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By Robert Cameron, Colin Ashton, John MacNeil, Leo Piciacchia

"The in pit dam construction and utilities relocation, known as the East Mine Corridor Relocation (EMCR) project, was developed to extend the life of the east side of the Base Mine pit by two veal's. This will result in the recovery of an additional 80 million barrels of oil and delay expenditures associated with the opening of the North Mine by two years. To accomplish this, a large in pit earth structure was required to provide a new embankment foundation for relocating a public highway, four powerlines, a natural gas back-up pipeline, a substation, and a conveyor train. This structure would also he required as a temporary dam 10 contain mature fine tails on the west side until mining is completed in the east mine corridor area, that will then be filled with fluid.The in pit dam, known as The Highway Berm, is 2.5 km long, 63 m high and has 42 million m3 of engineered soil added to the already existing end-dumped soil volumes. To complete the design and construction of a structure of this magnitude, in the very short time frame of two-and-a-half years, presented many new challenges. The main challenges faced were: designing while construction was ongoing; designing without the use of clay cores or sand filters; using relatively non-select overburden material; proper dewatering and base preparation; changing from construction of 50 m high spoil piles to a high specification construction operation; compacting lifts with heavy haulers; constructing during the winter; and monitoring movement of the structure with satellites."

Jan 1, 1995

By W. C. Zhu, C. H. Wei, L. L. Niu

With an increase of mining depth, a series of mining-induced hazards such as rockburst, coal and gas outburst, roof collapse, and water burst are getting more serious and more frequent. The intrinsic mechanism responsible for the occurrence of mining-induced hazards is the damage and unstable failure of rockmass or coal seam. The most distinct difference between deep and shallow levels is the so-called three ‘high’ (H3) conditions, i.e. high geo-stress, high fluid pressure and high geo-temperature. Therefore, the response of rock or coal to the deep mining operation is a phenomenon involving thermal (T), hydraulic (H), and mechanical (M) processes. Most importantly, mining excavation may vary the rock stress condition greatly, which may be a key factor to trigger the mining-induced hazards such as rockburst. In this regard, it is of great significance to clarify the damage and failure mechanism of rock and coal under coupled THM conditions, in order to clarify the rock failure mechanism responsible for the occurrence of mining-induced hazards. Thereafter, the mining-induced hazards cannot be predicted with confidence by considering each process independently. Of course, the requirement to include coupling of these processes depends on the specifics of the mining-induced hazards under consideration. For example, the water inrush is considered as a coupled hydro-mechanical (HM) process, in which the unstable failure of rockmass occurs under the combined contribution of geo-stress and water pressure. As for the coal mining at depth, in addition to high geo-stress and gas pressure in coal seam, the high geo-thermal condition that may greatly change the adsorption / desorption of gas and gas flow should be taken into account. Firstly, a general-purpose mathematical model for rock damage and failure process under coupled THM conditions is formulated based on damage mechanics principle, and it is solved by finite element method (FEM). In this model, the deformation and damage of rock, fluid flow and thermal transfer in rock would interact with each other, one process affects and initiation and progress of another. Then, the model is used to predict the mining-induced water outburst, where it is simulated as coupled hydro-mechanical (HM) problems. Based on the numerical simulation, the dimension of water-proof pillar is designed. Finally, the gas drainage from deep coal seam is numerically evaluated, where the coupled coal-gas interaction considering the effect of gas adsorption/desorption, gas flow in coal seam and geo-stress and geotemperature, is comprehensively taken into account. The proposed model could be used for clarifying the mechanism of mining-induced hazards in deep-level mining.

