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By Getu F. Biftu

There is general agreement among scientists that global surface temperatures have been increasing during the past decades. The increase in temperature is postulated to be the result of either an increase in greenhouse gases emission or climate variability (i.e., due to variations in sun or volcanic activity or El Nino and La Nina events) during past decades and may continue to increase. The effects of a predicted rise in the Earth?s surface temperature include an increase in average global evaporation and increase or decrease in precipitation (Bloomfield, 1992; Mann et al., 1991; Vinnikov et al., 1990; Gan 1995; Zhang et al., 2000a). The general circulation models (GCMs) project a global warming due to greenhouse effects of 1.5-4.5°C by the mid 2050s, with the most pronounced changes taking place in northern latitudes (Nicholls et al., 1996). However, similar predictions at a watershed scale or even a regional scale using GCMs are mot possible yet (Arnell et. al., 1996; Georgievskii et. al., 1996; Zhang et al., 2000a). Detection of historic trends, changes and variability in climatic variables is another indirect means of understanding potential future changes or variability at regional and local scales. The main objective of this paper is to review studies related to climatic change or variability and associated hydrologic changes at a regional scale and local scale, particularly those studies applicable to the Oil Sands Region (OSR) of Alberta. This paper identifies gaps in our current understanding of the hydrologic processes that may be affected by climate change; it discusses potential implications to developments in the OSR; and it explores mitigation opportunities including several that have already been implemented.

May 1, 2004

By Emilio Giuseppe Sarno Severi

Mining and Petroleum Similar Industries ?Asset Intensive ?Exposed to market volatility ?Highly Risky Operations ?Scarcity of Experienced and Trained resources ?Operating in diverse countries with different cultures ?Increasing Environmental and Safety Regulations

Nov 1, 2011

By Y. Shu, A. R. Laplante

"A laboratory Knelson Concentrator (LKC), 7.5 cm in diameter, was used to study the performance of a similar unit at plant scale, 76 cm in diameter, This paper reports on sampling and assaying procedures and problems, and discusses the performance of the plant unit.The sampling procedure was based on the extraction of large samples, 5-15 kg, and their complete processing with a LKC, to characterize size-by-size performance. The procedure yielded reliable estimates of overall gold assays, after blatant assaying errors were corrected. The plant centrifugal unit concentrate was sampled in situ, which yielded very erratic grades, with a large overall negative bias. Due to the very heterogeneous nature of the concentrate, which can be linked to flow patterns in the riffles of the unit, it is recommended that for future testwork, the concentrate be recovered separately, blended and then sampled.The plant centrifugal separator, when operated at a feed rate of 25 t/h, yielded total and free gold recoveries of 41 % and 62%, respectively. This is much lower than previously reported data, and suggest that at 25 t/h, the unit is overloaded. However, recovery did not decrease with time over a loading cycle of 2 hours, which suggests that present loading cycles, generally 1 hour, can be significantly increased. INTRODUCTIONThe study of gold gravity circuits is plagued with the statistical problem of determining the behaviour of particles occurring with a very low frequency. This problem becomes particularly acute with increasing particle size. For example, considering the average weight of a gold flake in the 840-1200 µm (20/28 mesh) to be about 5 mg (Banisi et al, 1991), a reasonably high grade feed of 10 git would require, for a relative error (standard deviation) of 10% on grade, 100 particles, that is 0.5 g of gold, or 50 kg of 840-1200 µm material (a Poisson distribution is assumed). Gy's formula, for the same data, yields a weight of 33 kg, with a shape factor of 0.1 and a size distribution factor of 0.5. Both results are comparable; to obtain the suggested weight of material, a stream containing 5% weight in the 840-1200 µm would require 1 tonne samples (of unsized material). The problem rapidly disappears with decreasing particle size. Still with Banisi et al's data, a gold flake in the 300-420 µm range averages 0.5 mg in weight; the same 10% error on grade corresponds to a weight of 5 kg. Gy's formula for the same size distribution and particle shape factors as above predicts a required mass of 1.4 kg. This would correspond to an unsized sample weight of 10 kg with 14% weight in the 300-420 µm, for example."

