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By Michael J. Rosko

Methods have been developed for processing and analyzing reflected solar radiation data obtained by Landsat 5 Thematic Mapper multispectral scanner. Spatial resolution for the Landsat series satellites is 30 meters per side per pixel. Materials on the Earth?s surface absorb or reflect different parts of the electromagnetic spectrum depending on their physical and chemical properties and, therefore, typically have characteristic spectral ?signatures?. Using these signatures, environmental parameters such as surface water and vegetation may be identified and analyzed. Principal advantages of the satellite image method for environmental monitoring include: a relatively long historic period beginning in 1985 for which information is available, the reliable numerical basis for the results, and the ability to assemble a historic environmental baseline and provide on-going monitoring for large or remote areas where standard monitoring methods may not be practical. However, because the long-term continued operation of Landsat 5 is problematic due to the age of the equipment, QuickBird and IKONOS satellite images were processed to determine if the two systems are sufficiently similar in their results to allow continuing monitoring using QuickBird data. The QuickBird satellite was launched in 2001 and collects the same visible and near infrared spectral bandwidths as Landsat 5, allowing for equivalent process algorithms for QuickBird, IKONOS, and Landsat 5 data. Spatial resolution for the QuickBird images is 2.4 meter per side, allowing for more detailed characterization of the land surface; spatial resolution for the IKONOS images is 4 meter per side. Because of several differences between the satellite systems, including degradation of the Landsat 5 sensor, it is necessary to calibrate QuickBird and IKONOS results to the Landsat results to verify similarity. Recent images from the satellite systems have been processed and results have been compared to determine the validity of comparing Landsat 5 and QuickBird/IKONOS images so that these newer data can be used reliably in the future instead of Landsat 5 data. Results from this comparison are presented in this paper and suggest that analyses for vegetation using the two satellite systems are comparable, and that little calibration is required. Results from comparison of surface water results from the two systems are less comparable and is currently being investigated by the authors.

Oct 1, 2009

By Rodrigo A. Marinho

Erratic high grade values are as common in Nature as they are a source of problems for resource estimators. In some highly erratic metal deposits, less than 2% of the drilling samples can represent more than 10% of the total metal in the blocks and they are associated with a high risk level. There is a risk of local overestimation but also of global overestimation, with the high grades being projected over too large a volume. Capping or restriction of these outliers control is being widely used in the industry and commonly applied in resource estimation for the last three decades. The primary purpose of this paper is to present and describe the most applied methodologies for restricting the extrapolation of high grade samples and discuss the results based on a theoretical simulated model. Additionally, this paper demonstrates the economical impact associated with the high-grade and the project risk profile associated with each method.

Oct 1, 2009

By Hamid Mahmoudabadi

In the present paper, the performance of four approaches based on neural networks and geostatistical method for grade estimation are compared and analyzed their performance to find a proper method. Four methods, Multi Layer Perceptron neural network (MLP), Radial Basis Function (RBF), General Regression Neural Network (GRNN) and Ordinary Kriging (OK) are selected for ore grade estimation of variable Fe in an iron deposit located in Iran. For each method, two diagnostic statistics are calculated: Mean square error (MSE) and correlation coefficient. The results show the superiority of the General Regression Neural Network.

Oct 1, 2009

By Solar D. Andrés

Several large open pit mines are facing the challenge to design and plan an underground transition to sustain the long term future of their operations. The desired underground method is Block Cave since its natural high productivity and low operating cost that could compete against the open pit cost to mine the final open pit pushbacks. It has been found at several operations where this transition is taking place that the pit limit at which transition is performed is rather deep. This aims to think that perhaps several transition projects have started late in the life of an operation producing an over stress in the transition project and reducing the flexibility in the design of the overall infrastructure and a substantial lost in the complete project NPV. Traditionally the approach to plan open pit underground transition consists of sequentially deciding the final pit using a Lerchs and Grossman type of optimization to find the overall maximum pit shell and then running block cave simulations to find the best footprint for the underground option. The research summarized in this paper is related to the development of an integer linear programming model that aims to compute simultaneously the maximum NPV of the combined option final limit open pit and block cave underground footprint. The model has been tested using two large block models representing two of the current operations in the process of transiting from open pit to underground operations. Finally, the integrated open pit underground transition model is going to be compared to the traditional sequential approach in order to define which method achieves the best NPV. The paper illustrates both case studies in depth.