Jan 1, 2015

By Libao Zhu, David J. Williams, Nazife Erarslan

"Statistics show that the drawbell in underground mines is usually subjected to significant damage by impact loading due to falling ore. Drawbell damage causes a large quantity of residual ore to remain on the drawbell, thus leading to a huge waste of ore resources. In this study, the Cavity Monitoring System (CMS) and Surpac software were employed to visualize the 3-D damage. Also, the Discrete Element Method (DEM) was employed to perform simulations of the falling ore to investigate the damage evolution of drawbells under repeated ore impact and obtain the dynamic damage accumulation mechanism. The reason of drawbell damage was found due to the micro-shear cracks. The numerical simulations of a drawbell damage process under repeated impact loading showed the main failure type was shear failure and this type damage was found increasing with more ore falling. INTRODUCTIONDrawbells are an important part of underground mines and play a significant role in ore recovery in terms of safety, economy and efficiency (Brunton et al., 2010; Hustrulid & Bullock, 2001; Trueman et al., 2002). In most cases, blasted ore is gravitated along the drawbell and finally arrives at the footwall of the drawpoint. However, some of the blasted oversize ore blocks clog the drawbell road and those ore pieces are called hang ups (Penswick, 1997). However, any damage on a drawbell is believed to be the reason for these hang-ups. In the literature, researchers have reported that the stability of the draw-point is influenced by the stress distribution above and near the drawbell (Butcher, 1999; Neverov & Neverov, 2013). Much research in the literature has been done on draw-points in underground mines. In fact, rockfalls cause very serious damage on a small impact area in a very short time (Volkwein et al., 2011). Hoek (2000) pointed out that the blasted ore causes progressive ravelling and even collapse of the drawpoint, thus the ore in the stope is abandoned. In this paper, the Cavity Monitoring System (CMS) was employed to obtain the damage profile of a drawbell due to the impact of rockfalls and to confirm the residual blocking ore on the damaged drawbell. Then, the drawbell damage evolution due to repeated falling ore was simulated by the Discrete Element Method (DEM)."

Jan 1, 2015

By Alim Ullah

Danieli entered into the Direct Reduction (DR) field in order to offer its clients complete turnkey facilities for steelmaking?from processing of raw materials through finished products. The Danarex® Process produces a passivated product, called the Supermetallic (SPM), without hot-briquetting. One of the main features of the Danarex® Process is its ability to produce approximately 50% of the Direct Reduced Iron (DRI) through reduction gas generated in a reformer and another 50% through recycling preheated furnace exit gas. Some other distinguishing features are: separation of carburising and cooling zones and the use of double bustle for better distribution of gas inside the shaft furnace. A pilot plant was set up at Hazen Research, Inc., Golden, CO in order to show that the integrated process works as expected and to obtain process data. The SPM obtained was of a very high quality, evidenced by metallization levels of 92% to 98%. The carbon content could be controlled between 1.5% to 4.0% by varying the operating conditions and approximately 75% of this carbon was present as Fe3C. The product was tested for inertness by Chilworth Technology, England, using UN standard tests and was found to be safe for outdoor storage and transportation.

May 1, 2003

By Marco Quirion

The Daniel-Johnson dam, formerly named Manicouagan-5 (Manic-5), is located 800 km northeast of Montreal (Quebec) in Canada. This is the largest multiple-arch concrete dam in the world consisting in 13 arches and 14 buttresses. Since its construction in 1969, various type of cracks have appeared on both downstream and upstream faces of almost all the arches of this concrete dam. As a part of the Daniel- Johnson’s dam safety assessment program, Hydro-Québec is currently performing structural analysis of the dam with advanced numerical models to better understand and predict the dam behaviour. Because the buttresses transmit all the arch loads to the rock mass, determination of the properties of the dam foundation should not be neglected in dam global safety analysis and also to insure that reliable input parameters are used in the dam numerical simulations. This paper summarizes the past and the more recent investigations of this foundation used to assess its safety and stability. Moreover, the use of rock mass classification to estimate the deformation modulus, based on empirical equations, gives values in the range of 30 to 40 GPa that are higher than expected values. Using those values in the numerical simulations for dam structural analysis gives an excellent correlation with displacements monitoring of the buttresses.