Jan 1, 1992

By Xing Jin, Dan Graffi, Glenn MacPherson, Dan Rioux

"The complexity of a modern flotation circuit makes it susceptible to disturbances such as changes in feed, ore mineralogy, equipment degradation, poor measurements and faulty instruments. Good measurements and a robust control system are critical to create and maintain a stable and optimum flotation process.This paper focuses on the development and implementation of process control applications in the flotation circuits at Xstrata Nickel’s Strathcona Mill ( referred to as the mill hereafter ) in Sudbury, Ontario. Following the path of ‘stabilize-improve-optimize’, basic controls to stabilize process variables such as flotation cell pulp level, air and reagent addition rates, cleaning-column feed and wash-water rates have been established. Factors such as best practice in pulp level and valve position measurement, feedforward control and the application of an appropriate control philosophy, have contributed to the significant reduction in process variability. For instance, standard deviation reduction of 79% for the Ni impurity in the column Cu concentrate grade was experienced and is shown. The variability reduction of the flotation circuits’ key process-variables paves the way to further improve and optimize flotation performance. A grams-per-metal unit reagent addition control scheme has been improved upon, particularly for different operating scenarios and better robustness. In addition, following significant stabilization of the primary controls and columns feedrates, Cu/Ni separation cleaning-column bias-control (cascaded to the wash-water rate) and hold-up control (cascaded to air flowrate) have been developed and tested. This strategy – from stabilization to optimization - is expected to achieve a more consistent control of final concentrate grades and improve recoveries.INTRODUCTIONFlotation is considered the most important and value-added process in the milling metallurgical plant and is still undergoing continuous evolution to treat greater tonnage and different ores (Wills, 2006). Starting over three decades ago, with the advent of on-line slurry content analysis devices, flotation automatic control has received persistent interest and a large number of applications have been reported (Thwaites, 1983, 1986 ; Mckee, 1991). Bergh and Yianatos (2011) reviewed different aspects of process control in flotation circuits and have evaluated the applicability of model predictive control to the process. Mckee (1991) analyzed the difficulty in developing lasting/robust process control applications for flotation circuits and stated that the path of stabilization-refinement-optimization would more likely lead to successful flotation circuit process control. Best practice on column process control was discussed by Bouchard, etc. where a multi-layered approach was proposed, provided that the measurement of column process variables ( i.e. bias, froth depth, hold-up, etc. ) are measured reliably (Bouchard & Thwaites, 2008). Wills (2006) stated that the best practice for flotation automatic control starts with fulfilling basic control objectives, such as stabilized flotation cell level, air flow, pH, reagent flow etc., before considering more advanced, or even optimal, control of metallurgical targets, which are more closely linked to economic performance."

Jan 1, 2013

By André Pomerleau, Michel Grégoire, René del Villar

"The operation of industrial flotation columns requires the control of at least two variables, the interface position and the bias rate, by manipulation of some appropriate operating variables. Problems arise due to the reliability of existing methods of measuring the bias (i.e bias = tailings water - feed water), a situation which has often forced the industry to disregard this control loop. Moreover, when using such a measuring approach, the identification of the process dynamics is impossible. A second problem arises from the possible interaction between both control loops that might call for the use of a more complex multivariable control strategy.Recent work done at Lava1 University has demonstrated the feasibility of an independent sensor for bias, which models the relation between the conductivity profile across the interface and the bias value using a neural network algorithm. A 250 cm height, 5.25 cm diameter Plexiglas laboratory column was equipped with a series of conductivity electrodes in its uppermost part (across the interface) to measure both interface position and bias rate. Using such equipment, the flotation column dynamics were identified. The results thus obtained permitted the design and implementation of a distributed PI control strategy, where bias was associated to wash water rate and froth depth to tails rate. Both PI controllers were tuned using a frequency-response tuning method. Results of both identification and process control are presented and discussed.INTRODUCTIONFlotation columns are used for the separation of valuable minerals from a carrier gangue. Typically, this device is a tall (9 to 14 m height) cylinder (1 to 3 m in diameter) although other cross sectional shapes are also used. Finely ground ore is fed as a pulp at about 2 m from the top of the column, and pressurized air is introduced through a sparger at the bottom. If the pulp has been properly conditioned with adequate chemical reagents (collectors and modifiers), the valuable mineral particles falling by gravity will attach themselves to the rising air bubbles, and the air-particle aggregates will rise to the top of the column where they overflow as a stream called the concentrate. The gangue particles,, that do not attach to the air bubbles, fall down the column being withdrawn at its bottom in a stream called the tails.A particular characteristic of flotation columns is the addition of a fine spray of water at the top. As the water flows down through the froth zone, it washes out the entrained gangue particles from the mineralized bubbles, thus improving the quality of the concentrate recovered at the top. As a result of its cleaning action, this water stream is called the wash water and the upper zone, the cleaning zone. In order to ensure a downward flow of wash water, a proper water balance must be kept in the froth zone, otherwise the water added at the top might shortcircuit to the concentrate without performing any cleaning action. This net downward flow of water inside the froth zone is called the bias and represents an important operating variable of a flotation column."