Oct 1, 2009

By Jan W. Merks

The objective of metrology in mineral exploration is to derive unbiased confidence limits for masses of metals contained in reserves and resources. Sets of test results for gold and silver determined in pairs of interleaved bulk samples give unbiased confidence limits for the central value of each metal. The same sets of test results show how to verify spatial dependence by applying Fisher?s F-test to the variance of a set and the first variance term of the ordered set. A significant degree of spatial dependence gives a higher degree of precision for the central values of gold and silver. Plotting variance terms of an ordered set against the variance of the set and its lower limits of asymmetric 99% and 95% confidence ranges gives a sampling variogram. Sampling variograms put in plain view where spatial dependence in sampling units or sample spaces dissipates into randomness. The application of statistical methods to test results for sets of ordered core samples within boreholes, and for sets of ordered ore volumes within profiles, plays an important role in defining reserves and resources.

Oct 1, 2009

By Ernest Baafi

A simulation model RoadSIM using the ARENA modelling system has been developed to evaluate roadway development options for a given development panel configuration. The RoadSIM simulation system has provisions for variability/randomness in operations including cutting and loading at the face, tramming and discharge of coal to the boot end and availability of equipment. The modelling system provides a means for assessing the operational limitations of roadway development practices at a particular coalmine. It is a ?what if? tool that allows a range of equipment, configurations and operating practices to be assessed in terms of achievable advance rates and equipment utilisation. Output from the system is in the form of a dynamic visualisation as well as summary reports and detailed logs of operations over time.

Oct 1, 2009

By Sebastián H. Troncoso

Open pit mine planning is normally based on the selection of an economic envelope that has been generated by the Lerchs & Grossman algorithm, which requires individual economic valuation of each block of a geological block model. The selected envelope, usually called Final Pit, is later discretized in pushbacks and benches, which correspond finally to the fractions that the production schedule will allocate in time. This planning methodology has been widely used by the mining industry in countless projects to exploit open-pit mines, however, in many of the deposits can be found some undesirable elements such as arsenic, phosphates, ash among others that tend to reduce the value of elements of economic interest, either by disrupting the processes of concentration or as deemed impurities that affect the quality of the final product. Thus, a fair amount of blending would be required to capture the real value of the ore body. The traditional approach under estimates a block value by penalizing the block value by the amount of contaminant even when at the mine a set of blocks is amine at a time. This paper proposes a methodology for computing cut off grades over time that would maximize net present value allowing blending that should fulfill a set of metallurgical constraints. Preliminary results show significant increases in value and reserves quantity, questioning the use of fixed cut-off grades in generating a production schedule when blending applies to fulfill a set of geometallurgical constraints. Finally, the model allows the authors to show the importance of having adequate planning tools that will lead to the ability to look at the potential economic value of a mineral deposit.

Oct 1, 2009

By Kadri Dagdelen

Recent trends of the mining project show that there will be more and more mechanized, largescale mining operations with complex process options to make low grade deposits economically feasible to develop. The global optimization of large scale, complex mine operations will become more important for the future mining. To serve the industry?s future needs, the OptiMine® software program is developed based on expertise gained at the Colorado School of Mines (CSM) for more than two decades, by using the special solution methodology based on the Mixed Integer Linear Programming (MILP) technique in the Operations Research (OR). The program has been beta-tested on more than 20 projects as a multi-time period scheduling and cutoff grade optimization tool that handles large scale open pit and underground mining operations involving complex process options, many stockpiles and dumps, blending requirements, and truck hour limitations. In each project, various operational options are evaluated in OptiMine® to develop strategic planning to help defining company?s strategies and directions. This paper demonstrates how the OptiMine® can be used to optimize a large scale, complex production scheduling problem on a case study coming from real world project. The case study describes multi-pit mine production scheduling optimization with pit backfills in such a fashion that acid generating waste rocks are encapsulated to minimize environmental impact.

Oct 1, 2009

By André van Wageningen

Since the beginning of this century Boliden Mineral and Atlas Copco have worked together in stages on improving the accuracy and quality of drilling. Navigation of the drill rigs with IREDES has been in use in the Boliden mines for several years. Recently the capability of the system has extended with map navigation to more accurately follow the ore in cut&fill mines. The system allows for changes on the individual round level to follow the ore without changing the whole design for the heading. Those changes are done in a CAD-system and remove the need for face markings and will allow for even better accuracy in both height and wall position. All the information between the CAD-system and the drill rigs is exchanged using the IREDES standard. This paper describes the workflow and the use of the IREDES standard.