Jan 1, 2015

By G. A. Witwicki

"The Thyssen Mining Group of Companies has successfully applied ground freezing technology to numerous projects throughout Europe and North America for over 100 years. Recently, the aspect of data acquisition and data verification has received greater focus.Thyssen Mining has been engaged in several relatively deep shaft sinking projects over the past five (5) years, all of which have required ground freezing to successfully sink through water bearing rock. To safely and economically sink through a quantity of water similar to Saskatchewan’s Potash Mines, it is imperative to understand freeze wall thickness and growth rate.Critical to understanding freeze wall thickness and growth rate, is the collection of accurate data as well as the interpretation of those data. The data can then be utilized to gain a better understanding of the freeze wall growth rate in active projects as well as to provide data to be utilized in modeling for future projects.This paper elaborates on the installation and operation of the data acquisition system utilized at the Newmont Leeville project, Nevada’s first frozen shaft project. In addition, this paper elaborates on the methodology developed by Thyssen Mining to manipulate the freeze wall data derived through the data acquisition system.The successful incorporation of the new system of collection and analysis of freeze wall data for the Leeville Project has given Thyssen Mining a high degree of confidence in the understanding, as well as prediction, of the ground conditions during shaft sinking.This paper will include:•,A brief description of ground freezing and its objective;•,An overview of previous data acquisition methods employed;•,Current data acquisition methods;•,Installation requirements; and,•,Data manipulation and presentation methods."

Jan 1, 2015

By A. Wright, P. Lacombe, R. del Villar, D. Hodouin, C. Sepulveda

"The data acquisition from industrial plants is a fundamental step for process modelling in process optimization, process analysis and automatic control.The introduction, some years ago, of modern distributed control and data acquisition systems in concentrators imposes a new approach in designing experimental schemes for data acquisition campaigns and new criteria for the treatment of the obtained discrete information.This paper presents the methodology applied to sample a zinc flotation circuit at Les Mines Selbaie, Joutel, PQ. Values of 85 process variables were obtained form the Distributed Control and Data Acquisition System (Bailey Network 90) and transferred to the DOS environment. Another 11 variables (flowrates and valve positions) were directly sampled using an IBM-PC compatible computer equipped with a data acquisition card and a signal processing circuit.All variables, under the vector form, were processed in the PC-MATLAB environment to either filter or eliminate the non-linear disturbances and noises, producing useful data for model development. The filtering algorithms are also presented.INTRODUCTIONProcess control does not need to be justified. Whether manual or automatic, any processing plant requires some form of control to accomplish its main objectives: a good quality product and a target throughput. Process control of mineral processing plants has steadily evolved from manual control, where the operator skills and/or experience play an important role, to some level of automatic control, usually considered better, as less human subjectivity is involved, at least when actions have to be taken.The design of these control systems requires the knowledge of the dynamics of the process it is deemed to control. Process modelling is therefore an essential step in the assessment and the design of a control strategy. The choice of model will depend on the available resources and manpower."

Jan 1, 1991

By Jeonghwan Kim

Intelligent Excavation System (IES) has been considered to be one of the desirable solutions to improve the productivity, quality and safety of the current earthwork processes. IES is composed of various hardware and software modules including task planner (work command generator), local and global work environment sensors, GPS and other sensors to acquire the excavator?s status, robotic controller and electronic valves, and the manipulator (excavator). A data communication manager was required to coordinate the signal or data-flow in between these modules considering the operational status of IES such as; excavation start/completion, truck detection, terrain model update, emergency stop, local sensing, GPS/motion sensor data handling, and so on. This paper presents the role and functions of this data communication manager. After every possible operational status of IES operation was identified, a protocol of each communication process in the form of string-type was made. The components of IES are connected with either wired or wireless network. Therefore, they can communicate with the manager using socket (TCP/IP) communication. The data communication manager is also capable of accessing a web-based project management information system, which constantly updates the performance of excavation robot to online database.

Aug 1, 2013

By S. Dessureault, J. Porter, M. Woodhall

Information and communication technology (ICT) is seen as a key source of future productivity improvements in mines. The information technology infrastructure (ITI) necessary to achieve these productivity improvements will come in the form of data integrated from multiple source systems throughout the mining value chain. Two pure approaches are available: supplier-controlled or operations controlled data structures; each strategy has its own advantages and disadvantages. Case studies involving the South African mining industry are used to demonstrate the advantages of using hybrid-controlled data structures. Depending on the level of operational control, new skills are also necessary to be learnt by mining professionals including: information engineering; creating consistent and quality data; and process improvement techniques that use the integrated data for improving the operation.

