is set up in a redundant way using ring or meshed topologies. This provides a much higher availability compared to traditional phone systems or dedicated data links using a conventional star topology.Distributed computing intelligence that is installed on active network nodes throughout the whole network, additionally supported by a central server system, creates the basis for new mine safety functions introduced in this paper for both coal and non-coal mining. These new safety functions cover the detection of potential emergencies, using the status of the network as a æsensorÆ, as well as dynamically guiding people to safe exits or rescue shelters in case of an emergency. Furthermore, these functions are of important benefit for improving the efficiency of search and rescue operations following a major incident or accident underground.

Sep 26, 2011

By A Bird

Gravity gold circuits have an important part in reducing operating costs and maximising recovery in modern gold plants where coarse gold is present in the ore body. The design and selection of equipment has a vital part in the overall effectiveness of the gravity gold circuit. There are a number of associated factors that need to be taken into consideration when selecting the most suitable equipment for gravity gold circuits including occupational health and safety, security and labour requirements. This paper is a case study that outlines the validation behind the design, selection of equipment and subsequent benefits of the recent upgrade of the gravity circuit at the Marvel Loch gold mine with the main component to the upgrade being the installation of a Consep Acacia Reactor. Since the upgrade there has been a significant increase in gravity recovery, which has reduced the amount of gold reporting to the leaching circuit therefore reducing reagent consumption and overall operating costs. There has been an increase in overall gold recovery and therefore increased gold production. The benefits to occupational health and safety include the removal of toxic gases being released in the gold room during the previous practice of gold concentrate calcination and the removal of the arsenic and nickel from the gold doré, which poses a risk during refining. Manual handling and security has improved as there is no physical contact with gold concentrates during the automated process using the Acacia reactor. The total time for gold room personnel working in the gold room has also reduced from around six hours per day to less than one hour per day.With the continuing development of low grade gold deposits, there will be an increase in demand for low capital, high recovery gravity gold circuits that can significantly increase overall production while reducing operating costs.

Aug 8, 2011