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By S. Sinha, S. Ganguly

"In an opencast mine explosives are used for fragmentation of rock. Inefficient use of explosive energy in an opencast operation produces excessive ground vibration, which is measured by peak particle velocity (PPV). To mitigate ground vibration, it is essential to develop a model to predict PPV. At present empirical models are used. These models are based on only a few input variables, hence they fail to take into account the effects of the myriad factors that cause ground vibration. Due to lack of explicit knowledge about the complex mine blasting system the scope of application of mathematical and statistical modeling techniques is limited. The artificial neural network (ANN) technique is a learning algorithm that can remove some of these limitations and can be applied to predict PPV. In this paper an ANN model is developed for prediction of blast vibration using 248 data records collected from three coal mines with diverse geomining conditions. The correlation coefficient between measured PPV and model output was found to be 0.96 and the average error percentage 11.85. The ANN model output was compared with the output of three empirical models that are widely used for prediction of PPV. The correlation coefficient between the PPV predicted by an empirical model and measured PPV data was 0.63 and the relative error percentage 38.47. This result demonstrates the superiority of the ANN model compared to empirical blast models. By using site-specific structural discontinuities as input the model performance can be further improved. Sensitivity analysis and 3D plotting were used to gain further knowledge about blast-induced ground vibration. IntroductionIn an opencast coal mine explosives are used for fragmentation of coal and overburden. If the explosive energy is not fully utilized it causes blast-induced ground vibration, which may damage nearby structures. Ground vibration is expressed as peak particle velocity (PPV). During different stages of mine planning and operation, it is necessary to use a ground vibration prediction model for blasthole design. Selection of the modelling technique is crucial. Mathematical and statistical modelling techniques have limited application because of the lack of explicit knowledge about the complex mine blasting system. Vogiatzi (2002) highlighted the problem of multicollinearity in case of statistical modeling techniques. Mutalib et al. (2013) stated that mathematical models are unable to capture the nonlinear relationship between several blasting-related parameters due to the complexity of the model input data. However, the difficulty involved in modelling complex blast vibration problems can be removed by adopting an alternative soft computing modelling approach. One of the soft computing techniques is the artificial neural network (ANN). Ragam and Nimaje (2018) developed an ANN model for predicting PPV using six input variables. Kosti et al. (2013) stated that the conventional predictors fail to provide acceptable prediction accuracy. They showed that a neural network model with four mine blast parameters as input could make significantly more accurate on-site predictions. Sayadi et al., (2013), using a database from Teheran Cement Company limestone mines, found that a neural network resulted in maximum accuracy and minimum error. Khandelwal and Singh (2009) developed an ANN model using 150 data records from an Indian coal mine with site-specific rock characteristics and geomining setting. Khandewal and Singh (2007) built a ground vibration prediction model for a magnesite mine using four prediction variables with 20 data records. Kamali and Ataei (2010) predicted PPV in the structure of the Karoun III power plant and dam using an ANN. El Hafiz et al. (2010) evaluated ground vibration predictors using data from a single-station seismograph at a limestone quarry in Egypt."

Feb 1, 2019

By A. Lane

The socio economic risks of mining in South Africa have been emerging for some time now, and have been brought into sharp relief by recent events in the platinum sector. The slow pace of social upliftment in the country has lead to widespread social unrest with consequent calls for different forms of resource nationalism. Fundamentally, the key stakeholders are not fully aligned, and are not engaging productively. This poses significant above-the-ground risk to mining companies. Measuring social impact, deploying inclusive solutions and engaging effectively with stakeholders are three ways in which mining companies can mitigate this risk.

Jan 1, 2012

By M. S. Shishvan, S. Klerkx, J. Sattarvand

The inaccurately drilled blastholes from the planned locations cause changes in the spatial distribution of explosive energy; some areas of the blast may receive a surplus of explosive energy, while others see a reduction. This results in less uniform fragmentation, reduces the efficiency of mining operations and increases costs. Additionally, it can lead to slope stability issues, flyrock, and uneven benches. To mitigate these problems, this study attempts to reduce differences in the explosive energy distribution (EED) through an optimization approach that adjusts the height of explosive columns in blastholes. Two optimization algorithms, the Genetic Algorithm (GA) and Tabu Search (TS), are tested. The latter is preferred for its local search neighbourhood strategy that gives superior computation times. Applications on different blast patterns result in improvements of 0.53–1.54%, or 2.14–3.94% when only the affected blocks are considered.

