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By Jeanie Wills, Theresa Nyabeze, Samantha Espley, Donna Beneteau

This presentation reports survey findings that aim to modernize the definition and understanding of the term 'mining.' The survey, conducted via LinkedIn in Winter 2024, garnered responses from a diverse group of individuals, including current or former employees of mining or exploration companies, mining consulting firms, service providers, supplier firms, as well as students and retirees with industry experience. The data, ethically approved by the University of Saskatchewan, offers valuable insights into satisfaction levels within the mining sector and suggests an expansion of the identifying characteristics of definitions of mining. This marks the third CIM gaining insights paper by Beneteau, Espley, and Nyabeze, following previous works on 'Career Satisfaction for Women in Mining' (2010) and 'Mentorship Initiatives in the Canadian Mining Industry' (2018*)."

Oct 1, 2024

By A. Ghahreman, M. Oliazadeh

"Heap leaching is an attractive process for low grade deposits where the metal content of ore does not justify the high cost of milling and agitated leaching. In general, the heap leaching capital cost is low, construction is rapid, and production costs are low. The primary disadvantage of heap leaching is low recoveries (typically 65% of agitated leach recovery); thus, recovery improvements could convert more lower-grade deposits into minable reserves. This will also allow to process primary sulfide ores and result in a dramatic expansion of the technology, as ~80% of total ore types are sulfidic in nature. The old gold operations tailings are another massive source of low-grade gold material that can be retreated by the heap leach process. The major parameters affecting the recovery rates are ore characteristics (mineralogy, particles size of metal and host minerals, ore permeability), and operational conditions (segregation of ore, compaction, leach cycle time, lift height, and solution application rates). The design of a percolation leach process is based on a limited number of coarse ore bottle roll and/or column tests under ideal conditions. The economics of the projects and engineering design of the process facilities are developed based on the bench scale test work results and the application of the conventional engineering scale up factors. This paper will deal with the parameters affecting the HL efficiencies and focus on the potential improvement of gold heap leach recoveries. This would include design of heap leach operation and evaluation of processes such as fine crushing and bioleaching.INTRODUCTION Gold heap leaching is a hydrometallurgical process designed to treat amenable low-grade gold ores that contain typically 0.5 to 1.5 g/t gold (Marsden and House, 2006; Wong Wai Leong and Mujumdar, 2010). Ore is stacked by various types of equipment on an impermeable barrier, and a sodium cyanide solution is applied to the surface of the stacked ore. Gold, silver, and other metals contained in the ore are dissolved to various degrees by the cyanide application, as it percolates downward through the stack of the ore. The pregnant leach solution (PLS) is then collected at the bottom of the heap. The PLS is then sent to the gold recovery plant where the metals are extracted. The barren leach solution (BLS) is then reapplied to the top of the pad. Ore is placed on a pad or previously leached lift by various means, including ramp conveyor belts, radial-arm and self-leveling stackers, and trucks. Once trucks are used to construct the pads, the pad can be compacted and hence the pad should be graded and ripped or scarified (roughened up) with wheeled or tracked equipment to produce shallow cuts to increase surface area exposure to the leachate."

Jan 1, 2019

By Carricajo T., S. Nazari

This paper discusses a unique dynamic solution for optimizing comminution area in real time. The proposed technology is a combination of model predictive controller, optimization methods and real-time digital twin for mineral processing. For grinding area, the ultimate goal of an effective control strategy is to maximize the mineral processing, reduce energy consumption and stabilized size classification. To have a continuous and effective comminution operation, a reliable control system that minimizes the need for human intervention is necessary. The implemented advanced control strategy for comminution area consists of two layers in hierarchical structure. The lower layer objective is to stabilize the process stabilization using model based predictive controller (MPC) technique. The unique MPC used in this layer is called BrainWave™ chosen for its robustness, convergence and delay handling; furthermore, the developed platform offers stable and repeatable solution and has short implementation time. The upper layer is a supervisory control, which sends the preferred process operation points to the lower layer to drive the process towards optimal performance. The goal of this layer is to optimize the process targets, as well as making decision. To increase process performance, automatic ore characteristic adaptations are implemented in this layer. A digital twin of comminution area is built in the second layer that runs amongst the process in parallel. By communicating, the process data in real time, a virtual densitometer is built that is being used in our advance process control strategy. Our control strategy has been developed, tested and implemented in various areas of a copper concentration plant. The targets for implementing advance process control are usually increased throughput, decrease energy consumption and variability reduction in particle size distribution. Overall, the results showed in different mine sites are increase throughput between 2 and 5%, specific energy consumption reduction about 15% and process variability reduction up to 60%. In this paper we discuss the results of the recent implementation of this technology on Minera Los Pelambres, Minera Collahuasi and CAP Minería. Their concentrator plants have installed control systems with the most updates optimization features, for SAG mill, ball mills and thickeners.

