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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 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 M Aros, L Reilly

Iron ore is normally sold in bulk at certain specifications. These include iron grade and specific contaminant grades, typically silica, alumina, phosphorous and sulfur. These target grades are normally agreed between the mining company (producer) and the steelmaking company (customer).This study presents an alternative to traditional cut-off grade calculation, using linear programming that maximises the total ore inventories within a predefined mining envelope while meeting the specified targets. Providing a feasible mining sequence that maintains the target grade is not covered in this study.The method was applied to Fortescue’s operations. The complexity arising from differing ore quality within each mining horizon, variable yields and upgrades and the need to control iron and contaminant grades provided a good opportunity to test an alternative method of ore selection. The new method significantly reduced the time spent in cut-off selection and sensitivity analysis, and provided an optimised solution.CITATION:Aros, M and Reilly, L, 2014. Ore selection optimisation for an iron ore deposit using linear programming, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 345–350 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By C Fricke, R Wood, P Velletri

"In a climate characterised by an ever increasing focus on cost reduction and maximising the utilisation of existing assets and infrastructure, understanding the uncertainty associated with alternative investment and operational choices becomes paramount to minimising the risk of making an ineffective decision. To assist in this process, TSG Consulting has developed an analytic framework to capture the underlying complexity of a mineral supply chain, and then quantify the impact of the uncertainty associated with the key drivers of business productivity. The technical basis of this approach follows three distinct steps: analyse the current system and identify the major factors that drive value build detailed models that can measure the response of the system to potential changes in the factors identified quantify the sensitivity of financial and capacity forecasts to these factors.Each of the above steps draws on a different area from the field of applied analytics, namely: data analytics dynamic modelling and designed experimentation meta-modelling and optimisation.Following the three-step approach described above ensures a rigorous modelling and analysis process is executed to support strategic mine planning decisions. The approach is equally applicable to the analysis of fully integrated system supply chains (pit-to-port), the evaluation of incremental capital investments to targeted areas of a supply chain, or when considering revisions to the operating philosophy of a system in the short term. The basis of each of the three analytic steps is explored in detail in this paper. The result is the definition of a structured mechanism for a business to actively manage risk and drive productivity as a component of the strategic mine planning process.CITATION:Fricke, C, Velletri, P and Wood, R, 2014. Enhancing risk management in strategic mine planning through uncertainty analysis, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 275–280 (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 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

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 D W. Airey

Frictional rock bolts are widely used because of their low cost. However, they have a thin wall section that makes them prone to corrosion, and they cannot be relied on to provide long-term ground support. It is difficult to assess the capacity after the bolts have been installed as they can only be pulled out if this has been allowed for during insertion. The questions of how long can the rock bolts function effectively and the effectiveness of various surface coatings, which can have significant cost implications are, investigated in this study.A series of accelerated corrosion tests have been performed on frictional rock bolts. The rock bolts, typically 900 mm long, have been inserted into concrete cylinders produced using a styrofoam insert to create the hole for the bolt insertion. Strata rock bolts with four surface coatings have been tested: uncoated black steel, galvanised, enduro (plastic coated) and coated with a proprietary aluminium/zinc alloy. Tests have been performed on two diameters of bolts. Following insertion of the bolts, the concrete cylinders were placed in a large drum filled with saltwater and current was applied to accelerate the corrosion process. The rock bolts were then extracted at various times after the commencement of corrosion. Comparison of the insertion and extraction resistances shows that corrosion initially increases the bolt resistance and that substantial section loss is required for the bolt resistance to drop significantly.CITATION:Airey, D W, 2014. Laboratory corrosion tests of frictional rock bolts, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 257–262 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By B Jones, M Chappell

Installing ground support correctly is not an easy task, whether lack of operator training, poor ground conditions or underperforming equipment. Confirming the quality of installation can help with planning and remedial works and help to maintain a safe working environment. A 2?m bolt with 700?mm of encapsulation will pass a 10?t pull test (assuming ground conditions permit); however, it will not provide any data of the unencapsulated length and thus the ability to withstand corrosion. Complimentary testing in the form of non-destructive testing (NDT) can provide factual data that leads to the assessment of the quality of the encapsulation. By improving the quality of the encapsulation, the risk of corrosion is reduced, the ground support durability is improved and hence the asset life is enhanced.This paper presents a case study of a trial using the NDT system RokTel™. Installations of varying quality were installed and tested. The characteristics tested were corrosion, load and free length. These characteristics can be tested and assessed for cable bolts, thread bar bolts and split sets. The aim of this paper is to present NDT testing as a viable method for assessing installation quality and ongoing performance of the ground support.CITATION:Jones, B and Chappell, M, 2014. A non-destructive testing method for measuring bolt condition, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 307–314 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By M J. Dunn

