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By E. Siami-Irdemoosa, S. R. Dindarloo

Ease of excavation or rippability, also called diggability or excavatibility, is a critical decision-making parameter in the selection of both the overburden removal method and the required equipment in surface mining and geotechnical engineering projects. The most widely used method of estimating rippability is rock mass classification. Although there are different classification schemes in the literature, all of them have the two major limitations of sharp transitions at class boundaries and subjective uncertainties in decision making. In this study, the decision trees method was employed as a classification tool for estimating ground rippability, using the four rock mass parameters of weathering degree, uniaxial compressive strength, joint spacing and bedding spacing. The results were compared with those of the widely used method of diggability index rating (DIR) and a fuzzy-based DIR. The problem of subjective uncertainty was resolved in the proposed decision trees method, as the tree rules were derived automatically from the training data sets. Compared with fuzzy-DIR, a decision tree classifier is simpler, needs less computational time and is more appreciable by industry practitioners. Nevertheless, the proposed method is not flawless and, similar to both the conventional and fuzzy DIR methods, yielded poor estimations in particular instances. The limitations of the three methods are discussed.

Jan 1, 2015

By K. D. Luxbacher, E. C. Jong

Perfluoromethylcyclohexane (PMCH), a member of the perfluorocarbon tracer group of compounds, has been shown to be a viable supplement to the widely used tracer gas sulfur hexafluoride (SF6). This viability stems from the fact that PMCH can be used concurrently with SF6 while maintaining adequate chromatographic separation and comparable sensitivity during analysis. However, the release of PMCH in an underground mine ventilation system is challenging due to its physical characteristics. While SF6 exists as a gas at room temperature and pressure and can be accurately released by a variety of means, PMCH exists as a volatile liquid at room temperature and pressure, preventing it from being deployed in a similar manner. One method to release PMCH is to use a permeation plug passive release vessel (PPRV), which allows for the controlled release of the gas. This paper presents the results of a study evaluating various preparation techniques, plug thicknesses and plug materials of an aluminumvessel PMCH release source, so that a source appropriate for the mine scale may be developed.

Jan 1, 2015

By P. G. Dempsey, J. R. Heberger, J. P. Pollard

During a mine disaster or emergency, underground air can quickly become contaminated. In these circumstances, all underground mine workers are taught to don breathable air supply units at the first sign of an emergency. However, no contemporary oxygen consumption data is available for the purposes of designing breathing air supply equipment specifically for mine escape. Further, it would be useful to quantify the oxygen requirements of breathing air supply users for various escape scenarios. To address this need, 14 participants crawled a distance of 305 m each while their breath-by-breath oxygen consumption measurements were taken. Using these data, linear regression models were developed to determine peak and average oxygen consumption rates as well as total oxygen consumption. These models can be used by manufacturers of breathing air supply equipment to aid in the design of devices that would be capable of producing sufficient on-demand oxygen to allow miners to perform self-escape.

Jan 1, 2015

By G. Bylapudi, A. Bhagwat, K. Mondal, A. J. S. (Sam) Spearing

Minimizing the effects of corrosion improves the long-term performance of the rock anchors and ground control systems in underground mines, which is fundamental for safe operation over the design period. The primary objective of this study is to explain the problems due to stress corrosion cracking (SCC), strain-induced corrosion cracking (SICC) and other forms of corrosion, and why the mining industry’s ground control professionals should take this into serious consideration. It is important to clearly determine the kind of SCC mechanisms that causes roof bolt failures in order to suggest the necessary action plan to mitigate or eliminate the possibility of the cause. Pertinent literature and studies around the globe on this complicated subject are reviewed. The secondary objective is to encourage the use of corrosion-resistant ground control products in the underground mining industry in areas of high corrosion potential. Characteristics of SCC on high strength steel are also reviewed. The literature and preliminary studies to date indicate that research work is necessary in United States.