Jan 1, 2004

By S. Goodman

Successful exploration for and exploitation of a mineral deposit requires an accurate understanding of the deposit architecture in 3D, and of the development of the mineralizing system through time, which requires a thorough comprehension of the structural framework of the deposit. The integration of geological, geophysical and geochemical datasets to arrive at a 4D structural framework is well-established and has been successfully applied by SRK Consulting in projects from deposit to regional scale. In some cases, we can go beyond this, applying the SEEBASETM technique, which utilizes a ?bottom-up? approach to basin analysis. SRK?s approach primarily relies on the interpretation of magnetic and gravity data, calibrated with many other datasets including mapped geology, topography, event histories, wells/drillholes and seismic data. The SEEBASETM model is a culmination of this data integration and is produced through an iterative process of structural interpretation and geophysical modeling, where an interpretation of basement composition and 4D structure is used to constrain depth-to-basement geophysical modeling, and the modeled depths are then used in conjunction with the structural interpretation to constrain contouring of the basement topography. The result is a rigorously calibrated, 3D view of the basement surface, which can be used to understand the basement and basin architecture, and thus serves as a predictive exploration model. This technique, which was developed for use in the petroleum industry, is now finding success as a predictive tool in mineral exploration.

May 1, 2003

Today?s Topics ? Data to decision value chain ? Practical Considerations ? Example ? Before / After DSS ? Quick Decision Support Demo Practical Considerations ? More data is not necessarily better ? Organization and process silos ? Good vs. ?optimal?, but impractical Solutions

May 1, 2008

By Sylvain Létourneau

Help organizations maximize the benefits of the data that they collect ? perform scientific research in: machine learning, data mining, statistics, artificial intelligence, soft computing, information retrieval, information systems, and natural language processing ? preferred application areas: Equipment Health Management, Bioinformatics, Health, Web Mining ? today?s talk limited to Equipment Health Management While the aircraft is still in the air, IDS: ? clusters relevant WRN, FLR, and snag (pilot) messages ? identifies probable causes based on TSM and provide links to corresponding TSM pages ? assesses MEL conditions (GO, NOGO, GOIF, ?) ? displays relevant maintenance history, suggests fixes based on similar cases ? Commercialization with MxI Technologies Ltd and Air Canada in 2000

May 1, 2008

By S. Dessureault, M. Yildirim

More mining companies are now investing in IT, including updating one of the traditional IT process control tools used in the mining industry: real time in-pit truck allocation control and monitoring systems, or fleet management systems (FMS). These systems have been used to maximize the overall mine production by improving equipment utilization and reducing production costs. Most modern operations monitor the in-pit operations using GPS and wireless communications to produce data. Improvements in bandwidth, sensors, and computing power are causing modern systems to become more complex and generate more data. However, human analysis by simple regression or table generation in spreadsheets of the data is becoming impossible. Data mining solves this data management problem. Data mining finds patterns and relationships in very large data sets. This paper describes the application of modern data mining techniques on truck dispatching systems in a real open pit hard-rock copper mine. The analyses conducted included determining how the trucks performed under particular conditions and allocation systems. The long-term benefits of this work are to identify strengths and improvement opportunities in truck assignment systems and establish the skill sets and IT infrastructure needed in undertaking more complex datadriven technology such as a truck dispatcher trainer.

Jan 1, 2007

By S. Dessureault

The relatively recent explosion of available data in all business sectors has induced a common expression of “drowning in data, starving for information.” The mining sector is affected by the information age through equipment-based sensors, process monitoring, and traditional enterprise data sources. Information technologists have developed techniques such as data mining that apply new and old statistical algorithms to large datasets. Mine planners and managers can apply these tools for improved planning and control, thereby increasing the use of the highly underutilized information system infrastructure in most modern mines. This paper describes the use of data mining and its enabling technology, data warehousing, in the development of an energy consumption model for large surface mines using real historical data.

Jan 1, 2007

By Ken Witherly

Modern airborne EM surveys typically acquire more data than is processed or analyzed at the time of acquisition Suitable additional processing can provide more diagnostic information, thereby allowing for more effective ranking and hopefully, follow-up of outcomes

Apr 1, 2005

By K. El-Ouassiti, M. Zouadi, C. Bazin, D. Hodouin

Data reconciliation techniques are used to attenuate the effect of measurement errors and estimate unmeasured variables. This paper illustrates the application of data reconciliation to hydrometallurgy processes using measurements from leaching and solvent extraction obtained from laboratory experiments. The application of data reconciliation provides an efficient way to detect gross and systematic errors and produces reliable performance indices for process evaluation.

