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By B. T. Lusk, Q. Q. Huang, R. Q. Honaker, K. A. Perry

Rock dust is applied in underground coal mines to prevent the propagation of coal dust explosions. It is applied either dry or wet. Both methods have advantages and disadvantages, but the formation of caked rock dust particles is cited as a significant concern for wet applications. We conducted a study to evaluate the effect of modifying the rock dust particle surfaces to repel water and each other by the addition of oleic acid and sodium oleate. At a sodium oleate dosage of 1 kg/t, a contact angle of 112o was measured, indicating strong surface hydrophobicity and thus the ability to repel water. Fourier transform infrared spectroscopy (FTIR) studies indicated a chemisorption mechanism, which is necessary for long-term stability of the surface modification. The dispersibility of the modified rock dust samples was elevated by the application of both oleic acid and sodium oleate, thereby indicating a significant reduction or elimination of the detrimental effect of caking. Tests in an explosion chamber showed an 82.8 percent reduction in the dust explosion potential relative to untreated rock test applied by the wet technique.

Jan 1, 2015

By R. Gray, B. Hebblewhite

Experience from Australia had identified what is referred to as nonconventional surface subsidence behavior. This occurs under irregular surface topography, resulting in valley closure, valley floor uplift or “upsidence,” and far-field horizontal movements, occurring even beyond conventional “angle of draw” limits. This paper discusses such behavior recently observed in Pennsylvania and focuses on the 2005 case of Duke Lake Dam in Ryerson Station State Park. In July 2005, there was a significant increase in water leakage through a number of growing cracks in the dam, leading to the dam being breached to avoid an uncontrolled failure. An underground longwall mine was located approximately 900 ft to the north, mining at depths of 330 to 720 ft. Investigations, including a subsequent ground movement monitoring program, found a range of evidence in the vicinity suggesting that valley closure and farfield horizontal movements may have occurred, resulting from the adjacent mining. Besides discussing the phenomenon of nonconventional subsidence behavior and the Ryerson State Park case study, this paper includes an assessment of the mining, geology and subsidence impacts and suggested ground behavioral mechanisms.

Jan 1, 2015

By C. S. Todd, R. L. McNearny, S. Dun, P. Clark, P. W. Conrad, X. Liu, J. Q. Wu, H. Rhee, W. J. Elliot

Soil erosion is strongly related to soil hydraulic properties. Understanding how surface coal mining affects these properties is therefore important in developing effective management practices to control erosion during reclamation. To determine the impact of mining activities on soil hydraulic properties, soils from undisturbed areas, areas of roughly graded mine spoil, areas with replaced topsoil before seeding, and revegetated areas at the Rosebud Mine in Eastern Montana were evaluated. Field and laboratory studies were conducted to determine the soil hydraulic properties of the four representative areas, including particle-size distribution, organic matter content and saturated hydraulic conductivity. Using this data, Water Erosion Prediction Project (WEPP) simulations and risk analyses were performed to investigate mining’s effects on changes in soil erosion potential. Significant differences were seen in the hydraulic properties of the soils in the representative areas due to the mining and reclamation practices at the mine. The WEPP simulations show that the potential for soil erosion increases as a result of mining activities disturbing the soil. The simulations also indicate that the erosion potential may return to pre-mining levels over time with effective revegetation practices.

Jan 1, 2015

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 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 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 P Cesare, S Munro, D Wandel, R A. Bearman