Jan 1, 2015

By L. Zhou, J. P. Rider, T. W. Beck, J. A. Organiscak, Y. Zheng

The National Institute for Occupational Safety and Health’s Office of Mine Safety and Health Research recently developed a series of models using computational fluid dynamics (CFD) to study the gas distribution around a continuous mining machine with various fan-powered flooded bed scrubber discharge configurations. CFD models using Species Transport Model without reactions in FLUENT were constructed to evaluate the redirection of scrubber discharge toward the mining face rather than behind the return curtain. The following scenarios are considered in this study: 100 percent of the discharge redirected back toward the face on the off-curtain side of the continuous miner; 100 percent of the discharge redirected back toward the face, but divided equally to both sides of the machine; and 15 percent of the discharge redirected toward the face on the off-curtain side of the machine, with 85 percent directed into the return. These models were compared against a model with a conventional scrubber discharge, where air is directed away from the face into the return. The CFD models were calibrated and validated based on experimental data and accurately predicted sulfur hexafluoride (SF6) gas levels at four gas monitoring locations. One additional prediction model was simulated to consider a different scrubber discharge angle for the 100 percent redirected, equally divided case. These models identified relatively high gassy areas around the continuous miner, which may not warrant their use in coal mines with medium to high methane liberation rates. This paper describes the methodology used to develop the CFD models, and the validation of the models based on experimental data.

Jan 1, 2015

By Y. Luo

Highwall mining, which is a relatively new mining method, is a preferred and often the only feasible method for extracting coal reserve left by surface mining operations in areas with steep terrain and in closely spaced thin coal seams. Though its safety record is comparable to that of surface mining, failures of mine structures in highwall mines, especially the highwall, have occurred. Methods for the systematic designing of highwall mines to meet the safety and operational challenges are still evolving. This paper presents the results of research into improving the existing design methods and developing new ones for highwall mining operations. The design methodology is aimed at ensuring structural stability of the highwall, roof, web and barrier pillars and preventing subsidence. It takes into consideration the major ground control challenges of soft and layered mine roofs, and interactions from mining closely spaced coal seams. An optimization design process applying a pressure arch concept can be incorporated to improve the recovery rate of coal reserve. A computer program based on the design methodology was developed.

Jan 1, 2015

By Gregg Davidson, Lonnie Jacobs, Brett Zernich, Alan Howard, Robert Pintabona

All Rights Reserved. Printed in the United States of America. Information contained in this work has been obtained by SME, Inc. from sources believed to be reliable. However, neither SME nor its authors guarantee the accuracy or completeness of any information published herein, and neither SME nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that SME and its authors are supplying information but are not attempting to render engineering or other professional services. If such services are required, the assistance of an appropriate professional should be sought. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Any statement or views presented here are those of the authors and are not necessarily those of SME. The mention of trade names for commercial products does not imply the approval or endorsement of SME.

Dec 1, 2014

By T Elkington, A Finch

The theory of constraints (TOC) is a business improvement method that focuses on exploiting a business’s bottleneck to deliver the highest possible profit. Early applications were mostly in the manufacturing industry; however, the theory in itself is completely generic and has now been applied widely in other industries such as services, retail, software and distribution, amongst others. The intent of the approach is attractive – it focuses on the ‘silver bullet’ rather than ‘death by a hundred projects’, and it focuses on growth rather than cost cutting. Application within the mining industry has been limited to date, although there are a few applications emerging. This paper discusses how TOC can be applied to maximise value during the project planning phase and how to maximise profits when the mine is operational. The paper uses two case studies to illustrate the approach. Case study 1 uses the approach to improve tactical mine planning, which delivers an increase in revenue of 58 per cent. The second case study is a strategic mine planning example that delivers an increase in value of 77 per cent.CITATION:Finch, A and Elkington, T, 2014. Application of the theory of constraints to strategic and tactical mine planning, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 129–136 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By P A. Grossman, J H. Rubinstein, M Brazil, K G. Sirinanda

