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By E Rubio, N Morales

Currently, mine plans are optimised by using several criteria as objective functions, like profit, life-of-mine, concentration of some pollutants, mining costs, confidence level or ore resources, with consideration of constraints related to production rates, plant capacities and grades. Whilst this approach is successful in terms of producing high value production schedules, it uses a static opening sequence of the drawpoints and therefore the optimisation is made within the level of freedom left by the original opening schedule, and as a result it is far from the true optimal value of the project. This paper presents a model to optimise the sequence of drawpoint opening over a given time horizon. The emphasis is in the precedence constraints that are required to produce meaningful operational sequences considering the exploitation method (panel or block caving), physics considerations and logical rules. Further on, while it applies the standard approach of maximising net present value (NPV), it considers other targets for optimisation, like the robustness and constructability of the plans. Finally, it applies the model to real data to obtain feasible plans by means of this model. The first tests were done varying the production capacity of the mine.

Sep 26, 2011

By I Douglas, L Allen

Localised indicator kriging was developed following a similar approach used by Marat Abzalov (2006) in his paper titled æLocalised uniform conditioning (LUC): A new approach for direct modelling of small blocksÆ. Abzalov introduced the idea of mapping panel distributions from uniform conditioning onto selective mining unit-sized blocks that were created using ordinary kriging. This concept of remapping panel distributions was applied to multiple indicator kriging histograms.At Newmont a program was developed that made the remapping of MIK histograms to SMU sized blocks extremely efficient and was subsequently tested on several gold deposits. The results have been encouraging as the localised indicator kriging (LIK) method has eliminated many issues that have plagued both ordinary kriging and multiple indicator kriging. Use of localised indicator kriging methodology limits the smearing of high-grade and the over-smoothing of grade that is common and difficult to control in OK but retains the ability for localising grades. LIK also simplifies change-of-support corrections, eliminates un-mineable slivers of low or high-grade when dealing with small tonnages, and allows for the mapping of linear and non-linear estimates into the same block.

Sep 26, 2011

By S D. Dessureault

The largest surface coal mine in North America requires complex materials handling infrastructure to fulfil the highly variable quality specifications of its contracts. These diverse demands, reflected in the arrival of numerous customer trains every day, necessitate the integration of information in every stage of production. To meet this goal, quality measurement, train line-up and mine planning processes are being integrated into local and remote control rooms. The effectiveness of such a system can only be measured by comparing decisions that are made with, and without, each of the individual integrated control systems. Traditionally, mine controllers use their experience, intuition or a variety of trial-and-error spreadsheets to determine the ideal materials handling flows needed to achieve the correct quality. These balanced decisions are complex since many factors must be considered such as the mine plan, fleet costs, quality variability and others; consequently mine controllers usually have widely varying success between crews.An evaluation model was developed to assess the impact of a decision support system (DSS) integrated in a control room for controlling the coal blending process. To this end, an ARENA-based simulator representing the whole production process can be used to pull performance and current materials handling settings directly either from the real-time systems in the mine, or from historical data. In this way, the same shift (breakdowns, cycle rates, etc) can be simulated and performance compared. Different settings of the DSS, in terms of what information is displayed and the methods for doing so, can be tested for effectiveness. The historical data are extracted directly from a corporate data warehouse, without altering the everyday working databases. At the same time, the simulator writes its results back into the same data warehouse structure, allowing the same KPI reports to be used to measure simulated shifts.

Sep 26, 2011

By A Noack

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

Sep 26, 2011

In this paper a quantitative deterministic risk modelling approach (Quadrim) is introduced. The mathematical framework and equations for quantifying uncertainty within and aggregating across value chain nodes from error propagation techniques is proposed and discussed. A case study and worked examples, based on a hypothetical mine are then presented. This illustrates how uncertainty from the mining and economic value chains can be handled in a typical net cash flow calculation, and how this can be translated to a risk model. It is then illustrated that current valuation techniques do not just result in an information gap for decision makers. Traditional approaches such as discounted cash flow (DCF) analysis and truck and shovel productivity analysis, which do not take into account uncertainty in input values, can result in potential bias in estimates such as net present value (NPV) or equipment hours