Consideration of the processing plant operational envelope is a key factor in production scheduling,and therefore mine planning, for any mining operation. In many cases hard-wired or regressionbased tonnage-grade-recovery relationships are used as mine planning constraints and as a means of valuing the system output. In extensions of this type of approach, various regressions can be used to describe throughput limits, based on a number of global metallurgical parameters.The ultimate position for the optimisation of a mine plan and production schedule is to have a full process plant model running as an integrated part of the mine planning exercise. A plant model suitable for this needs to have all the required sensitivities to input parameters such asfragmentation, grade, mineralogy, strength and hardness. The model then needs to convert these to performance measures for the plant, which include recovery, throughput, product size distributions, energy consumption, water use and operating cost.In this paper an approach is outlined that takes this view and then goes beyond it to provide a full, time-based bottleneck identifi cation and valuation tool.Using such an approach it becomes possible to run mine plans and production schedules in windows of days, weeks, months and over the life-of-mine with a time-enabled process model acting as the active constraint. In this way virtual bottlenecks can be identifi ed for various mine plans and schedules well ahead of time. The value of de-bottlenecking can be defi ned, not just at a plant scale, but in terms of the overall mining operation, and the data can be used as the basis for capital investment decisions.CITATION:Bearman, R A, Cesare, P, Munro, S and Wandel, D, 2014. Incorporation of a full process plant model as an active constraint for mine planning and production scheduling, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 121–128 (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 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 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

By M Wortley, J Korteniemi, D La Rosa, L Rajavuori

Geometallurgical modelling of an orebody provides benefits to a mine by gaining a better understanding of the ore characteristics and how they affect the performance of the concentrator. With this knowledge, plant operating conditions can be adjusted to optimise throughput and recovery in advance of the arrival of particular ore types. Therefore, it is extremely important that the origin of the ore being processed is known as accurately as possible. Depending on the homogeneity of the ore characteristics, reliance on assumptions about stockpile residence times, scheduling and material handling can render the best geometallurgical models useless.The solution adopted at Agnico Eagle’s Kittilä mine was to utilise Metso SmartTags™ and in-house expertise to develop a system that continuously and accurately links geotechnical and lab data from the mine to the performance of the plant. This application presented several unique opportunities and challenges. For example, this was the first installation of a SmartTag™ system for geometallurgical modelling in an underground mine. Challenges included the fact that the system installation is routinely subjected to temperatures below -20°C.The system was installed and commissioned in early 2013 and has been operating continuously since. Kittilä has begun to see the benefits of the system, with an increased understanding of how different ores are processed in the concentrator. Other advantages include the ability to alert operators about the arrival of difficult ores and a better understanding of the ore handling systems.This paper describes the installation and use of the system at Kittilä and details some of the geometallurgical relationships that have been developed using the data collected so far.CITATION:La Rosa, D, Rajavuori, L, Korteniemi, J and Wortley, M, 2014. Geometallurgical modelling and ore tracking at Kittilä Mine, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 291–298 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By P A. Grossman, J H. Rubinstein, M Brazil

The installation of truck turntables at above-ground crushers has the potential to yield gains in efficiency and productivity by eliminating the need for the trucks to turn around and reverse up to the crusher to dump their loads. The benefits include savings in time, fuel consumption and tyre wear. In addition, having a smaller area near the crushers dedicated to manoeuvring the trucks can be a significant benefit at some sites. Safety is also enhanced using turntables.This paper describes a project with the Australian Turntable Company to develop software that generates near-optimal layouts for the paths taken by the trucks in the vicinity of the crushers when turntables are present or absent. The geometry of the paths is constrained by the turning radius of the trucks and by the boundary of the manoeuvring area. The software quantifies the benefit of installing turntables by generating a design for paths with turntables and comparing it with the layout in current or planned use by the mining company. Through the use of this software tool, a mining company can readily assess the benefits of using turntables at their site.CITATION:Brazil, M, Grossman, P A, Rubinstein, J H and Thomas, D A, 2014. Demonstrating efficiency gains from installing truck turntables at crushers, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 259–266 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By J Deraisme, P Epinoux, O Bertoli