Sep 1, 2021

By A. F. Silva, R. Dockendorff, J. M. Girao Sotomayor, V. F. Navarro Torres, C. Castro

This paper shows the importance of performing probabilistic analyses in open pits, especially for mine planning, which can lead to more efficient ore extraction and meeting the acceptability criteria for safety in mine slopes. Three-dimensional stability analyses were performed to evaluate the future geometry of a large open pit for iron ore extraction in Brazil. The strength parameters of the lithologies were calibrated using ruptures in the pit walls. After determining the factors of safety (FoSs) from the calibrated parameters, probabilistic analyses were performed using the total range of values of each parameter under different field conditions to verify the reliability of the initial analysis. In this sense, it was possible to plot the probability of failure (PoF) and the FoS on the graph of slope height versus slope interramp angle (IRA) for the future pit in each lithology. IRA recommendations are made for two scenarios: (1) the best scenario: dry without ubiquitous joints and (2) the worst scenario: the water table at 10 m depth with ubiquitous joints in the most unfavourable direction. The results show that probabilistic evaluation is an important tool for establishing alert mechanisms in slopes that can be termed stable.

Jul 2, 2022

Mill relining is a major contributor to overall plant downtime. Reducing the number of mill liner pieces removed from and replaced in the mill has a direct impact on the overall reline time and in turn, mill availability. To improve the mill availability of Ridgeway Operations' 32 foot SAG mill, a number of initiatives were implemented in terms of liner design. These included the conversion of the shell from 40 to 30 rows, reducing the number of pieces from 80 to 60 each shell reline and reducing the number of pieces from 48 to 32 per feed end reline. In addition, modifications were made to the discharge end of the mill to extend the life of the outer pulp lifter and discharge cone, thereby reducing the frequency of change out. The standard radial outer pulp lifter was converted to an angled design. The discharge cone was converted to the BullnoseTM design supplied by Bradken. This paper discusses the design changes made and the expected benefits to the Ridgeway Operations in terms of mill availability improvements.

Jan 1, 2007

By R. Xie, J. Liu, Y. Zhu, Y. Li

The surface chemistry features of spodumene and feldspar were investigated by XPS, zeta potential measurements and first principle calculation. The results indicated that the zeta potential of feldspar was more negative than that of spodumene. The most possible active sites on spodumene and feldspar were Al sites and O sites. However, the number, type and activity of these sites were different. The flotation behaviour of five new collectors (cationic collector decyloxy-propyl-amine (DPA), anionic collector α-bromododecanoic acid (α-BDDA), N-Dodecyliminodiacetic acid (DIDA), and mixed collector DPA-BDDA and DPA-DIDA) were investigated through micro flotation experiments and analysed based on the surface chemistry features of spodumene and feldspar. The results revealed that cationic collector DPA processed a high collecting capacity for both minerals. The highest recovery of spodumene and feldspar was 91.60% and 95.30% respectively. The anionic collector α-BDDA and DIDA showed poor flotation behaviour. The recovery of spodumene and feldspar when using α-BDDA as collector was less than 5% and when using DIDA as collector was less than 1%. For the mixed collector DPA-BDDA, the recovery of spodumene and feldspar was 82.27% and 32.61% respectively at pH 4.5. For mixed collector DPA-DIDA, the recovery of spodumene and feldspar was 35.69% and 9.08% respectively at pH 5.8. The results indicated that the cationic collector had high collecting capacity, but low selectivity. The collecting capacity of anionic collector for spodumene and feldspar was poor at the same concentration compared with cationic collectors. Mixed collector DPA-BDDA showed good flotation behaviour and selectivity on spodumene. The ―COO- in mixed collector might improve the selectivity. However, too much ―COO- would increase the electrostatic repulsion, which might cause low selectively and poor recovery. Keywords: Spodumene, feldspar, surface chemistry features, mixed collector, flotation