Oct 1, 2009

By Jiwen Zhang

Abstract Due to the blocking nature at the crusher station, straightforward application of queuing theory cannot give realistic results on the performance of a shovel-truck-crusher system. A new queuing network-based model has been developed in which, the crusher station is formulated into an open queuing network and the whole shovel-truck-crusher system into a closed queuing network with the crusher station as a special server. To fully account for the influence of blocking, Monte Carlo simulation is first used to obtain the performance parameters of the open queuing network for the crusher station. The closed queuing network for the entire system is solved by applying the Extended Summation Method (ESUM), in which the crusher server is described by the simulation results. The model has been applied to the Yuanbaoshan open-pit coal mine to analyze its shovel-truck-crusher system and to improve its efficiency. Results indicate that the blocking at the crusher is an important factor affecting the crusher output and in turn the efficiency of the whole system, and prove that the model can realistically describe the behavior of such systems.

Oct 1, 2009

By Reik M. Winkel

Radar Technologies are successful implemented in the military industry since decades and recently found their way in the mining industry as level gauge radars for bin applications. The latest generation of microwave radar sensors are capable to provide geometrical data of the surrounding area of mining machines, too. Radar sensors are an improvement to laser scanners as they are more robust and able to penetrate dust and mist. Radar sensors will be the key source for operator assistance systems. indurad and RWTH Aachen University conducted a large series of tests at open pit mines and underground coal mines to determine the potential of the new two dimensional Dual Range Radar iDRR. Several applications were determined as highly feasible and are now completed respectively in the implementation stage. The authors are giving an insight in the experimental results, the implementation and an outlook of future applications for this technology.

Oct 1, 2009

By Jorge Amaya

A critical aspect of long-term open-pit mine planning consists in computing a production schedule based upon a block sequencing strategy. Such a schedule should specify when and if blocks should be extracted in such a way as to maximize NPV, while satisfying wall-slope and production capacity constraints. It is well known that this problem can be modeled with integer programming (IP). However, integer programming is not used in practice because the size of typical block models makes such problems intractable to standard IP solvers. In this article we describe a scalable IP-based methodology for solving very large (millions of blocks) instances of this problem. We show that embedding standard IP technologies in a local-search based algorithm we are able to obtain near-optimal solutions to large problems in reasonable time. This methodology has been tested in several mine wide block models.

Oct 1, 2009

By Zhanyou Huang

The logic and capabilities of a short-term planning tool are presented. It was developed using mixed integer linear programming (MILP) techniques to solve the open-pit and underground mine planning problems that include multiple mining areas, multiple processes, multiple destinations and blending requirements. It finds the optimum schedule that achieves the objective while satisfying comprehensive product quality and quantity requirements, equipment utilizations, as well as physical and technical constraints. A case study is given to demonstrate its applications.

Oct 1, 2009

By Shahram Tafazoli

This article presents a novel technology for sensing the size of rocks after blasting in hard rock mines. Blast engineers require rock size statistics to carefully adjust the blasting parameters. The rock fragmentation requirements vary depending on the ore type and crusher specifications. The most popular statistical parameters in the industry are the so-called P numbers (e.g., P80 and P100). A machine vision based system is introduced here for automatic image collection and fragmentation analysis of the material right inside the bucket or dipper of mining shovels. A heavy-duty camera provides the required imaging data to an embedded computer mounted inside the cab. A custom machine vision software continuously analyzes the captured bucket images and stores the suitable ones in local storage which are then fed to a Desktop software for automatic fragmentation analysis. This technology has been developed by Motion Metrics International and is commercially available as FragMetrics?.

Oct 1, 2009

By Jiwen Zhang

Due to the blocking nature at the crusher station, straightforward application of queuing theory cannot give realistic results on the performance of a shovel-truck-crusher system. A new queuing network-based model has been developed in which, the crusher station is formulated into an open queuing network and the whole shovel-truck-crusher system into a closed queuing network with the crusher station as a special server. To fully account for the influence of blocking, Monte Carlo simulation is first used to obtain the performance parameters of the open queuing network for the crusher station. The closed queuing network for the entire system is solved by applying the Extended Summation Method (ESUM), in which the crusher server is described by the simulation results. The model has been applied to the Yuanbaoshan open-pit coal mine to analyze its shovel-truck-crusher system and to improve its efficiency. Results indicate that the blocking at the crusher is an important factor affecting the crusher output and in turn the efficiency of the whole system, and prove that the model can realistically describe the behavior of such systems.