Jan 1, 1999

By Gavin A. Hunt

In order for mines to operate profitably throughout their life it is important to monitor and maximise ore recovery. A common problem facing many mines is the underestimation of clay type and its distribution in ore at the mine face, blast hole or in the ore stockpile. Too much clay entering the heap leach ore stream for example causes a dramatic reduction in heap leach efficacy and or increased leaching times. The end result is poor leaching performance and much reduced metal production. Poor clay identification and quantification is attributable to many factors, including costly and slow off-site mineral analysis techniques, such as XRD, XRF and petrology, the visual and subjective limitations of the core logging geologist and a lack of suitable low cost, high throughput mineral logging instruments. To get round these problems a new, non-contact, imaging spectrometer - the SpecCam - was developed by Spectra-Map Ltd, to allow high throughput identification and quantification of minerals from mineable material. Its novel imaging design can collect millions of data points (pixels) per day; each pixel contains spectral information that allows a wide variety of mineral types, including the smectite and illite clays, and phyllosilicates such as talc and kaolin, to be identified. Because all the ore can be imaged a much more reliable mineral log can be made. Hence, mapping changes in mineral composition - related to variations in phenocrysts, macrocrysts, veining or wall rock - is possible. Examples of SpecCam data from Goldfields Cerro Corona Porphyry stockpile and from Rio Tinto?s Argyle Diamond mine illustrate the mineral identification and quantification capabilities of the SpecCam. More importantly, for the first time very accurate % abundances for the different minerals can be obtained using an image-based modal count technique. The modular design of the camera, plus its extremely flexible high speed filter, mean that the SpecCam can be easily installed on different equipment, each one suited to different ore recovery problems. For example the SpecCam can be used on an automated portable logging frame to measure drill core, RC chips, hand samples or powder, or alternatively installed on a Geotek multi-sensor core logger for high-throughput, automated logging of drill or blast hole core using co-registered multi-sensor data. An exciting recent development has been the installation of the SpecCam on CommoDas ore sorting equipment, used around the world for 24 hour mill-feed monitoring and automatic ore sorting. Real-time ore sorting decisions can be made as material is monitored on a conveyor belt running at 3m s-1, from which the ore can be automatically sorted into high-grade, low-grade or waste streams for example. The three installation options for the SpecCam mean that most mineral analysis and automated core logging or ore monitoring needs can be met at the mine. For the first time rapid and automatic mineral identification and accurate quantification can be made. All of which allow the mine geologist or metallurgist to make important decisions about maximising the metal recovery process.

May 1, 2007

By D. Marcotte

The Rock Quality Designation (RQD) is a standard scalar measure of rock quality used in common rock mass classification systems (e.g. RMR, Q system). RQD is measured along diamond drill holes. RQD interpolation between holes is nontrivial. Despite the inherent limitations of drill hole data and the local complexities of structural geology, it is often the only information available for mining and major civil engineering projects. Therefore, maximizing the usefulness of this data is warranted. We derive a correction for directional effects that help reduce the bias and improve the accuracy of the estimations. The correction is derived with the aid of numerous simulations. It relies on simple information, the angle between the joint normals and the borehole axis (JO). A reference direction is identified as the borehole direction with smallest JO. A multiple linear regression model based on JO statistics in the various boreholes defines the correction model. The corrected RQD values are then interpolated. It is shown the method enables reducing the bias on RQD estimation by 50% and improves the accuracy of the estimates by 30%. The corrected RQD values show stronger spatial continuity than the raw values. The benefits of estimating the RQD indirectly by using joint frequency measures are also assessed.