Jan 1, 2019

By S. Espley, T. Nyabeze, D. Beneteau

"Many mentorship programs are available to Canadian mining industry employees. Some are company-led initiatives, whereas others are provided through educational institutions or nonprofit organizations. In 2016, a national survey was launched to gain insight into perceptions of what mentorship is, learn about available programs, and collate experiences with formal and informal mentorship opportunities. This paper outlines survey findings and delivers recommendations to industry for consideration in employee mentorship programs. In addition, mining industry leaders share their mentor/mentee perspectives. The intent of this paper is to bring awareness of best practices that can help employees grow and develop in their profession.RÉSUMÉ Les employés de l’industrie minière canadienne ont accès à de nombreux programmes d’encadrement. Certains sont des initiatives menées par les sociétés, d’autres sont proposées par le biais d’établissements d’enseignement ou d’organismes à but non lucratif. En 2016, une enquête à l’échelle nationale a été lancée en vue d’obtenir des informations quant à la perception de ce qu’est réellement l’encadrement, de découvrir les programmes proposés et de comparer les expériences aux possibilités d’encadrement, officielles ou non. Cet article présente les résultats de cette enquête et fournit des recommandations à l’intention de l’industrie afin qu’elle les prenne en compte dans ses programmes d’encadrement des employés. En outre, des chefs de file de l’industrie minière partagent leurs points de vue conseillers/protégés. L’intention de cet article est de sensibiliser les employés aux meilleures pratiques, ce qui les aidera à évoluer et à se développer dans leur profession. INTRODUCTIONThis paper about mentorship in the mining industry is based on voluntary responses to a cold survey, written and circulated by the authors. In 2016, a link to an online mentorship survey was circulated to males and females in the mining industry with the belief that mentorship programs should be available to everyone. The link was delivered via the authors’ personal networks in mining, the CIM Reporter, Women in Mining (WIM) email blasts, LinkedIn, and Facebook. This paper summarizes the answers to the survey questions. The paper is a follow up to one by the same authors (Nyabeze, Espley, & Beneteau, 2010), which was written to gain insight into why women join and stay in the mining industry, and to learn why the overall representation of women is low."

Jan 1, 2018

By Quenton Johnson, W. A. Gough, David Carr

"This paper describes the application of the BrainWave Model Predictive Controller (MPC) and Advanced Control Expert (ACE) Advanced Supervisory Control System on the SAG Mill, Ball Mill, and Rougher Flotation cells for a new gold processing line at the Oceana Gold - Haile Gold mine in Kershaw, South Carolina. For this project, ANDRITZ supplied the control system design and programming, operator-training simulator and advanced control. The advanced control was tested against the IDEAS™ dynamic simulator, and commissioned during the startup of the processing plant to help achieve target production as quickly as possible. Operators were able to run the equipment in a consistent and optimized manner from an early stage of the plant operation, increasing efficiency and profitability. MPC is able to reduce process variability beyond the best performance that can be obtained with conventional Proportional Integral Derivative (PID) control methods. MPC is able to optimize the control of processes that exhibit an integrating type response in combination with transport delays or variable interaction, which are characteristic of many gold processes including SAG mill weight control and Flotation cell froth level control. The experience and benefits of applying MPC during the startup of a new gold processing plant are presented in this paper.INTRODUCTION Mineral processing operations present many challenges for automatic process control due to variations in unmeasured ore properties, material transport delays, and non-linear response characteristics. Advanced process control technologies such as expert systems and multi-variable model predictive controllers are often used to improve the control of these processes to increase productivity and recovery efficiency. Typically these systems are applied after the mine has been in operation for a period of time. For this project, a complete dynamic process simulator was developed using the IDEAS platform for the purpose of training operators before the plant was constructed. Operators were able to become familiar with the process and the control system in order to become proficient in the use of the controls before the plant was ready to start. They were able to practice abnormal condition management including startup and shutdown of the process using the simulator and develop complete Standard Operating Procedures (SOPs) for these situations. The simulator was also used to test the control system functionality and operator Human Machine Interface (HMI) configuration to reduce errors and improve the performance of the control system during plant start-up."