Oct 1, 2009

By Shahram Tafazoli

This article presents a novel technology for sensing the size of rocks after blasting in hard rock mines. Blast engineers require rock size statistics to carefully adjust the blasting parameters. The rock fragmentation requirements vary depending on the ore type and crusher specifications. The most popular statistical parameters in the industry are the so-called P numbers (e.g., P80 and P100). A machine vision based system is introduced here for automatic image collection and fragmentation analysis of the material right inside the bucket or dipper of mining shovels. A heavy-duty camera provides the required imaging data to an embedded computer mounted inside the cab. A custom machine vision software continuously analyzes the captured bucket images and stores the suitable ones in local storage which are then fed to a Desktop software for automatic fragmentation analysis. This technology has been developed by Motion Metrics International and is commercially available as FragMetrics?.

Oct 1, 2009

By Andrew Bamber

A fast and objective spreadsheet-based model for the financial evaluation of innovative mining and processing strategies such as pre-concentration vs. a conventional base case is presented. The size and grade of the deposit must be chosen, from which a mining rate is selected. Expected operational data for the deposit as well as any mill testwork and results from the pre-concentration testwork are entered as input variables on the sheet, and cost and revenue impacts are calculated in the ?Output? sheet. A capital sum and operating costs for the initial mine and mill development as well as the pre-concentration facility are calculated. The net changes in capital and operating costs are calculated, and impacts on revenue through changes in metal recovery are also calculated. These outputs are used to calculate the overall impact on the cutoff grade and thus the size of the mineral reserve using a generic grade-tonnage model. The NPV and NPV profile of the two scenarios is calculated, with variations in basic parameters such as operating cost, capital requirements, metal price or grade as well as discount rate. Cost and revenue impacts are evaluated and compared to the baseline to establish a positive or negative impact overall. Different scenarios of grade, tonnage, mining rate, process performance, capital and operating cost structure can be explored using the model. Outcomes projected by the model for case studies conducted thus far have been calibrated against internal estimates by the sponsoring organizations and found to be accurate to within 30%, confirming the utility of the model in practice.

Oct 1, 2009

By John W. Korczak

The use of geological and grade block models has been standard practice in mine design for many years now, with a wide range of software available for creation and analysis. Although geotechnical parameters are of vital importance to mine planning there is very little in the way of commercially available systems for integrating geotechnical data into the mine planning and design process. Sirovision is a new technology developed by the CSIRO (Commonwealth Scientific and Industrial Research Organization) in Australia for automated, safe and accurate 3D mapping of geological and geotechnical features. Datamine has integrated this capability into its product range so that Sirovision has become an integral part of the day-to-day mapping, mine geology and geological / geotechnical modeling in both open pit and underground mine environments. This is the first integrated underground application of Sirovision from Datamine collaboration with Xstrata Nickel at the Nickel Rim South Project. This paper discusses the role of Sirovision in collecting the raw data required for geological and geotechnical analysis and the interpretation in a quick, safe, auditable and reproducible manner.

May 1, 2009

Safety Leadership The management and leadership of a mining operation is a challenge at all times. The pressure to make production, safety, and environmental goals is intense. At some point mining cycles will put every operator into periods of time where economic issues seem to over-ride all other concerns. This is when leadership is most needed.

May 1, 2009

By H. O. Ghaffari

A complex network approach on a rough fracture is developed. In this manner, some hidden metric spaces (similarity measurements) between apertures profiles are set up and a general evolutionary network in two directions (in parallel and perpendicular to the shear direction) is constructed. Also, an algorithm (COmplex Networks on Apertures: CONA) is proposed in which evolving of a network is accomplished using preferential detachments and attachments of edges (based on a competition and game manner) while the number of nodes is fixed. Also, evolving of clustering coefficients and number of edges display similar patterns as well as are appeared in shear stress, hydraulic conductivity and dilation changes, which can be engaged to estimate shear strength distribution of asperities.

May 1, 2009