May 1, 2003

By M. Abzalov

"Control of analytical data quality is usually referred to in the mining industry as Quality Assurance and Quality Control (QAQC), and involves the monitoring of sample quality and quantification of analytical accuracy and precision. QAQC procedures normally involve using sample duplicates and specially prepared standards whose grade is known. Numerous case studies indicate that reliable control of sample precision is achieved by using approximately 5% to 10% of field duplicates and 3% to 5% of pulp duplicates. These duplicate samples should be prepared and analyzed in the primary laboratory.Bias in the analytical results can be identified by inclusion of 3% to 5% of the standard in each sample batch. Several different standards are used, with values spanning the practical range of grades in the actual samples. A blank (a sample in which the concentration of metal of interest is below detection limit) should also be included. Standard samples alone cannot identify biases introduced during sample preparation, and therefore approximately 5% of the duplicate samples (coarse rejects and pulp) should be processed and assayed at another, external, reputable laboratory.This paper discusses techniques used for estimation of errors in precision and accuracy, and overviews diagnostic tools. It is shown that one of the most commonly used methods, the Thompson-Howarth technique, produces consistently lower results than other methods. These results reflect the nature of this method, which relies on the assumption of a normally distributed error, and thus produces biased results when errors have a skewed distribution. This study concurs with the suggestion of Stanley and Lawie (2007: Exploration and Mining Geology, v. 16, p. 265-274) to use the average coefficient of variation (CVAVR(%)) as the universal measure of relative precision error in mine geology applications: Le contrôle de la qualité des données analytiques est habituellement désigné sous l’appellation d’Assurance et Contrôle de la Qualité (ACQ), elle implique le suivi de la qualité des échan¬tillons et la quantification de la reproductibilité et la précision analytiques. Les procédures des pro¬grammes d’ACQ impliquent habituellement l’usage de duplicata et de standards analytiques dont la teneur est connue. Plusieurs études de cas indiquent qu’une bonne fiabilité du contrôle de la précision des échantillons est atteinte par l’usage de 5% à 10% de doublons sur le terrain et de 3% à 5% de doublons de pulpe. Ces duplicata devraient être préparés et analysés au laboratoire principal.Un biais des résultats analytiques peut être identifié par l’inclusion de 3% à 5% d’échantillons standard dans chaque envoi d’échantillons. Plusieurs standards sont utilisés, avec des valeurs couvrant l’étendue des teneurs habituellement rencontrées dans des échantillons réels. Un blanc (un échantillon dans lequel la concentration d’un métal donné est sous la limite de détection) devrait aussi être inclus. L’emploi exclusif d’échantillons standards ne permet pas l’identification de biais résultant de la préparation des échantillons, de telle sorte qu’environ 5% des duplicata (rejets grossiers et pulpes) devrait être traités a un autre laboratoire indépendant et fiable.Cet article passe en revue les techniques utilisées pour évaluer l’erreur liée à la précision et a la reproductibilité, et effectue aussi un survol de divers outils diagnostiques. Il ressort de cet examen qu’une des techniques les plus fréquemment utilisées, la méthode Thompson-Howarth, fournit des estimés systémati¬quement inférieurs à ceux provenant des autres méthodes. Ces résultats sont un reflet de la nature de cette méthode, laquelle assume une distribution normale de l’erreur, biaisant ainsi les résultats lorsque l’erreur présente une distribution asymétrique. La présente étude recommande de privilégier l’usage du coefficient moyen de variation (CVAVR(%)) en tant que mesure universelle de la précision relative de l’erreu"

Jan 1, 2008

Improved Process & Practices Result In: ? Reduction of undesirable downtime, & expensive secondary damage ? Improved equipment performance & health ? Extension of equipment life, & reduction of operating costs ? Safety and environmental performance improvement Equipment knowledge capture and consistently applied

May 1, 2010

By Michael Hood

An overview is given of some of the major mining research activities in Australia. Automation of mining equipment is not an objective in its own right. The objective is to improve the safety and the economic performance of mining operations. Automation can be a useful method for achieving this objective. There is a strong focus on mining equipment automation and related issues and specific examples of ongoing and recently completed automation projects are described.