Sep 26, 2011

By J V. Mehrabani, A R. Sayadi

Adequate estimation of equipment costs is a key factor in a feasibility study and in evaluation of design alternatives for mining and mineral processing projects. Inaccurate early cost estimation could lead to the elimination of investment benefits. However, this estimation is complex and time consuming because of data accessibility problems and consequently access to a rapid, up-to-date and accurate tool is desirable for carrying out cost estimations.This paper describes the development of models for estimating capital and operating costs for a jaw crusher, which is used as the primary crusher for a wide variety of mineral beneficiation plants, applying single and multivariate regression analyses, together with the design of experiment approach, based on principal component analysis. Explanatory variables include gape size, length of feed opening and power as numeric (quantitative) variables and toggle type (single or double) and the existence of extra heavy duty construction as categorical (qualitative) variables. The performance of each model has been investigated and comparing the estimated R-squared (R2) of each model, the best was selected and its validity examined. The cost models include the capital and operating costs along with the operating cost components. The results indicate that the suggested best cost model is sufficiently accurate for use in feasibility studies.

Sep 26, 2011

By D Wyborn, P A. Dowd

The characterisation of rock fracture networks is an important component of rock engineering applications involving stability assessment or fluid flow analysis. However, the derivation of a reliable rock fracture model remains a very challenging problem in practice. This paper describes a Bayesian framework, in the form of Markov Chain Monte Carlo (MCMC) simulation, for the construction of such a model. Model conditioning using different data sources is discussed including seismic events recorded during hydraulic fracture stimulation, rock face fracture mapping data and downhole geophysical survey data. The freeware FracSim3D is used for the simulations.

Sep 26, 2011

Real-time data collection and plant historians are becoming common place in mining and processing plants. This vast quantity of data must be turned into easily accessible and actionable information for all levels of the organisation.Queensland Nickel use a combination of Microsoft and SAP business intelligence tools to collect, cleanse, aggregate and present plant information to the appropriate people for supporting decision making in the business. SAP Business Objects, for visualisation, and SAP MII, for integration, allows complex and accurate metrics to be delivered as real-time dashboards. Designing a rigid data management architecture to segregate the data collection, integration and logic and visualisation into distinct logical layers, allows for rapid report development and greatly assists with IT maintenance, while also minimising the complexity of any customised programming. This type of architecture ensures a common data source for all business reports, ensuring one version of the truth. The past few years at Queensland Nickel have seen process and maintenance engineers spending considerably less time collecting and integrating data and spending more time analysing what is happening in the plant. Real-time reports and dashboards have been developed around the business needs rather than around the data. Two years ago Queensland Nickel introduced an employee bonus scheme based upon meeting monthly performance targets; an easy to use dashboard that allows everyone, from operators through to management, to monitor these metrics day-to-day.

Sep 26, 2011

By A Esfahanipour, M Osanloo

Determination of cut-off grade?strategy is one of the most important stages of open pit mine planning and design. It is the parameter directly influencing the financial, technical, economic, legal, environmental, social and political issues in relation to mining operation. Choosing the optimum cut-off grade strategy that maximises the economic outcome has been a major topic of research workers for nearly one century. Many researchers have contributed in devising methods and algorithms, such as dynamic programming, linear programming, optimal control and so on for various aspects of its determination. In this paper, a non-linear mathematical programming for cut-off grade strategy optimisation is presented, considering the three main stages of mining operation introduced by K F Lane. In this model maximisation of net present value of mining operation, under the three constraints of mining stagesÆ capacities, considered as the optimisation criteria. Due to the discrete representation of the mining resource, the proposed non-linear formulation is approximated by a non-linear signomial geometric programming. According to non-convexity and the complexity of the proposed model, an augmented Lagrangian genetic algorithm was used to find the optimum cut-off grade strategy under varying and fixed price circumstances. To validate the proposed non-linear model efficiency, the results were compared with the results obtained by the K F Lane methodology. It was found that the proposed non-linear model works efficiently in the determination of cut-off grade strategy. According to the simplicity of the structure of non-linear programming modelling in comparison with dynamic programming it is hoped that, further development of this model would certainly provide the ability of considering managerial and technical flexibilities as well as incorporating more real mining conditions in the determination of cut-off grade strategy optimisation.