Jan 1, 2017

By Technische Universität Braunschweig, K. Saksl, J. Furste, P. Eschenbacher, F. Brunke, D. Wolter, M. Kohnke, C. Siemers, J. Kiese, M. Schlemminger

"In general, titanium alloys combine outstanding mechanical properties with corrosion resistance and biocompatibility and are, therefore, used in many challenging applications. Nevertheless, for special products, well-tailored properties are required which might not be achievable by a specific design so that new or modified alloys are needed. In this overview paper, alloy development strategies performed at the Institute for Materials of the Technische Universitat Braunschweig are discussed at different examples, namely, (1) oxidation-resistant, microstructural-stabilized and cold-workable alloys for exhaust applications, (2) aluminum- and vanadium-free, medium-strength and cold-workable alloys for implants and osteosynthesis applications and (3) free-machining alloys by the addition of particles with low melting points for non-safety critical light-weight constructions to replace heavier steels, e.g. in automotive applications. A special focus is set on the alloy development techniques and the analyses carried out to achieve well-balanced properties by the optimization of the alloy compositions. INTRODUCTIONTitanium belongs to the allotropic metals and can therefore exist in two different equilibrium lattice modifications. Pure titanium crystallizes at 1668°C in a body centered cubic (bcc) structure called ?- titanium which at 882°C transforms to a hexagonal close packed structure (hcp), the a-titanium. A martensitic ?-to-a-transformation is possible at large cooling rates. This thermally induced hexagonal martensite is called the a'-phase. The transformation temperature named ?-transus-temperature (T ?) can be influenced by alloying elements (Peters & Leyens, 2002).For titanium alloy production typical alloying elements are aluminum (Al) and oxygen (O), both a-stabilizers shifting the ?-transus temperature to higher temperatures, whereas tin (Sn) and zirconium (Zr) only show a limited influence on the ?-transus temperature. The ?-stabilizing elements are subdivided into two groups: Niobium (Nb), molybdenum (Mo) and vanadium (V) stabilize the ?-phase between the melting point and room temperature and are therefore called isomorphous -stabilizers. Elements like copper (Cu), iron (Fe) or silicon (Si) also stabilize the ?-phase to lower temperatures but undergo a eutectoid reaction during cooling. ?-titanium then dissociates to a-titanium and an intermetallic compound. Consequently, these elements are called eutectoid ?-stabilizers (Boyer, Welsh & Collings, 1994)."

Jan 1, 2016

By Saravarim A.

"The aim in flotation systems is to control the grade and recovery of the product., numerical method or sampling and analysis is used to achieve this goal. Weakness of measuring instruments, lack of process knowledge, deficiencies in management and data processing in the control of flotation cells, has led the academic and industrial units to use numerical models. In this regard, using the results obtained from the experimental design carried out in the DTP line of Gol Gohar industrial and mining complex, a regression model was developed based on the analysis of variance. To present this model, after variance analysis of factors and interactions, all models were investigated and the final model was created based on 75% of the data. The model was tested with the remaining 25% of the data to confirm the goodness of the fit. The coefficient of determination for training and testing resulted 71% and 74%. Moreover, a feed forward back propagation neural network with different layers and neuron was used to model the results. The best network structure was 6-27-1 and the coefficient of determination for this network was 99% and 98% for training and test respectively. Given the complexity of neural network models and the relatively low accuracy of the regression model, neural network has a priority assuming we have access to a specialist. In addition, the results obtained from neural network can be used as expert systems to control and optimize the flotation cells.INTRODUCTIONThe primary objective of the flotation cell control is to maintain the product's (in this case tailing) recovery and grade, which represents the index for process efficiency and product quality. Continuous estimation of these indexes requires a significant amount of maintenance, and calibration of the continuous analyzers, in order to maintain an acceptable level of accuracy. Weakness of measurement equipment, lack of process knowledge and the general deficiency in management and processing of data in the flotation cell control, will lead industrial units to use smart methods such as mathematical models, regression and neural networks in near future (Panahi, Abdollahzadeh, & Sam, 2010). Artificial neural networks are inspired by the very complex structure of human brain in which millions of nerve cells solve problems or store information by communicating with each other. The duty of neural networks learning. It should be noted that learning in artificial neural networks is limited, and what is practically considered is the computing power of the network. A neural network consists of units called neurons, and has the capacity to handle a set of input data to produce a desired output data set. Each of these input and output data sets can be assumed as a vector (Soltanmohammadi & Noparast, 2006)."

