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By D Thornton

Geologists use large data sets and spend many hours and much computing time modelling the distribution of minerals throughout a rock mass. Significant investments in drilling, assaying and quality assurance and quality control (QA/QC) are made before sophisticated geostatistical techniques are applied to the collected data. A large amount of research has been done in this field such that the ore control model is a reasonably accurate reflection of the mineral that is actually in the ground. However, after all this effort, the mining engineers then work just as diligently to blast the in situ rock mass to a particle size that can be efficiently handled and further reduced by downstream comminution processes. In open cut mines, this invariably requires large amounts of explosive energy that displaces the ore boundaries from where the geologists originally defined them. Failure to accurately account for blast movement will result in misclassification, whether that is ore to waste; low grade to high grade; sulfide to oxide; or other contaminates û collectively referred to as ore loss and dilution. The financial consequence of getting this wrong is substantial and not well quantified. This diminishes all of the good geological QA/QC done in defining the ore. This paper discusses various technologies used to physically measure blast-induced orebody movement and the difficulties in modelling this with a purely theoretical approach. Rock mass structure, blast energy, design and timing contours all have significant and interrelated effects on blast movement vectors. Measured blast movement has a large variance due to the uncertainly of many of the controlling parameters û arguably dominated by the heterogeneous nature of the rock mass. Although there have been significant advances in blast movement modelling capability in recent years, this unpredictable blast movement limits their use in the context of production ore control. Certainly, without physical field measurements, accurate predictions of movement are near impossible.Limitations of traditional surface markers in determining three-dimensional (3D) blast movement within the orebody are also reviewed, and advancements in accurately measuring these vectors within blasted ore discussed

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 Mavroudis, M Gaastra

Due to the increasing demand for resources worldwide, efficient utilisation of raw material deposits and recycling technologies become more and more important. Growing industrial nations and increased living standards require a large raw material supply. Hereby responsible handling of existent primary and secondary raw materials is indispensable. By utilising state-of-the-art technologies resources are extracted, recovered and recycled more efficiently which increases sustainability. Hereby sensor technologies combined with intelligent data processing systems in particular provide a considerable research area. Innovative sensor technologies are already implemented during recognition of material-specific characteristics, during elemental recognition as well as during machine control. They are applied to attain increased automation levels of mining machineries, higher recoveries during mining and processing as well as higher recoveries. To be able to face the increased demand for sensor technologies and the integration into raw material industries, an interdisciplinary association of three RWTH Aachen University Institutes has been founded. The association has expertise on increasing productivity and capacity utilisations by automating mining and recovering processes by sensor technologies. Due to the utilisation of sensor systems, materials and structures can now be detected and elementary analysed on a real-time scale. The developed and enhanced techniques are the key for any ambition of autonomous plants and machineries. This paper gives an overview on the regarded sensor technologies for material recognition, machine automation and mineral processing. The authors present concepts based on extensive laboratory and field studies of successful implementation and application the technologies considering special mining conditions. Overall three applications are described to demonstrate the potential of sensor technologies for autonomous and sustainable mining: real-time analysis: recognition of elementary compounds during extraction processes; multi-sensor system EiControlPlus: designed for automation of longwall shearers by complete detection of the machineÆs environment; and sensor-based sorting: applied in recycling and mineralÆs industries.

Sep 26, 2011

The cloud transform simulation is a technique used to generate realisations of correlated attributes. The principle of this technique is to partition the scatter diagram between the input attributes into several interval classes and derive for each class a cumulative distribution function (CDF) using only the data pairs of the scatter diagram in that class. The simulation then proceeds like a traditional Monte Carlo simulation but using the derived CDF in each class.The cloud transform simulation has the advantage of being a simple and fast technique that is able to reproduce the uncertainty in the relationship between the two input attributes regardless of whether the relationship is linear or not. However, the technique has three major drawbacks. First, the number of classes has an impact on final simulated results and there is not a robust approach to define such number. Second, simulated results exhibit some saw tooth variations that are unrealistic and third the reproduction of the spatial continuity of the simulated attribute is not guaranteed.This paper presents the use of the quantile regression approach in order to overcome the first two disadvantages of the cloud transform simulation. Details of the technique and how it can be coupled with the cloud transform simulation are presented along with a real case study.

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 Q Qian, M Karakus, J Wang, N Melkoumian, D Goodchild, Q Sui, C Wang

Probabilistic analysis is widely used in slope stability assessment because of its capability to take into account uncertainties associated with geotechnical parameters. There are, however, still many unresolved practical issues to the application of the method. One of these issues is the integration of assessments when multiple sets of fractures are considered for the entire slope. In the present study, this issue is addressed within the framework of Monte Carlo simulation. Probability of failure for pairs of fracture sets are assessed independently and the final assessment of the probability of failure for the entire slope is done using conditional probabilities. Prominent Hill open pit, in particular, the problematic fresh Bulldog shale formation, was used as a case study to test the method proposed. The SWEDGE program of the RocScience software package was used for the analysis.