Sep 26, 2011

By P Lukic

The definition of the working sections that will be used in a mine is usually initially made in the field by the geologist supervising the drilling program. These initial definitions are often made on the basis of rules of thumb such as æcoal less than 30 cm thick cannot be mined separatelyÆ; æpartings more than 30 cm thick will be mined separatelyÆ; and æif a coal seam is less than 50 cm thick and the parting above or below is thicker than the coal, the coal will be wastedÆ. These decisions are also often made based on the requirement for a minimum sample mass for analysis, and the desire to collect data at the minimum resolution to conserve the exploration budget.In many cases the geological models based on this data are produced at a resolution that is inadequate to allow the mining engineer to produce a mine plan that will maximise project value. This problem is generally unrecognised.Where data is collected to a higher level of resolution the subsequent processes employed in the production of geological models and mine plans often discards the inherent value that is hidden in this data. Again this problem is generally unrecognised.This paper highlights this problem and then presents a methodology that ensures that the optimal working section is selected and compares the outcomes of applying this methodology versus adherence to the usual rules of thumb.

Sep 26, 2011

By C Augustin, M Hahn, K Nienhaus

Operators of mining machinery like haul trucks or excavators have very limited information about the exact distance to other equipment as well as to the natural boundaries like berms, walls and structures such as crushers. The industry is seeking solutions to provide safety and positioning. The authors have developed a solution approach which is being used in several installations. This solution consists of three parts: first robust and compact two-dimensional (2D) radar scanners that provide range and angular information of the environment especially under difficult conditions like dust, rain, snow and fog; second an intelligent data processing framework flexible enough to adopt to different machines and operation modes like speed, inclination, visibility, tire friction, GPS position, orientation and acceleration; and third a high quality and easy to use interface giving highly condensed data to the operator, not blinding the operator at night and being sunlight readable. The truth of present proximity detection sensors is that they not only have a high false alarm rate but furthermore cover only a fraction of the possible scenarios. This makes them unsuitable for stand-alone collision avoidance systems. On the other side, mine dispatch systems only deliver database and GPS information, but no information regarding the real environment. The indurad company and its Australian partner CTS (http://www.cts.com.au) addressed these aspects by developing smart productivity enhancement driver assistance tools like lane and crusher dumping assistance.An innovative driver assistance tool developed in cooperation with the coal shearer manufacturer Eickhoff and the RWTH Aachen University has been awarded with the annual research award of its customer RAG, being the largest German hard coal producer, as well as with the bauma Innovation Award in 2010.

Sep 26, 2011

By M Armony, J F. C L Costa, J C. Koppe

Linear kriging methods fail to estimate local grades and local reserves for highly skewed variables due to three reasons: it uses only part of the available data information, it has no physical principles associated with the mathematical proceedings to minimise the problems, and it works with continuous variables while data are discrete because of the limited precision of any equipment. The techniques commonly used up to now to solve the highly skewed variables estimation problems were unsuccessful, unless mathematical rigor is abandoned. Even the method of multiple indicator kriging is not satisfactory. This paper presents a new framework, the field parametric geostatistics (FPG) that transforms noisy variograms into well-behaved variograms and justifies mathematically empirical procedures commonly used, as trimming or capping arbitrarily very high values. The method, when applied to non-skewed variables, yields similar results to classic kriging. The methodology is illustrated in a case study at a gold deposit in Brazil, and compared to results obtained by usual techniques.

Sep 26, 2011

By F Ramos

Conventional techniques for resource estimation generally involve the laborious analysis of variograms and the specification of parameters for covariance functions. In large deposits, construction of resource models and their update require significant amount of manual work, expert knowledge and time. In this paper we take a machine learning view to the problem of resource estimation. This is a non-parametric Bayesian method, leading to automatic parameter estimation (learning). Through Bayesian learning, the parameters of the model can be obtained by optimising a quantity known as the marginal likelihood. The main advantage of this approach over conventional maximum likelihood estimators is that the objective function incorporates the OccamÆs razor principle. This allows the comparison of different statistical models û for example, models designed with different covariance functions û and naturally penalises complexity, thus avoiding overfitting. Our technique presents significant flexibility for the definition of mean and covariance functions and permits the usage of more sophisticated models.The second contribution of this work is the formulation of a data fusion mechanism that continuously updates the resource model. As mining progresses, more information becomes available. For example, the hardness of the rocks can be measured while drilling blast holes, grades of ore and contaminants are obtained from cone logging. This information is in general available at a finer spatial resolution but can be more uncertain. The data fusion mechanism can seamlessly estimate the uncertainties of the different types of information and fuse them as new measurements are acquired. This procedure can significantly improve the quality of the resource model, defining new grounds for stochastic mine planning. We demonstrate the effectiveness of our approach in estimating iron ore deposits by integrating information about different grades.