Jan 1, 2016

By T. G. Carter

"Tremendous progress has been made in recent years towards developing computational tools that allow ready solution of most common rock engineering problems, with amongst the most advanced of the tools focusing on evaluating engineered openings within Synthetic Rock Masses. These new codes have the potential to allow much more realistic design, but they must not be used without careful calibration – prior to – during and – post completion of any modelling. This paper explores some of the pitfalls of inadequate data collection and suggests more emphasis be given to calibration. Guidelines for minimum levels of parameter data are suggested for improving application of basic to sophisticated modelling codes.INTRODUCTION & BACKGROUNDTremendous progress has been made in recent years towards developing computational tools that allow ready solution of most common rock engineering problems. The degree of sophistication now possible with some of the available codes allows one to tackle extremely complex problems that were not thought tractable even a decade ago. Indeed, generation of synthetic numerical rock masses, based on discrete fracture network representations that closely mimic actual rock mass conditions, such as are shown in Figure 1, is today relatively straightforward, and not as user-challenging as employing state-of-the-art codes of even a few decades ago. This is largely because major improvements in computer graphics and in availability of ready-made user-friendly input-output interfaces have paralleled development of these new codes, now in some cases outpacing actual new analytical/procedure developments. This is something of a reversal from the first few decades of DOS-based rock engineering computational experience, when only rudimentary graphics were available and user-friendly input-output interfaces were virtually non-existent."

Jan 1, 2015

By S. Devereaux, P. Gover, S. Everett

Having real-time data of blast furnace burden profile with respect to burden height and temperature is critical to making informed decisions on blast furnace operation. Given the high temperature and gaseous environment within the blast furnace shaft, traditional instrumentation has been limited at providing the level of real-time feedback information needed to optimize blast furnace operations. Infrared thermal imagery technology provides non-contact temperature measurement across the entire burden profile, allowing for better understanding of the dynamic movement of the burden within the blast furnace shaft. This technology increases blast furnace performance by improving the decision-making process for hour by hour operations. This paper will discuss the development of incorporating infrared thermal imagery technology into the operating strategy of a lead blast furnace.

Jan 1, 2015

By Renliang Shan

Site conditions of China?s coal roadways are complex and changeable, and scientific classification of them is the fundamental basis for coal roadway support design, with great significance for ensuring proper roadway service. Upon analysis of the issues, a commentary regarding the research progress on classification of the stability of rocks surrounding coal roadways in China has been achieved from the point of view of classification methods and indexes. The shortcomings and applicable scope of rock stability classification methods related to coal roadways have been analyzed. It has been asserted that combining artificial neural networks with fuzzy mathematics, combining fuzzy mathematics with grey theory, applying new avenues such as support vector machine algorithms or unascertained average classification, and making classification indexes more scientific are future directions for development of rock stability classification for coal roadways.

Aug 1, 2013

By E. Brzychczy

Artificial intelligence techniques are ever more frequently implemented in the modern world. One of their numerous uses is supporting enterprise management. Intelligent techniques and intelligent information technology (IT) systems can be implemented in mining-related issues as well. The author of this article concentrates on supporting the process of planning mining operations by intelligent systems and techniques. The author also underlines the importance of knowledge accumulation in a mining enterprise (especially tacit knowledge) as well as its efficient storing and using. Additionally, the author provides a short description of characteristics of intelligent IT systems and indicates their capabilities in planning mining operations. She presents two solutions, namely: an advisory system which supports the process of planning preliminary works and exploitation works in hard coal mines, and a method of modeling and optimizing mining operations. Finally, the author indicates a few possible future development trends of intelligent systems - the intelligent systems of decision support.

Aug 1, 2013

By Chen Feng

Compared to widespread successful deployment of robotic manipulators for repetitive and hazardous tasks in related industries such as manufacturing, the construction industry has achieved relatively limited benefits from robotics and soft automation. Unlike manufacturing, where robotic solutions benefit from the structured layout of the environment (e.g., factory assembly line), construction robots face unique challenges that arise from the rugged, dynamic, and unstructured environment of the work site, as well as the uncertainty and evolving sequence of occurring on-site events. This challenges any intended construction robots to not only replicate basic human motion, but also be capable of sensing and adapting to environmental changes, and making decisions based on the evolving state of the environment. Building upon recent advancements in robotic mapping, computer vision, and object recognition, the authors propose to introduce autonomous behavior at the basic task level for on-site construction robots to address these challenges in a flexible and extensible manner. This paper reports the outcome of the first phase of this research - a structured methodology for improved design and development of basic task automations - and focuses on algorithms developed for mobile robot navigation and relative pose estimation. The algorithms are implemented on a prototype mobile robotic platform, and evaluated in several experimental scenarios.