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 V Gau, L Overmeyer, M Kesting

Economically efficient mining processes can be significantly assisted by the implementation of sensor technologies for the detection of materials and boundary layers between materials inside the stratum. These sensors are meant to facilitate the machinery operator and illustrate furthermore the prerequisites in assisting tools towards fully automated mining equipment. Therefore, project æSensory Identification of Material Type and Detection of the InterfacesÆ (SIMT) aims at the integration of ground penetrating radar (GPR) and geoelectric sensor technology by endowing with them a bucket of a bucket wheel excavator. For this reason, a sensor bucket was developed and tested in the Inden Mine of RWE Power AG. The feasibility of integration and deployment of such sensor technology has been proven effective for the conditions of open cast mining. The main focus of current research lies on developing algorithms to analyse the acquired measurement data from the sensors to automatically detect layers and materials. A computer network receives the GPR and geoelectric measurement data as well as the positioning data of the sensor bucket. The positioning data mainly consists of GPS and encoder information, which is merged with the sensor data by using the UTC time stamp. With the aid of consecutive processes the relevant information will be extracted and provided to the user. The aim of SIMT is to replace material identification, traditionally carried out by the operator, by implementing a continuous operating interpretation system in mining equipment based on GPR and geoelectric sensor technology, resulting in more detailed information regarding the working face during an excavation. This detailed information provides an opportunity for efficient planning and controlling of selective mining of natural deposits, such as the process of lignite mining.

Sep 26, 2011

The paper provides an overview of the development and content of APCOM symposia since their inception in 1961. This development is set within the context of the academic environment in which much of the research published at APCOM symposia is conducted. This environment includes rigorous external assessment of research quality at national levels and against international benchmarks, which carries significant consequences for funding and for the continued existence of the academic minerals industry disciplines. Adverse consequences that undermine the academic provision of mining and resource engineering will impact negatively on the minerals industry by reducing the level of research and education resources available to it.The traditional reductionist approach to research is contrasted with the inter-disciplinary approach that is required to address the complex systems problems that the minerals industry will have to address to ensure its technical, economical and environmental sustainability. Such an approach offers a means of raising research profiles, of establishing mutually beneficial academic-industry engagement and provides an opportunity for APCOM to take a lead role in identifying the research and development agenda for the future

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

By G van Niekerk, M Wortley

Screening is a critical part of many mineral processing circuits and keeping the aperture of the screening media within specification is vital to ensure efficient performance of the processing plant. Typical ways of estimating and/or measuring the wear of the screening media vary from very subjective methods (for instance, using the human eye) to manually checking the width of a few of the more severely worn gaps with a measurement device. Subjective methods can be flawed by human error while manual checking can distort the polyurethane or rubber materials that are used in several types of screening media. All of these errors can cause either premature replacement of panels or, even worse, poor screening of the material.Metso Process Technology and Innovation (PTI) and Metso Screening Media Solutions (SMS) have developed an innovative method that measures screen aperture using advanced image processing techniques. Field trials of the device are presented in this paper, which shows the comparison between the different methods of measuring apertures. Case studies demonstrate how the system, when combined with ScreenTrack, MetsoÆs industry leading maintenance system, and screening media, is providing users with the best possible screening solutions.

Sep 26, 2011

By E Nettleton, A Melkumyan

A probabilistic system for autonomous tracking of excavated ore in mining would be highly valuable. Currently, mine sites can have a vast array of sensors; examples include excavator load cells, bucket volume estimators and haul truck strut pressures which can be used to gather information about the excavated ore at different locations. These sensors can be utilised efficiently to increase the accuracy of mine estimates by introducing a real-time ore tracking system. This requires the introduction of a probabilistic ore tracking framework to consistently fuse information from any sensor input. Current modelling practices are manually intensive, deterministic (no recognition of the quality of data) and generally not a complete end-to-end system. This paper will provide a novel method for tracking extensive ore properties (mass, volume) and intensive ore properties such as chemical composition (eg Fe per cent, SiO2 per cent, Al2O3 per cent). This method is proved to ensure that correct correlations between states are conserved as material is transferred, combined and/or separated at different locations with any configuration of sensor inputs. This ensures that consistency of estimates is maintained and other benefits such as real-time probabilistic reconciliation can be implemented. A method for combining material of different mass and chemical compositions is also developed to enable accurate and efficient operation of the system. Representative experiments on a small-scale and a larger field trial which mimic the mining processes of excavation, haul and unload to ROM Stockpile will be used to verify the approach.

Sep 26, 2011

By S D. Dessureault

In large coal strip mines, there are many different processes at work: stripping, overburden removal using trucks/shovels, cast blasting, slot dozer pushing, more fragmentation and further truck/shovel benches. A key component to each of these steps is the use of machines. In modern operations, most machine costs are tracked within Enterprise systems that transact costs and repair work order management. Similarly, in contemporary mines most machines are tracked using technology that provides precise performance measures for each key process. Such technologies include productivity monitors on draglines, dozers and drills and fleet management systems for trucks and shovels. Linking these two sources of seemingly disparate data û costs and performance by machine û would allow for the precise calculation of unit costs by specific machine. This is similar to an activity-based costing system, except in this machine-based system, calculations are made at an even finer granular level. There are many uses for such an integrated information system in mine planning and performance management, both in real-time and through historical analysis.A real-time fleet costs (FLC) measurement process was developed as part of a larger blending-related, multi-million dollar project centred on a centralised remote control room developed at the University of ArizonaÆs Mining Information Systems and Operations Management Mine Control Center. The FLC component of the overall blending system would allow a mine controller to manage the equipment fleet by viewing its cost in real time and, when mixed with other revenue-related components, the exact profit. For example, a mine controller may show high utilisation while still maintaining a production surplus. This could occur, for example, if the equipment is driven long distances. This might appear in traditional performance metrics as æhigh production performanceÆ, but in reality may prove less profitable. This paper discusses the technical development of the FLC, its deployment and its impact on controller performance, and compares mine profitability before and after its application.

Sep 26, 2011