Sep 26, 2011

By R Razanatsimba, A Galli

A mining company has entered into contractual commitments to supply certain quantities of its product to clients in each time period. Failure to fulfil its obligations would damage its reputation as a reliable supplier. The planned production would normally be sufficient unless major problems such as highwall failures, roof falls, natural disaster, or strikes that interrupt production or delays in obtaining environmental permits, occur. To overcome these difficulties, the company may be able to obtain more of the commodity: from its strategic stockpile (if there is sufficient there); by buying it on the spot market; or for some commodities such as gold and uranium, by leasing it. Two sources of uncertainty, the spot price of the commodity and the occurrence of serious incidents that interrupt production, are considered. For simplicity it is assumed that the commodity price follows a geometric Brownian motion, that productions incidents have a binomial distribution, that they are independent from one time period to another and that they do not affect prices. A branching tree structure is used to model the joint evolution of prices and production incidents. The aim of this research project was to evaluate the companyÆs options for fulfilling its contractual commitments. When evaluating these options, multi-stage stochastic programming with recourse was used to solve this problem because in addition to providing the dollar value of the project, it gives decision-makers the æroadmapÆ to reach the optimal value. That is, how much material should be bought/sold on the spot market, how much to add to/subtract from the stockpile, how much to lease and in the worst case what the shortfall would be, for each time period as a function of the current spot price and breakdown status. A case-study over a five-year period is used to illustrate the proposed procedure. In this study the production would be sufficient to cover the companyÆs contractual commitments unless production incidents occur. Focus is on evaluating the impact of the quantity initially in the stockpile on the value of the project when the commodity market is tight, that is, when only small quantities can be bought on the spot market or by leasing.

Sep 26, 2011

By B F. J Kelly

Multiple-point simulation is a family of methods used to generate conditional facies simulations that present the same spatial dependence as a user-defined training image. The main advantage of using a training image is the easy integration of geological concepts in numerical subsurface models. The strength of multiple-point methods is that it allows making the best use of geological expertise when data are too sparse for inferring a model of spatial continuity. However, despite being appealing to geologists, the multiple-point methods are often not used in practice due to the difficulty of building complex 3D training images that contain realistic features.A new framework for multiple-point simulation is presented that involves small and simple training images. The main idea is to use random transformations to expand the range of structures available in the simple training image. The training image is not regarded any more as a global conceptual geological model, but rather a basic structural element of the subsurface. Complex geological structures are obtained, whose spatial structure can be parameterised by adjusting the statistics of the random transformations, based on field data or geological context. In most cases, such parameterisation is possible by adjusting two numbers only. One advantage is that the training images are so simple that they can be easily built even in 3D. The method allows building 3D models that reproduce shapes corresponding to a desired prior geological concept and are in phase with different types of field observations, such as orientation, facies or geophysical measurements. The flexibility of the approach allows for naturally integrating different types of data. This is demonstrated on an example involving seismic data assimilation. Examples where complex 3D folded structures are built from a simple training image and a few orientation data are shown.

Sep 26, 2011

By Q Wang

Net present value (NPV) has been the main criterion in mining project evaluation and production plan optimisation. It is a common practice in NPV calculations to take into account only the tangible cost items in the corporate accounting system. The costs incurred due to damage to the local ecosystem and environment are left out and treated as externalities. Such practice on the one hand underestimates the total cost of a mining operation and, on the other hand, ignores the difference in ecological/environmental impacts between different mine plan alternatives. This paper attempts to measure the ecological costs of mining and to incorporate such costs into the evaluation scheme in mining project evaluation and mine planning. The ecological costs of mining are estimated based on the areas and types of land (eg forest land, grazing land, crop land) damaged by mining activities and the carbon emission from fossil fuel consumption. For the land areas (and their associated ecosystems) directly damaged by mining activities, the ecological costs are measured by the prevention and restoration costs, the lost values of eco-services of the damaged land, including bio-product production, soil erosion control, water run-off control, oxygen release, air pollutant absorption and formation of soil nutrients. The ecological cost of carbon emission from the energy consumption of a mining operation is measured by the cost of cultivating the equivalent forest land required to uptake the emitted carbon. A case study on a large-scale open pit mining project is presented to demonstrate the influence of ecological costs on the mine planning outcome.