The geotechnical model is the cornerstone of any mining geotechnical design and as such the confidence level and reliability of the geotechnical model is paramount. The geotechnical model confidence level needs to be commensurate with the level of design that is being applied or study that is being undertaken. The geotechnical model is made up of several components and the reliability of the data underlying these components ultimately determines the reliability of the geotechnical model.Data reliability is linked to the quantity of data collected, the spatial distribution of the data collected, quality of the data collection and the interpretation of the data. In a typical project, there is an opportunity to improve data reliability through the scoping, prefeasibility, feasibility and final design and implementation stages.Currently, very little quantitative guidance exists in the literature on assessing the confidence level of geotechnical studies, although there have been attempts by various authors (Haile, 2004; Haines, Swart and Kruger, 2006; Read and Stacey, 2009; Dunn, Basson and Parrott, 2011) to qualitatively describe what level of geotechnical data is required. Recently a number of authors (Read, 2013; Fillion and Hadjigeorgiou, 2013; Thomas, 2013) have outlined methods that could be applied to assess the reliability of some types of geotechnical data that are used in the development of geotechnical models.This paper briefly discusses some of the factors influencing data reliability and the geotechnical model confidence and some of the tools available.CITATION:Dunn, M J, 2014. Geotechnical models and data confidence in mining geotechnical design, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 127–134 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By I D. Gregson, A Gandhe, A S. Garcia, K M. MacAndrew

"Falls of ground still cause around one-third of all underground mining fatalities. The recent introduction of mechanised room and pillar working into Indian coalmines is an example of the application of new design by measurement and safety monitoring strategies, which can be used to reduce falls of ground risks in mines.Rock Mechanics Technology, now part of Golder Associates UK Ltd (Golder), is providing rock bolt support and pillar design services to the mines using a design by measurement approach. This involves in situ monitoring to confirm support and pillar designs and pillar extraction sequences.Site examples are given of the support designs determined and the monitoring programs undertaken for both design and safety.Routine safety monitoring of roof movement using telltales is also described. A new auto warning telltale has been developed specifically to warn of imminent caving as pillars are extracted.The approach used by Golder has played a major role in ensuring the success of these projects. As a consequence, mechanised room and pillar working is now firmly established in India, and wider application is planned to help meet future demand for coal.The experience confirms that the design by measurement method for this application has important advantages over conventional design approaches using analytical or empirical methods. Firstly, it measures the design performance or outcome rather than trying to calculate or predict it. Secondly, it provides the opportunity for the design to be adjusted to obtain the optimum outcome. Thirdly, it can do this at a local level, so that the support design can be matched to changing conditions to give the most cost-effective design. Finally, it incorporates long-term monitoring of support performance, again at a local level, so that subsequent change can be identified to enable corrective measures to be implemented in a timely manner and to ensure that ground control safety is maintained.CITATION:MacAndrew, K M, Garcia, A S, Gregson, I D and Gandhe, A, 2014. Application of design by measurement for support and pillar design in mechanised room and pillar coal mining in India, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference, pp 65–76 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 5, 2014

By F M. Weir, M Fowler

The design of excavations in rock must, implicitly or explicitly take into consideration the influence of small- and large-scale geological structures. For most sites the complexity of a fractured rock mass is best captured using a 3D fracture system model based on field data. A discrete fracture network (DFN) approach involves stochastic modelling of the ‘smaller scale’, nondeterministic structures. For slope stability or tunnelling projects DFN modelling provides a valuable geotechnical tool for characterisation of a rock mass and identification of likely failure mechanisms.This paper presents a suite of the DFN modelling undertaken for the design of a large open pit in Australia. The proposed pit is to encounter a 160?m thick, high strength, sheared shale unit, which overlies a crystalline basement. DFN modelling was undertaken separately for both the shale and basement units. While the model inputs and development for each unit are briefly presented, the focus of this paper is on the various applications of the DFN modelling.A key advantage of the DFN approach for design studies is its probabilistic application to structural analyses and results. Multiple realisations of the same model were generated for both the shale and basement units, with the stability analysis carried out on each iteration. The generation of a large number of DFN models and analyses allow assessment of wedge volume, factor of safety and proportion of unstable slope for a range of conditions. The DFN modelling at the case study site was also utilised for a number of other purposes. For example, investigation of likely fault lengths in the shale unit and combined rock mass and defect failure. The development of this tool has been influential in improving our understanding of fracture networks for excavation design.CITATION:Weir, F M and Fowler, M, 2014. Rock mass characterisation and analysis for excavation design – a discrete fracture network approach, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 445–456 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By A Duran