Jan 1, 2005

By A. Alfantazi, M. Mahon

The current efficiency in zinc electrowinning is a key indicator of the performance in a cell house. This is typically measured by comparing the weight of the cathode to the electric current applied over the deposition period. This calculation can be cumbersome because the deposition history of each pulled set of cathodes will be unique. It will depend on the applied current and electrolyte conditions from onset of deposition until the cathode is removed and stripped. Not accounting for these can introduce errors to the calculated current efficiency. To track this history and reconcile the current efficiency, a time based computer process simulation was made of an industrial cell house. Two months of hourly recorded measurements from the cell house were input to the simulation, including current to the cell houses, concentrations, flow rate, and temperature of the purified leach solution. The simulation’s predictions of the concentration of zinc in the circulated, spent, and returned electrolyte all showed good agreement with the industrial data over the two months giving a validated zinc balance. The simulation was then tuned to predict the instantaneous current efficiency for all times, as well as the expected masses for the deposits given their deposition history.

Jan 1, 2014

By B. Samanta

Abstract - Ore reserve estimation, based on sparse drill hole data, was conducted for a placer gold property in Nome, Alaska. A problem with sparse data is that random subdivision of the data into modelling and evaluation subsets (as is commonly done) becomes a problem, as random selection may result in biased/skewed subsets. Therefore, a technique that combined data segmentation with genetic algorithms (GA) was applied to divide the samples into three equivalent subsets: training, validation and testing. Data segmentation was done on the basis of the distribution of gold values. Neural network and a variety of kriging techniques were used to estimate gold grades. A multi-layer feed forward neural network along with "early/quick stop" training was used for neural network modelling. A comparative evaluation of kriging and neural network methods was then performed. The results revealed that neural network was generally superior to the kriging techniques for gold grade estimation in the Nome deposit.

Jan 1, 2002

By Frédéric Flament

The aim of this paper is to present the development of a data validation software as component of a commercial mass balance package. Data reconciliation through mass balance is basically an optimization problem constrained by the law of mass conservation. As any optimization problem solved with a modern and robust software application, erroneous information or starting point will always lead to a solution, whether it is realistic or not. Moreover, good information wrongly weighted by an incorrect error model will lead to the same bad ending. In an industrial context where competition requires accurate information, data reconciliation without validation can be disastrous and calls for data validation before and after reconciliation. The challenge in automated data validation resides in the development of general theoretical solutions. Until now, none has been presented and only partial solutions are available. The development presented in this paper incorporates some of these partial solutions. The integration of human knowledge into the application paved the way to a more general solution. The combination ?theoretical validation ? human expertise? proved to be flexible and reliable enough to be integrated in a commercial data validation package. Numerous examples though industrial applications are presented. These applications demonstrate the validation of raw measurements, user support in the development of error models and validation of reconciled measurements.

May 1, 2001

By Deborah A. McCombe

"There are a number of important dates that must be disclosed when a Qualified Person (QP) is preparing a technical report for securities purposes. The dates are discussed in NI43-101 and the Form of the Technical Report, NI43-101F1. •,Effective date of the technical report •,Possible revision date of the report •,Effective date of mineral resources and mineral reserves •,Date of the personal inspection (site visit) •,Signature date of the date report (execution date) •,Date of the certificate of the QP •,Date of the consent of the QP The effective date of the report is basically the cut-off date for the information that is included in the technical report. The effective date should be close to the signature date. If there is too long a period between these dates, the QP runs the risk of new material information becoming available and then the technical report would no longer be current. The effective date is disclosed on the title page of the report and on the signature page. If a technical report needs to be revised to correct problems or disclosure deficiencies identified by the regulators, the QP will normally need to include a revision date on the title page of the report to distinguish the revised version from the original version. In these circumstances, the regulators will request that the original date of the report remain on the title page and the revised date will be below it. When a technical report must be revised, the QP must resign and date the signature page of the report and provide a new certificate and consent."

Jan 1, 2003