Aug 1, 2013

By S. Mao

Total station has been predominantly applied in stationary survey scenarios in construction. With the moving target tracking and point survey automation functions, a robotic total station (RTS) lends itself well to more dynamic applications. Nevertheless, a RTS unit is still unable to track multiple targets simultaneously or to survey a target point when the line-of-sight is temporarily unavailable. In this paper, we propose a methodology to synchronize and automate multiple RTS units intended to address dynamic tracking and surveying applications in the construction field. By using the application programming interface (API) from the manufacturer, we implement the proposed methodology and the prototype system integrates two RTS units in regard to space and time and communicates survey command instructions among RTS units through wireless networks. The two RTS units can be operated to survey the two ends of one swinging sling concurrently in order to retrieve the actual length of the sling within several millimeters accuracy. Besides, in applications where line-of-sight between a target object and one RTS unit cannot be guaranteed all the time, continuous surveying can be materialized by automatically delegating the task to another synchronized RTS unit with clear view of the target object. A field test was conducted to demonstrate the application of the proposed automation approach in which sling length was measured of a rigging framework used for lifting industrial modules. The testing results are presented and achievable accuracy and reliability are discussed. The proposed solution overcomes the limitations of global positioning system (GPS) and laser scanning and holds high potential to provide cost effective solutions to many dynamic field applications.

Aug 1, 2013

By J. Y. Kim

This paper presents a novel action recognition method for observing human workers using interactions between actions and related objects on an internal construction site. This method can be used to measure work rates for labour productivity monitoring. This monitoring is critical because the performance of a construction project is significantly impacted by labour productivity. However, construction sites are generally crowded with a large number of workers and objects. Such congestion disrupts the accurate, automatic recognition of construction workers? actions. This congestion is one reason that existing automatic action recognition studies of construction areas mainly focus on workers? actions themselves. However, the crowded conditions mean that sites could offer a great deal of clues that could be used for automatic action recognition. According to psychological studies, interactions clearly take place between human actions and related objects, such as between hammering and a hammer. Humans use these interactions to recognize actions or objects more accurately. On the construction site, workers, materials, tools, and equipment are carefully planned out ahead of actual construction. The categories of workers and objects are pre-defined and, as noted, specific interactions define relations between worker actions and objects. In this paper, the interactions are limited to human workers and their hand-held objects. Action recognition results can be combined with hand-held object information to improve recognition accuracy. With the limited interactions, experiments in this paper show a significant improvement in action recognition. This paper describes the utilization of these interactions to improve construction action recognition accuracy based on human skeleton data and 2D color video from Microsoft KINECT sensor.

Aug 1, 2013

By Linlin Zhang

Rare earth elements (REEs) are a group of lanthanides elements which have been widely used in the electronic, petrochemistry, metallurgy, and defense industries. Their demand has increased sharply in the past decade with the boom in electronic device production. Some countries now consider them strategic metals for the future and it has been forecasted that REEs may become a dominant contributor to global economy. In the wake of REE exploration, mining and processing, concern has grown over occupational and community health issues and risks. A portion of available literature on this topic however is written in the Chinese language, and thus research information related to health and REE mining is not readily accessible to mineral development planners in countries such as Canada, where REE mining is now evolving. As REEs also represent an important commodity, primarily stemming from Chinese production, it is important to begin to understand the potential health costs related to this mining sector. There are two main objectives of this paper. The first is to present an overview of REE mining with a focus on geological characteristics, global production and uses with particular attention to the main producer: China. The second is to present the results of a literature review (using both Chinese and English sources) on REE mining and health and identifies key occupational and community health issues that require consideration. This paper concludes by identifying some critical issues this sector needs to address to ensure the sustainable development of this mining activity.