"Société le Nickel exploits the Dôme lateritic nickel orebody at its Tiébaghi operations in New Caledonia. The site geology has an obvious bearing on recovery and metallurgical performance, with controls that are extremely complex at all scales, including lithology, oxydo-reduction conditions, mineralogy and multivariate geochemistry. In this context, establishing an adapted recoverable resource estimation method that is efficient and transparent proves an interesting challenge. The method must address the key notions of: support effect – the exploration data set can only warrant the estimation of large panels of 20 × 20 × 3 m3 that are much larger than the selective mining units (SMUs) of 5 × 5 × 3 m3 information effect – the selection at the production stage uses estimates based on information that is much denser than that available for mine planning.The problem is rendered more complex in this type of deposit by the fact that the additive variables used for the estimation (metal accumulation and ore tonnage) are not the ones used to establish the selection at the mining stage (ie the nickel grade of SMUs, which is the ratio of accumulation on tonnage). Eventually, the selection criteria not only involve Ni grades, but also other elements such as Al2O3, Fe2O3, MgO and SiO2.The solution presented in this paper is to construct an SMU multivariate simulation in the saprolitic horizon and construct an efficient post-processing aimed at producing multivariate recoverable resource estimates. The efficiency constraints imposed by the number of blocks to be simulated (1.5 million) lead to resorting to direct block simulations. The underlying multivariate discrete Gaussian model, which had its validity tested beforehand, is put to good use to mimic the selection process that happens at the mining stage by offering the ability to simulate a composite value located at random within each block.The paper also presents the application of a scenario reduction algorithm to pick a representative subset of a few simulations to help appraise the risk attached to the downstream (reserve optimisation and mine sequencing) phases of the project. The original version of the paper (see Deraisme, Bertoli and Epinoux, 2014) used an early version of the scenario reduction plug-in (named S2RM) built in Isatis® software, where measuring the distance between the initial set of scenarios and the reduced set was based on Ni only. The implementation presented here is for the second generation of S2RM, where measuring the distance between the initial and the reduced set of realisations is based on all study variables. The benefits of the measure adapted to the true multivariate nature of the problem are highlighted in this updated version of the paper.CITATION:Bertoli, O, Deraisme, J and Epinoux, P, 2014. Multivariate block simulations of a lateritic-type nickel deposit and post-processing of a representative subset, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 99–108 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By M Recabarren, A Echeverria, J Ronda, J I. Guzman, R Dodds, G Juarez, E Vila-Echague

A strategic mine plan is a fundamental part of any mining operation. It must provide a realistic and operative extraction and processing schedule, and yield the highest value for the business. For open pit mines, the problem can be modelled as a set of blocks representing the deposit, for each of which we need to decide if it is going to be mined, if so, when and where it will be sent (process, stock or dump).This problem can be proven to be of NP-Hard complexity. The traditional approach used by mining engineers to tackle this complexity is to separate the problem into more tractable components, solving each separately. The first step is to use the Lerchs-Grossman (LG) algorithm to obtain the final pit limit, as well as a set of optimised pit shells (nested pits), using different input prices. Then, using this input, operational phases are designed. Third, the set of phases can be used as an input for a phase-bench style optimisation, usually using a mathematical programming-based algorithm.There are, however, several problems with this approach. First, dividing the problem into simpler parts has the consequence that any compromises made at early stages limit the potential value left for the following steps. Second, LG is a static algorithm, with no concept of the time-value of money, capacity limits, opportunity costs, etc. Phase design is essentially a manual step, for which nested pits provide insufficient information in practice, and therefore the quality of the result in terms of potential net present value (NPV) depends strongly on the experience and expertise of the designer. This means that key input data such as commodity prices, different processes capacities and mine movement limits, are considered only at scheduling, when there is little room for optimisation. This sequential approach limits the potential value in each step, where a simplified problem is addressed, instead of addressing the real, and more complex problem, which is dynamic and should be solved as a whole.We present in this paper an algorithm, and its commercial software implementation, that addresses the dynamic problem as a whole, simultaneously and automatically creating a high-value strategic mine plan that adheres to basic operational constraints, determining dynamic cut-off grades and delivering a set of phases which can serve as a much stronger guide than nested pits for the final design. We discuss some of the key elements of the algorithm and propose a new methodology for strategic mine planning, where phase design dynamically responds to mining strategy definition. Results using different mining and operational parameters on a fictitious copper deposit are used as a demonstrative example.CITATION:Juarez, G, Dodds, R, Echeverria, A, Guzman, J I, Recabarren, M, Ronda, J and Vila-Echague, E, 2014. Open pit strategic mine planning with automatic phase generation, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 147–154 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By P Malkin, S Thomas, P M. Stone, D Kostyuk