May 1, 2002

By Jean-Marie Fecteau

The gold mine sector is presently facing low gold prices as well as technological challenges. Its competitiveness and survival will depend on new mining methods and equipment to improve ore extraction. In 1999, Natural Resources Canada has invested new funds over a period of three years at CANMET?s Experimental Mine to establish the Narrow-Vein Mining Project. A team of engineers and researchers specialised in mining, mechanics and electronics engineering are working to meet the critical need of ore-extraction technology. CANMET?s program in mechanisation and automation for narrow vein mining had, prior to 1999, realised several important achievements, many in co-operation with a consortium of mining companies (Soredem). The investment of new funds in this area will contribute to develop technologies to improve the productivity, as well as health and safety conditions of the narrow vein mining industry. Several important impacts of this project will be monitored. Specifically, a database of methods and equipment used in narrow vein mining is being developed. A key thrust is to identify operators? needs with respect to the development and automation of mining methods and equipment. Based on those needs, research and development projects will be created. The main problems identified following meetings with mine operators are described with a few elements of solution and the Web site created for the broadcast of the results is presented.

Oct 1, 2001

By Pierre Rocque

The Red Lake Mine is located approximately 600 km northwest of Thunder Bay. This 545 tpd (600 tons/day) underground narrow vein gold operation is set to produce in excess of 14.8 tonnes (475,000 ounces) in 2001 at a cash operating cost below 75 U$/oz. The high-grade nature of this deposit (>55 g/t or >1.6 opt) coupled with its complex geological environment and relatively deep location dictated the choice of a very selective primary mining method, Mechanized Overhand Cut and Fill. In addition to geological challenges, mine design issues such as material handling, ground stability and requirements for yieldable ground support are also discussed in this paper.

Oct 1, 2001

By Jason J. Ballentine

This paper presents a case study of how an asset strategy and zero based budget was developed for an existing crushing plant that had been purchased from the contract service provider by an Australian Iron Ore miner. The goal was to directly align the strategies and budget to the business goals. This however was not a simple task due to poor historical records and a general lack of information. These challenges were overcome and the benefits of a documented maintenance strategy, a justifiable zero based budget and employee engagement were realized.

May 1, 2007

By E. Pribonic

Failure of a mine material hoist can cause injuries, fatalities and significant infrastructure damage, along with an associated loss of production. Principal causes of hoist accidents are overwind and underwind. Past and present means of arresting hoisting equipment are marginally effective and utilize destructive systems that are not reusable following an arrest. The use of permanent magnet eddy current arrestor technology is proposed; the history and fundamental science of the technology are presented, followed by real world examples and calculations of performance for failsafe, friction-free, instantly reusable eddy current arrestors as applied to stopping a 30-ton ore skip traveling at 16 metres per second. A comparison of existing arrestor types with the eddy current arrestor is included and limitations of the ECA are also discussed.

Jan 1, 2008

By Malcolm Scoble

Process Technologies Suitable for Application Underground Design Criteria - coarse particle technologies - compact, robust, flexible - waste products suitable for use as backfill Process technologies identified: - Optical/conductivity sorting - Dense media separation - Coarse-particle flotation Process technologies supported by compact & efficient comminution stages Mineralogical evaluation to select process & estimate Performance Further Work U/G Plant Layout & Excavation Modelling Evaluate scenario at increasing depth Establish properties of waste as backfill Model impact of improved backfill quality Evaluate further case studies Evaluate further Environmental Health and Safety Issues Model impact of system development on inventory of national mineral reserves Conclusions Technologies exist for integrated underground mining and processing systems These technologies to be successfully integrated into underground mining system Positive economic and environmental benefits Technical issues to be resolved at depth System Development path identified

May 1, 2004