When dealing with rocks in the geotechnical profession, a common activity involves providing an estimate of the intact strength. The tactile approach and descriptions of strength that apply to soils is well documented, can be readily checked through the use of a pocket penetrometer and are known to provide reliable estimates of strength. Moreover, although different soil strength classification systems are present, the bounds between classification classes are compatible across almost all documented classification systems. However, this is not the case for rock strength materials. There are numerous systems within the literature, some with different concepts, and almost all have different bounds to each strength classification. In this paper, the author presents seven classification systems for estimating intact rock strength and highlights issues in their implementation. Example cases are presented to discuss the typical concerns confronting field strength estimates.CITATION:Duran, A, 2014. Comparison of field estimated strengths, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 101–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By I D. Gregson, A S. Garcia, K M. MacAndrew

The design work undertaken by Rock Mechanics Technology (now part of Golder Associates (Golder)) has played a major part in successfully establishing mechanised room and pillar working in Indian coalmines, both for the development of new districts and for the re-establishment of old districts prior to pillar extraction on panel retreat.Golder has used appropriate design of pillars, extraction sequences and final snook sizes to minimise ground control risks during pillar extraction. Where the strata will not cave reliably, partial extraction systems leaving either a crush pillar or a substantial yield pillar have been adopted.Remote monitoring of selected pillars during the extraction process using stress cells, extensometry and convergence measurements provides confirmation of pillar behaviour and verification of designs.A new telltale device, giving a visible warning of impending caving, is now installed at all Indian pillar extraction sites and is proving very successful.CITATION:MacAndrew, K M, Garcia, A S and Gregson, I D, 2014. Coalmine pillar design and performance during mechanised pillar extraction in India, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 347–358 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By L Tatnell, R Mackay, A Tolooiyan

The multi-reversal direct shear test (MRDS) method is commonly used to measure the residual shear strength of soils. However, when the standard direct shear (DS) apparatus is used, the MRDS method is prone to two major sources of error: load cap tilting and specimen loss. These two sources of error can cause erratic behaviour in the residual shear strength curve, making it difficult or even impossible to determine the correct residual shear strength value of the specimen being tested. This paper presents the results of new modifications to the standard DS apparatus that prevent load cap tilting and specimen loss. Consolidated drained testing was performed on highly-over consolidated cohesive soil samples from a Latrobe Valley open pit mine, with results obtained from the modified DS apparatus showing a great improvement in the residual shear strength profile compared to those obtained using the standard apparatus. Large numbers of reversals (up to 14) conducted on a single specimen in the modified DS apparatus showed no notable load cap tilting and no specimen loss occurred. The modifications are easily applied to the standard DS apparatus, and analysis and correction of the data are simple.CITATION:Tatnell, L, Tolooiyan, A and Mackay, R, 2014. Measurement of residual shear strength using a modified direct shear apparatus, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 425–434 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By T J. Sullivan, H Pinkster, G Swarbrick

From 2002 to 2006, longwall mining was undertaken directly beneath the Cataract Tunnel, which is a 100-year-old, heritage-listed tunnel in Hawkesbury Sandstone responsible for delivering 20 per cent of Sydney’s annual water supply. At one location, undermining resulted in movement of at least 350 mm along a known fault that transects the tunnel. During this movement, the continued operation of the tunnel was ensured through a careful system of planning, monitoring and management.Of key importance to the success of the operation was the use of advanced numerical modelling to guide operations at all levels, including feasibility assessment, pre-mine mitigation works, monitoring design, operation performance and post-mining condition. This allowed many aspects of the potential impacts to be explored, including joint movements, rock mass deformations and changes in permeability. A key challenge was to successfully model near-field influences on adverse geological structure due to very far-field effects. This paper explains the model’s conceptual development, calibration, performance and limitations.Modelling provided the confidence to manage the impacts of large mining-induced movement on key infrastructure and ultimately predicted fault movement accurately. The fault movement remains one of the highest ever recorded due to mine subsidence.CITATION:Swarbrick, G, Sullivan, T J and Pinkster, H, 2014. Longwall mining beneath critical infrastructure – prediction versus performance of the Cataract Tunnel, New South Wales, Australia, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 157–166 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By A M. Myrvang, B Nøst, N Q. Trinh, I S. B Bergh