Aug 1, 2013

By Leslie Gertsch

Outline First progress report ? ?Introduction ?Non-terrestrial mining ?Near-term targets ?Stages of mining ?Study procedure Capabilities needed for non-terrestrial mining ?Mining methods ?Mining unit operations ?Typical surface mine operations sequence ?Results to date General effects of gravity ?On fragmentation ?On excavation ?On transport ?Conclusions / Recommendations

May 1, 2013

By S. Amid, D. Fisk

"Wireless technologies are permeating the mining and metals industry and enabling a myriad of benefits. With standards such as IEEE 802.11 for wireless devices and ISA100.11a for wireless field instruments protecting their investments, customers look to benefit from the cost and flexibility offered by wireless devices. Using wireless field instruments, plants are eliminating the costs associated with wired system by 50 to 70% and using these savings to install more field instruments, which, when used smartly, enables them to optimize their processes efficiency and equipment reliability. Wireless also empowers a mobile workforce by allowing them to have access to key process and maintenance data directly from the field. This paper describes how wireless can help operations and maintenance personnel to be more effective. Three case studies, illustrating how the mining and metals industry is taking advantage of the technology today, are presented:1.,Optimisation of the water recovery process using wireless2.,Field operations improvement with wireless handhelds3.,Improving fleet maintenance through wireless mobile equipment management"

Jan 1, 2011

By J. Paquin, P. Doiron, G. Proulx, P. Champoux

After nine years on a 36 hour schedule and two programs of creeping, the Alcoa Deschambault Potroom of faced the necessity of changing its organization for many reasons: the anodes butts were too small, the anode schedule was unbalanced, the iron content in the metal trends had increased, the metal tapping volume did not convene with crucible capacity and the liquid measurement task was delayed by tapping activities. A kaizen activity inspired the Potroom department to improve the organization. A team of 15 people including the process engineer, the process technician, team supervisors and Potroom operators developed a scenario, which would permit flexibility to creep pots if energy is available and an increase of added value production.This paper will describe the systematic approach, the communication method, the trials, the changes, and our success, along with the problems experienced by the team during the adaptation of Alcoa Deschambault Potroom organization over a 20 month period. Aluminium 2006 45th Annual Conference of Metallurgists ofCIM Montreal, Quebec, Canada Edited by

Jan 1, 2006

By P. Mundell, R. Torbin

"There are many physical and operational obstacles in pipelines that make the passage of inspection robots impossible including:•,Small radius bends•,Low operating pressure•,Plug valves•,Large changes in pipe size•,No permanent access to the pipeline.The inspection of unpiggable pipelines requires the marriage of a highly agile robotic platform with NDE sensor technology operating as an integrated system. Foster-Miller and GE/PII are developing a robot that is essentially a battery powered, train-like platform. Both front and rear tractors propel the train in either the downstream or upstream direction. Like a train, the platform includes additional ""cars"" to carry the required payloads. The cars are used for various purposes including the NDE sensor module(s), the power supply, and data acquisition/storage components. The robot is designed with a slender aspect ratio and the ability to change shape as required by the physical obstacle presenting itself. The MFL sensor module must also morph itself through the physical obstacles, and thus, will require some level of segmentation. The segmented MFL magnetizers and transformable sensor module represent a major advance in the science of sensor technology and pipeline inspection."

Jan 1, 2005

A case study for the application of a novel geostatistical technique for resource estimation of a narrow steeply dipping, gold-silver mineralized quartz vein deposit is presented. The technique is novel in two respects. First, mineral grades are kriged directly rather via the accumulation method more often applied to vein deposits and, second, a modified 2D ordinary kriging algorithm is used that allows the calculation of a single grade and variance for irregular shaped blocks of varying sizes. The objective of this investigation was to evaluate the suitability of this novel geostatistical technique for resource estimation of the Poura mine deposit and, if appropriate, to lay a firm foundation for future geostatistical work at the mine. The reserve estimation concentrated on the remnant ore blocks and pillars in both underground and surface workings. The data, which was collected in 2D coordinates with grade and vein thickness values, was first analyzed statistically and used to compute experimental semi-variograms. Appropriate semi- variogram models were fitted and various aspects of the estimation technique were evaluated using cross-validation error analysis, with acceptable results. A block kriging computer program called Krige2D was developed to implement the modified 2D kriging algorithm and calculations. Production data were not available to evaluate the computed block resources, but they were compared with a previous resource data determined using an arithmetic approach. The geostatistical technique estimated slightly higher grades but lower overall tonnages as compared to the earlier arithmetic estimates.

Feb 1, 2004