To date, the scheduling and access design of an underground mine have only been considered as two separate optimisation problems. First, access to the mine is designed and then the scheduling is completed. One drawback of this approach is that the costs of access construction fail to be reflected in the net present value (NPV) calculation. In this paper, designing the access and scheduling its construction are formulated as a single optimisation problem.The underground mine access construction process can be classified according to the number of faces being developed concurrently. An underground mine with a single decline branching at a junction point into two declines is considered. After construction reaches the junction, the two faces of the decline can be constructed sequentially or concurrently.This paper proposes an efficient algorithm for optimally locating a junction point to maximise the NPV where two faces are being developed concurrently. The NPV is defined by taking the locations of orebodies and their values, decline construction costs, decline development rate and discount rate into account. The variation of the NPV and the optimal locations of the junction point for one and two concurrent development faces for a range of discount rates are discussed and compared. The proposed algorithm is applied in a simulated case study based on hypothetical values for an underground mine.CITATION:Sirinanda, K G, Brazil, M, Grossman, P A, Rubinstein, J H and Thomas, D A, 2014. Strategic underground mine access design to maximise the net present value, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 235–242 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By M de Freitas Silva

One of the main steps during the decision-making process of long-term mine planning is the definition of the optimal sequence of extraction, which usually is synonymous with maximising the discounted cash flow of the project subjected to several constraints arising from aspects of technical, physical, and economic limits.Open pit mine production scheduling (OPMPS) comprises several intricacies related to its size and uncertainty of input parameters. Due to its complexity and prohibitive size, traditional mine planning usually relies on heuristic or metaheuristic methodologies which are able to provide good solutions in a reasonable amount of time. However, most of the uncertainty that surrounds the mining complex is ignored leading to non-realistic results.In this paper, a new heuristic approach is explored in order to solve a stochastic version of the OPMPS problem accounting for geological uncertainty in terms of metal content, multiple processing streams, and stockpiling option. The methodology involves generating an initial solution by solving a series of subproblems and this initial solution is improved using a network flow based algorithm.The algorithm was applied to a relatively large gold deposit with more than 119 thousands blocks. Results have shown that the methodology is promising to deal with large-size mine instances in reasonable time.CITATION:de Freitas Silva, M, 2014. Solving a large stochastic integer programming model for production scheduling at a gold mine with multiple processing streams and uncertain geology, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 389–396 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By T Wambeke, J Benndorf

A risk-robust development of a heavy mineral resource requires an assessment of the geological uncertainty and spatial variability of the key factors impacting the mining and processing operation. Attributes of interest are the total heavy mineral grade, the slime content and the amount of oversized particles. The modelling of a mineral sand deposit presents two main challenges. Firstly, the exact location of the geological boundaries are obscure due to the complex interaction of the deposit formation processes. Secondly, the properties of interest exhibit a rather complex transitional behaviour across the so-called soft boundaries. Traditionally, the modelling exercise is restricted to a consecutive stochastic simulation of distinct geological facies and orebody properties. This results in different zones separated by hard boundaries, ignoring the typical transitional behaviour.This contribution presents an alternative approach which models the entire sand body as a single domain while accounting for the complex trends present. Error curves are used to infer covariance model parameters without the need of a prior removal of the trend. The principle is based on minimising the differences between empirical and theoretical errors resulting from two methods of prediction calculated for different rings of influence. The added value results from the unambiguous decomposition of the spatial variation into a deterministic trend and a stochastic residual. The trend model neither overfits nor underfits the data. The calculated residuals are thus unbiased and the uncertainty can be correctly assessed.The effort results in a characterisation of the resource uncertainty which provides a more realistic image of the spatial variability of the key properties in and across the geological domains of an existing heavy mineral sand deposit.CITATION:Wambeke, T and Benndorf, J, 2014. Optimal inference of modelling parameters to simulate complex trends across soft boundaries – a case study in heavy mineral sands, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 73–84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By S Coward, C Xu, P A. Dowd