Sep 26, 2011

By P Hatherly, A Melkumyan, D Wyman

Chemical species distributions in rock sequences can be modelled using Gaussian processes (GPs) to predict the weight percentage between known data points. This method can be improved by dividing the modelled area into regions of different mineralogy. In the context of many iron ore deposits, marker shales give the initial guidance of where these regions may lie. These shales give rise to distinctive peaks in the natural gamma downhole logs, which are conventionally identified by hand. A GP method has been developed to automate this task.Once the appropriate boundary has been located on the basis of shale occurrences, chemical assays from exploration drill holes are used to find the exact boundaries of interest. These boundaries divide the drill hole stratigraphy into regions of different mineralogy, each of which display their own distinct correlations between the main elements and oxides (Fe, SiO2 and Al2O3). Iron ore shows a negative correlation between Fe and Al2O3, but in banded iron formation (BIF) there is a positive correlation between these species. Similarly, SiO2 and Al2O3 have a positive correlation in the shales and ore but a negative correlation in the BIF. Correlations obtained within ore-, BIF- and shale-dominated regions are therefore better than those obtained using the entire log and can be used to improve the results obtained when modelling.

Sep 26, 2011

By D Cai, E Baafi

Various enabling technologies and systems have recently been introduced in the mining industry. Such systems include miner-bolters with concurrent cutting and bolting, employment of two shuttle cars, adoption of self drilling bolts and utilisation of continuous haulage or monorail systems. The paper discusses how Flexsim discrete event simulation models were used to assess how these proposed mining systems can best be used to achieve and sustain high roadway development rates of 10 m per operating hour for 20 h/day.

Sep 26, 2011

By R Paterson, A Christensen

The routine use of gravity gradiometry for the detection of orebodies with no outcrop is now being undertaken. The commodities and orebody styles range from banded iron ore formations to volcanogenic massive sulfide (VMS) style polymetallic deposits. This recent innovation of flying gravity gradiometry was pioneered by BHP Billiton and Lockheed Martin with the Falcon technology (Lee, 2001), and now two additional systems, also using Lockheed Martin instruments, are deployed. In South Africa, magnetic gradiometry is being developed and deployed with the same objectives in mind. In this case, a system from Institute of Photonic Technology (IPHT) is being used. The detectable wavelengths from such systems have decreased to less than 200 m in the last year, and it is expected in 2011 that wavelengths to less than 100 m, with anomaly signal strengths of less than 2 Eotvos for gravity gradiometry will be viable. The key to these advances lies in the improvements of processing software and geological modelling. In particular, methods using all the tensor components are starting to be routinely deployed to filter, level and grid the observed signal. These methods do, however, require full insight and understanding of the reference coordinate systems used by the various instrument designers and survey operators. The digital terrain models need also to be observed to an accuracy of better than 20 m cell sizes, using such techniques as Lidar. Then the terrain effects can be modelled. The topographic surface represents the largest and most proximal density contrast encountered in an airborne survey. Hence terrain effects can have significant impact on airborne gravity gradiometry data. A decorrelation of the terrain effect with the observed signal requires a method of best fitting with a regional surface density. A novel technique has been developed for this purpose. This technique uses a tensor algebra to estimate a density between 1 - 4 g/cc that explains the average observed signal. Armed with this result, the anomalous buried bodies can be revealed by subtraction.

Sep 26, 2011

By E Cunha, D Roldao, TáTamantini, J F. C L Costa, T Webber, C Monteiro

The main problem of geostatistical simulations is to reproduce the real characteristics of the mineral deposit when there are few conditioning data. In this case, the geological interpretation, based on structures, geophysics and geological maps, plays the major role in terms of resource evaluation.The paper investigates the use of principal component analysis (PCA) to help classify multiple geostatistical categorical simulations considering the similarity among them and the interpreted model, herein referred as training image (TI).An iron deposit with four lithological facies, in a specific horizontal plane, was used as case study for two-dimensional (2D) simulations. Sequential indicator simulations (SIS) was used to obtain ten equally probable 2D images, which were generated and compared against the interpreted model (TI).In this study, 11 random variables are comprised by the vector of ten SIS realisations plus the training image (TI). The similarity between the TI and each SIS realisation is measured using the angle between the TI and SIS vectors projected in the new coordinate systems (PCA factors). It is possible to order the SIS realisations from the highest to the lowest PCA factor taking into account the TI similarity.The visual analysis of the images shows coherence in the PCA results as a method to measure similarity. This methodology can be used as a post-processing tool to rank simulation results and to select the ones which better represent the prior known geology or to compare the quality of different methods of simulation.

Sep 26, 2011