Jan 1, 2020

By P. M. Solozhenkin, O. I. Solozhenkin

Currently lead nitrate is used as the recommended activator in Au-Sb flotation. However, due to high levels of hazard, the application of lead nitrate constitutes a potential risk for human health and ecosystems. To mitigate the harmful impact of activators on the environment, further research on activation by alternative reagents has been launched to promote the efficiency of antimony ores. In the present study, adsorption of lead, copper and zinc cations has been investigated by nuclear quadrupole resonance (NQR), which has revealed copper and zinc cations penetration into the mineral lattice, although lead cations remain adsorbed on the mineral surface. However, the combination of zinc and copper cations leads to preferential volumetric adsorption of zinc in the mineral lattice and further surface adsorption of copper which positively affects the activation process. It has been established that activation of stibnite can be achieved effectively with the mixture of Cu2+:Zn2+=1:1 as much as with lead cations in antimony ore flotation. As a part of this work, the computational modelling has been used in prognosis of reagent activity evaluation (PRAE) for stibnite and aurostibite flotation by sulfhydryl collectors. The lower PRAE value the stronger the ability of a collector to form a stable complex with a mineral. PRAE has shown a strong negative trend to complex formation on the mineral surface of aurostibite and stibnite. Based on these studies, several collectors have been proposed for effective flotation. To verify the feasibility of proposed collectors tetramethyl (ethyl) thiuram disulfides (TMTD and TETD) have been used for flotation of stibnite, sphalerite, pyrite and arsenopyrite. Flotation performance has been improved significantly with TMTD that allows the avoidance of lead nitrate application and increases the recovery of antimony by 8,16%. Keywords: Stibnite, aurostibite, activation, lead, copper, flotation reagents

Jan 1, 2020

Keywords: Pyrometallurgy, zinc, electrowinning Zincor has been producing zinc since 1969 via the roast-leach-electrowinning process. It is the only primary zinc producer in South Africa, and currently supplies the entire country with zinc. The plant was built by Goldfields of South Africa, on the site of an old gold and uranium mine. Since then, the ownership of the plant has changed a couple of times, and the plant and process have also been improved. Production output has increased from around 80 000 tons per year to more than 110 000 tons per year. This was done mainly through increasing the capacity of the roasters and acid plant. Zincor produces four main grades of zinc: SHG, Zn1, Zn2, and Zn4, in three shapes: a 25 kg ingot and 1 and 2 ton jumbos. In 2005, a pre-alloy furnace was built that enabled the production of jumbos pre-alloyed with aluminium. This has allowed Zincor's customers to improve the efficiency of their continuous galvanizing lines and to lower their production costs.

Jan 1, 2006

By E. Machaka, A. Cornah

"Mineral resources are typically informed by multiple data sources of varying reliability throughout a mining project life cycle. Abundant data which are imprecise or biased or both (‘secondary data’) are often excluded from mineral resource estimations (the ‘base case’) under an intuitive, but usually untested, assumption that this data may reduce the estimation precision, bias the estimate, or both.This paper demonstrates that the assumption is often wasteful and realized only if the secondary data are naively integrated into the estimation. A number of specialized geostatistical tools are available to extract maximum value from secondary information which are imprecise or biased or both; this paper evaluates cokriging (CK), multicollocated cokriging (MCCK), and ordinary kriging with variance of measurement error (OKVME).Where abundant imprecise but unbiased secondary data are available, integration using OKVME is recommended. This re-appropriates kriging weights from less precise to more precise data locations, improving the estimation precision compared to the base case and to Ordinary Kriging (OK) of a pooled data-set. If abundant secondary data are biased and imprecise, integration through CK is recommended as the biased data are zero-sum weighted. CK consequently provides an unbiased estimate with some improvement in estimation precision compared to the base case."

Jan 1, 2015

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By W. E. Stumpf

"SynopsisSouth Africa recently announced a resurgence in its commercial nuclear power programme. The implications for the development of the necessary high-level manpower within South Africa’s tertiary educational system and its national research and development (R&D) capacity in materials science and engineering, as well as in other engineering disciplines, are placed into perspective. An organized national process of developing this manpower by moving away from the previously high-risk and costly ’large programmes’ to rather a selection of ‘small and better’ research projects and a redefinition of what constitutes ‘nuclear materials’ are proposed as parts of this strategy.IntroductionSince 2008, and more particularly in 2014/2015, South Africa has woken up to the fact that significant steps need to be taken to ensure sufficient electricity generating capacity for the future, even beyond the coal-fired stations at Medupi and Kusile currently under construction. It is, therefore, encouraging to see some active large-scale wind farms in the Eastern Cape near Jeffrey’s Bay, in the Couga area, and others in the Western Cape already in operation. In addition, many solar energy projects are also progressing from the small localized scale to larger programmes in the Northern Cape, which may contribute some capacity on a national basis. South Africa needs to tap into its renewable resources of wind and solar much more, but will these projects solve the country’s long-term industrial needs? Unfortunately not. One cannot run mines and trains on solar cells. Industry needs reliable baseload capacity, and with very limited easily accessible hydrocapacity this leaves really only coal, possibly natural gas, and nuclear power as options. South Africa’s current over-reliance of about 90% on coal–fired power, however, places it in an internationally vulnerable position, and diversification into a more equitable energy mix should be a national priority for the medium to long term. South Africa cannot significant climate change confronting the human race, as the IPCC cautioned in 2013, and will have to adjust its future energy reliance to a more balanced combination of sources."