The iron ore producer Rana Gruber AS is situated in northern Norway just below the Arctic Circle, and has been producing hematite and magnetite concentrates for more than 60 years. Since the late 1990s, the major part of the production comes from a sublevel stoping underground operation after many years of open pit mining. Despite moderate mining depth, the operations have experienced considerable rock stress problems due to quite high tectonic, horizontal stresses. To manage the problems, comprehensive rock mechanics investigations have been carried out by SINTEF, a major contract research organisation. This has included in situ rock stress measurements, laboratory investigations and numerical modelling. Based on this and practical experience, satisfactory design of vertical and horizontal pillars was achieved. At depth, the ore width increases from 30–40?m to more than 100?m. This, together with a major planned increase in production, called for a change of the mining method. After thorough investigations and considerations, it was decided to change to sublevel caving, very much like the LKAB system. The development of the new system has been closely followed up by rock mechanics measures, including 3D numerical modelling and comprehensive monitoring of deformations and rock stress changes. To achieve a satisfactory caving of the hanging wall, all vertical and horizontal pillars in the sublevel stoping area had to be removed. This has been a challenging task, and the development of the caving has been slow until recently. However, now the caving develops satisfactorily.CITATION:Bergh, I S B, Trinh, N Q, Myrvang, A M and Nøst, B, 2014. From sublevel stoping to sublevel caving at Rana Gruber, Norway – rock mechanical aspects, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 323–330 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By M Zoorabadi, B Hebblewhite, S Saydam, W Timms

Based on the cubic law, the hydraulic aperture of rock discontinuities has the most significant effect on the hydraulic conductivity of jointed rocks. The hydraulic aperture of rock discontinuities is a stress-dependant parameter and reduces with increasing applied stress. Furthermore, the rock stress increases with increasing depth. Therefore, hydraulic aperture is a depth-dependant parameter. In this paper, new empirical equations are introduced to calculate the hydraulic aperture of rock discontinuities at different depths. These equations were developed on the basis of back analysis of compiled packer tests from different actual cases. They provide the capability to calculate range of variation and average hydraulic aperture when the orientation of discontinuity and field stress tensor are given. Furthermore, it is possible to calculate the hydraulic aperture of rock discontinuities when its value is given for another depth. A hydraulic aperture of 7.7?µm was calculated by this method, comparing well with a reported site value of 8.3?µm for rock discontinuities at the Stripa mine project at a depth of 385?m. These new equations can be used by analytical or numerical methods to estimate the hydraulic conductivity of jointed rocks.CITATION:Zoorabadi, M, Saydam, S, Timms, W and Hebblewhite, B, 2014. New empirical equations to estimate the hydraulic aperture of rock discontinuities at different depths, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 375–380 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By L M. Zhang, X Y. Li

Surface displacements are routinely monitored at multiple points during slope excavation. The monitoring data reveals the safety status of the slope under current loading conditions. They can be used to enhance the prediction of the future performance of the slope by reducing the uncertainties of the prediction model and its model parameters. In a multistage excavation, the observed displacements in the current stage can be used to update the prediction of the displacements in subsequent stages. Besides, due to the spatial correlation of the slope parameters, the prediction of the displacement at one location can also be updated using the monitored displacements at adjacent locations. This study aims to develop a multistep updating method to enhance the prediction of the future performance of the slope using time-series monitoring data at multiple points. This method integrates the theoretical computational model with observational evidence. It considers the inherent uncertainty of the slope, model uncertainty and measurement uncertainty. With more monitoring information being incorporated, the prediction becomes closer to the actual performance of the slope. A case study of a multistage excavation of an extremely high rock slope in south-west China is presented for illustration.CITATION:Li, X Y and Zhang, L M, 2014. Better prediction of performance of a slope using time-series monitoring data at multiple points in a multistep excavation, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 183–188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014