"This paper provides an assessment of the current challenges in strategic mine planning and design and suggested approaches for addressing them. The specific challenges covered are: realistic quantification of downstream processes applied to orebody models to provide an integrated approach to mine design and optimisation modelling, estimation and simulation of geometallurgical variables and their integration into resource and reserve estimation and mine planning modelling, estimation and simulation of new variables for new forms of mining – deep mining, particularly block caving, and solution mining flexibility in planning and design to manage risk and minimise its impact information technology (IT) infrastructure and platforms for rapid online data collection, storage, access and processing.Most of these challenges require new types of data, variables, modelling and estimation methods. Foremost among the new types of variables and data are geometallurgical and dynamic rock mass characterisation variables. New types of data and data collection include rapid generation of very large amounts of online sensor data and the consequent need for rapid processing and modelling of these data.This paper outlines the challenges and strategies in each of these areas and uses examples of models and outputs to illustrate approaches and potential solutions.CITATION:Dowd, P A, Xu, C and Coward, S, 2014. Strategies for mine planning and design, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 41–50 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

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

By M Bloss, B Roberts

BHP Billiton Olympic Dam required a well-tested software product suitable for strategic optimisation and scheduling of options for a potential underground mining project. The company has a standard software package called Blasor® that is used for open pit optimisation of complex deposits such as iron ore, copper-gold-uranium and silver-lead-zinc. It applies a mixed integer programming formulation (MIP) to produce conceptual pushback designs and an optimised pushback sequence. Schedules can then be run on the resulting mine designs. Existing pushback designs can also be imported into the model and an optimum schedule generated. One of the key advantages of Blasor is that multiple strategic mine schedules can be quickly generated according to the various scenarios, options and constraints that are being investigated.It was realised that Blasor, if carefully configured, could be adapted for use in underground planning. The concept of using Blasor as an optimiser for underground strategic scenarios is to represent the underground stope and development data in the form and structure of an open pit mine. In simple terms, underground stoping areas are modelled in the form of pushbacks (phases) with vertical walls. The phase dependency tools in Blasor are used to link mine blocks and their access development drives. These underground phases are imported into the optimiser. Artificial block models are constructed using stope design tonnage and grade data at various fixed cut-offs. A variable cut-off grade model has also been developed using a method of parcels to represent each cut-off grade increment.So far, this approach has been successfully used to investigate the optimum stope design cut-off for various strategic options, the economic potential of a series of mining and processing configurations and to provide guidance on the optimum sequence for developing and mining the various stoping blocks in the resource. Examination of the results has highlighted the most suitable development paths for more detailed study.CITATION:Roberts, B and Bloss, M, 2014. Adaptation of an open pit optimiser for underground strategic planning, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 249–256 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By J Zhang, R Dimitrakopoulos

A two-stage stochastic mixed integer non-linear program is formulated for a mining complex to optimise strategic and tactical plans. The objective is to find the near optimal decisions for a mineral supply chain in the context with uncertainties in both ore supply and the commodity market (price and demand). The endogenous spot price in the commodity market and long-term sales contracts are considered in the formulation of the mining complex’s optimisation model and an ad hoc heuristic is developed to deal with the throughput – and head-grade-dependent recovery rate in processing plants. Numerical results indicate that the proposed heuristic is effective and efficient in numerical tests. Based on the proposed model and heuristic, a long-term contract design strategy is proposed for making decisions on the contract price and strategic investments. A shadow price based method is also proposed to evaluate the existing mining schedule.CITATION:Zhang, J and Dimitrakopoulos, R, 2014. Optimising a mineral supply chain under uncertainty with long-term sales contracts, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 25–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

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 H M. Parker, G Verly, T Postolski