Jan 1, 2015

By M. J. Kanda, T. R. Stacey

Thin spray-on liners (TSLs) have been used as sealants and rock support in tunnels for over 25 years. Laboratory tests have indicated satisfactory properties that can provide adequate strength, adhesion, toughness, and elasticity as part of rock support systems in mining excavations. These characteristics are, however, not always demonstrated in practice, when mine environmental conditions do not correspond with laboratory environmental conditions. The shortcomings of TSLs experienced in the mining industry have raised concerns, resulting in scepticism from some operators regarding their utilization. The research described in this paper aims to investigate TSL performance in environmental conditions similar to those experienced in mines. Brazilian indirect tensile (BIT) specimens were prepared from precast shotcrete and coated with TSLs. The specimens were then exposed to different environmental conditions for up to 112 days before BIT testing under various conditions: laboratory room temperature and humidity; saturated room temperature; and combined saturated and high temperature (50°C). Additional uncoated shotcrete and TSL BIT specimens were prepared for comparison purposes. The results of the BIT tests showed that environmental conditions have a significant influence on the tensile strength enhancement of shotcrete by TSLs. Water-based TSLs are most likely to be suitable for high humidity environments, although their performance decreases at higher temperatures. Numerical modelling of TSL-coated BIT samples confirms the potential limitations of designing TSL support based only on laboratory testing carried out under room conditions.

Jul 1, 2021

By D. M. C. Valbom

The introduction of new diamond sorting technologies as well as additional manufacturers I vendors, has increased the equipment selection and combinations available for recovery flowsheet design. This paper describes the methodology used and the benefits realized in the design of recovery plants by ensuring a fundamental understanding of the advantages and limitations of the technology embodied in the equipment, a comprehensive knowledge of the ore body characteristics, and the effective matching of this information in combination with operational commercial requirements.

Jan 1, 2010

By P. K. Jain

A spiral concentrator is a density separation device used for the beneficiation of coal and various minerals such as iron ore, chromite ore, gold, beach sand minerals etc. The flow pattern developed in the equipment is complex and unique, yet the operation is very simple, with low capital and operating expenditure. Spirals are applied for beneficiation of material in the size range finer than 2 mm and are capable of recovering heavy minerals as fine as .01 mm. The understanding of the unique flow pattern has kept researchers engaged over the last few decades and attempts are being made to explain such flow patterns so that they can be controlled and modified to improve the operating efficiency, Ep (Ecart Probable Error, also known as probable error in separation) and acceptability of spiral concentrators for processing of fines and slimes - currently being discarded and dumped in the tailing ponds. An attempt has been made in this paper to explain the generation of complex flow patterns with application to classical solid mechanics in the fluid and slurry system. The same has been used to explain the selective separation of particles in different zones in a cross-section on the spiral trough. The paper also discusses the application of a force balance model to explain the generation of secondary circulation. Due to the presence of laminar and turbulent flow regimes in the spiral concentrator, varieties of equations have been proposed in the literature, consisting of different equations for different zones. An attempt has been made to present a unified flow equation for calculation of flow velocity at different positions on the spiral trough. Keywords: Secondary circulation, spiral concentrator, density separation, fine particle processing