In open pit mining, it is common that the bottleneck to productivity and profit lies in the truck-shovel mining operation, especially as strip ratios and mining intensity have increased with resource depletion and advances in mining equipment capabilities. This paper outlines a study of truck-shovel productivity using a new proprietary discrete event simulation platform for truck-shovel operations called MineDES. The study will specifically address the issue of whether truck queuing at shovels should be considered productive or not, and how mining engineers can determine the optimal truck fleet size for specific operational configurations.The MineDES simulation platform will be described and illustrated, highlighting the features that make it an appropriate tool for conducting the experiments at the heart of this study. The study encompasses a set of experiments, consisting of a number of simple truck-shovel operational scenarios for a benchmark open pit mining operation, which are simulated using MineDES. Each experiment is designed to highlight different factors, which are most important in calculating the ideal truck fleet size and for understanding the marginal productive impact of each additional truck added to the fleet. The scenarios will principally address the issues of how different types and levels of unscheduled equipment downtime and process variation, combined with the traffic delays/congestion arising in more intense mining operations, will affect productivity. The results of the experiments are interpreted using a simple fit-for-purpose cost and revenue model in order to highlight the indicative cost of over- or under-trucked configurations.The study has found that the optimal fleet size that maximises productivity and value will, in the presence of even small process variation, lead to non-zero trucks queuing at shovels on average. As process variations and unscheduled downtime events increase in the truck-shovel system, the required fleet size to optimise productivity and value increases. MineDES provides a convenient platform for quantifying this for real operations.CITATION:Kostyuk, D, Thomas, S, Malkin, P and Stone, P M, 2014. Is truck queuing productive?, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 267–274 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By D J. Thobaven

Project financing challenges caused by declining commodity prices have heightened the need to improve project metrics such as minimising capital payback and maximising net present value (NPV). Khnaiguiyah Mining Company (KMC) recognised the need to improve early cash flows at their Khnaiguiyah zinc-copper project after initial studies showed the project could not provide the desired financial outcomes necessary to compete for investment dollars in the current market.A significant improvement to the project cash flow in early years was realised through simultaneous optimisation of cut-off grade, mining sequence and strategic stockpiling. This improvement was achieved by accelerating mining in the pits, stockpiling lower value material and feeding higher value material directly to the plant. The schedule required higher mining and stockpile capacities than the sequential mine plan although minimal change occurred in the definition of ore and waste as measured by tonnes and grade. The practicality of the strategic schedule was demonstrated by implementation in the production plan with excellent conformance.CITATION:Thobaven, D J, 2014. An application of simultaneous optimisation – improving the payback period of a zinc-copper open cut project, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 137–144 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By E Lima, D Gregory, C Faria, A Lapworth

Open pit mine enterprises are complex systems that depend on multiple parameters such as mineral grade distribution, geotechnical characteristics, economic conditions and engineering requirements, all of which vary in time and space with a different degree of uncertainty. The unpredictable nature of these inputs imposes a risk to mine owners and shareholders which in the worst case can lead to highly undesirable financial outcomes.Desktop studies commonly examine a set of scenarios based on adjusting variables such as commodity prices, mining costs, processing costs, and metal recoveries to understand their relative impact on the economics of a project. It is less common to systematically explore and simulate hundreds of alternative physical designs to understand and compare the financial risk associated with one or more mining projects.This paper presents a risk assessment tool set and methodology that uses web based cloud computing to enable multiple simulations of mine designs to be rapidly and efficiently executed. The methodology includes generating random sets of prices and costs values within their respective probability distributions. Pit designs are then created to maximise the profit for each set of input variables. Various approaches to analysing the results are discussed. Use of the same high performance computing environment for understanding the financial risk associated with the variability of the underlying geological resource model is also discussed, with provided examples using case studies from two of the major mineral producers.CITATION:Lima, E, Gregory, D, Lapworth, A and Faria, C, 2014. Simulating extraction shapes to understand financial risk using high performance computing, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 351–360 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014