Assessing the uncertainty and risk in mineral resource estimation is required for best practice and is implied by the public reporting codes in the categorisation of mineral resources and reserves. One industry best practice is quantifying the risk on future production for a given period, which can be done using two geostatistical approaches: conditional simulation and drill hole spacing studies based on estimation variances. Conditional simulation can provide a more complete and flexible answer to the problem, but it takes a fair amount of time to complete. Drill hole spacing studies are simpler, faster and can provide reasonable assessments of mineral resource uncertainty.This paper is a presentation of the principles, theory and practice of drill hole spacing studies. Various types of risk assessment are considered. Difficulties encountered in practice are discussed, and solutions are proposed. The important parameters impacting the results are reviewed. Examples of results and sensitivities are shown.CITATION:Verly, G, Postolski, T and Parker, H M, 2014. Assessing uncertainty with drill hole spacing studies – applications to mineral resources, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 109–118 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By S Q. Liu, E Kozan

This paper proposes a new multiresource multistage scheduling problem for optimising the open pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.CITATION:Kozan, E and Liu, S Q, 2014. An Open pit multistage mine production scheduling model for drilling, blasting and excavating operations, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 329–334 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By R Dimitrakopoulos, I Minniakhmetov

Geostatistical simulation techniques are used to quantify uncertainty of spatial attributes of interest describing mineral deposits, petroleum reservoirs, hydrogeological horizons, environmental contaminants and so on. The majority of existing methods consider second-order spatial statistics and Gaussian processes, while the more advanced multiple point-based simulation approaches are algorithmic and do not consistently account for the high-order spatial relations in data. Recently, simulation techniques for complex and non-Gaussian spatially distributed variables have been developed, based on high-order spatial cumulants, and make no assumptions on data distribution or require data transformations. In this paper, the previous developments are extended and a new approach for the joint simulation of multiple correlated variables using high-order spatial statistics is proposed. The technique is based on a new algorithm for the decorrelation of correlated variables into factors, using the so-termed diagonal domination condition of high-order cumulants. The decorrelated factors are then simulated using high-order simulation and back-transformed into the initial correlated variables. The decorrelation using diagonal domination of high-order statistics is tested with a data set from a multielement iron ore deposit, and then a fully known two-dimensional data set with two correlated variables is used to demonstrate the practical intricacies of the proposed method.CITATION:Minniakhmetov, I and Dimitrakopoulos, R, 2014. Joint simulation of correlated variables using high-order spatial statistics for orebody modelling, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 53–60 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By A Melkumyan, K Silversides

The banded iron formation-hosted iron ore deposits located in the Hamersley Ranges of Western Australia contain marker shales that are used to distinguish lithology for geological and orebody mapping. These marker shales produce distinctive signatures in the natural gamma downhole logs, which are conventionally manually interpreted. This paper proposes an alternative method of automatically identifying these shales using dynamic time warping (DTW). A Gaussian processes (GPs)-based method for automatic identification is also considered. Both methods are tested on a deposit that contains the Marra Mamba sequence of the Hamersley Province.Both methods were trained to predict the location of the desired shales, and the resulting outputs were compared with a manual interpretation of the results to determine the accuracy. The GP method can identify signatures with an accuracy between 87.0 per cent and 92.0 per cent, which increases to 92.9 per cent and 95.7 per cent where the GP is certain. The DTW method has an accuracy between 90.0 per cent and 91.6 per cent, which increases to 94.0 per cent and 95.4 per cent where the DTW is certain.The GP method has several advantages, including a more automated library building process, a probabilistic output and a shorter run time. However, the DTW method was capable of accepting more distortion in the signature and therefore identified more signatures. This is important in a deposit where the signals are frequently distorted by events such as hydration and folding. Both methods provide a viable alternative to the current manual detection, but their differences make them applicable to different cases.CITATION:Silversides, K and Melkumyan, A, 2014. Comparison between Gaussian processes and dynamic time warping for classification of marker shales in iron ore deposits, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 177–184 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014