Jan 1, 2020

By A. Pareek, V. S. Masampally, V. Runkana

Mineral processing plants, in general, consist of comminution and separation circuits. Rougher flotation is considered as the heart of the separation circuit with concentrate grade and mineral recovery being the key productivity and quality parameters that affect the downstream operations and profitability. Online prediction of these parameters can help improve process performance in real-time. Past efforts to predict flotation cell performance have focused on building physics-based or machinelearning (ML) based models. Although physics-based models are popular in process design applications, ML models are more appropriate for online monitoring, control and optimisation due to their lower computational requirements. Deep learning (DL) is gaining prominence nowadays for application in industrial operations where a large amount of data is available. We have developed a DL model based on long short-term memory (LSTM) neural networks to forecast the two key performance indicators (KPIs), namely, mineral recovery and concentrate grade in a mineral processing plant. Rougher feed characteristics such as mineral grade and particle size distribution, upstream measurable disturbances such as throughput of the comminution circuit and pulp density, and control variables such as aeration rate, pH, and collector addition rate are considered as explanatory variables to train the model. The model was tested with data from an industrial mineral processing plant. For real-time dynamic predictions, the trained model appropriately accounts for mismatch in measurement frequency of real-time process data and off-line laboratory analysis data. Such a time series model can be used as a state observer in model predictive control techniques for optimal control of unit operations in a mineral processing plant. Keywords: Mineral processing, flotation, time-series, dynamic modelling, deep learning

Jan 1, 2020

By N. P. Mabasa, N. Naudé, A. M. Garbers-Craig

An improved methodology is presented for assessing the economic feasibility and effectiveness of recycling MgO-C and Al2O3-MgO-C refractory bricks, which are widely used in the steelmaking industry. Since approximately 28 Mt of refractory bricks are discarded each year, it is logical to recycle them. When furnaces and ladles are relined, the spent refractory bricks become mixed up, and need to be sorted before recycling. This study examined the use of a hand-held X-ray fluorescence analyser (HH-XRF) to distinguish between spent oxide-based and oxide-carbon-based refractory materials, with special emphasis on spent MgO-C (MC) and Al2O3-MgO-C (AMC) bricks. HH-XRF analysis was conducted on 18 oxide-carbon refractory bricks as well as on MgO-chromite and bauxite-based refractories. X-ray diffraction, reflected light optical microscopy, and scanning electron microscopy with energy dispersive spectroscopy were used to characterize the MgO-C and Al2O3-MgO-C bricks to confirm the accuracy of the HH-XRF analyses. This study also underlined the importance of calibrating the HH-XRF analyser for the refractory bricks to be sorted. The HH-XRF was successful in distinguishing between the different oxide-carbon-based refractory bricks both before and after cleaning. This result is important as it proves that HH-XRF provides a method whereby spent MC and AMC bricks can be sorted quickly and reliably.

Jan 26, 2023

By G. Song, S. Yang

"SynopsisThe development of techniques and equipment for single-pass high-seam longwall mining in China is reviewed. Some methods used to obtain the fractured zone height are discussed. The boundary between the caved and fractured zones is generally not clear, but one important difference that distinguishes the two zones is that horizontal compressional forces exist only between blocks of fractured zone. Based on this, a theoretical method is presented to investigate the destabilizing modes of the main roof (by sliding or rotation) and is used to determine if the main roof is in the caved or fractured zone. This method considers the mining height, immediate roof thickness, bulking factor, main roof thickness, main roof strength, main roof periodic weighting interval, and vertical stress in the overlying strata. To verify the method, a representative physical model of Wangzhuang coal mine is developed. The movement of overlying strata and fractured zone height are thus obtained. According to the results, the total collapsed height of the strata reaches about 70 m above the coal floor; the first main roof bending interval is 45 m and periodic bending distance is 10–15 m; the maximum strata subsidence is around 62 mm; and the presence of a three-hinged arch causes the fluctuation of subsidence in the same stratum level. Based on the theoretical and experimental analysis, the middle of the main roof is considered the boundary between caved and fractured zone; the caved and fractured zone heights are about 21 and 49 m respectively.IntroductionThick coal seams (>3.5 m) account for about 44% of the coal rescource/reserves and more than 40% of the total annual production in China (Zhao 2004; Wang 2009). Three mining methods – slice mining, top coal caving, and single-pass high-seam longwall mining – are frequently used in underground thick-seam operations. Compared with slice mining and top coal caving, high-seam single-pass longwall mining significantly simplifies the mining processes, reduces roadway excavation, and improves coal production, productivity, and recovery. The favourable economics, high production, and technical simplicity make high-seam single-pass longwall mining one of the most popular underground mining methods for thick coal seams in China."

Jan 1, 2015

By H. Karabulut, S. Gündüz, K. Karacif, M. A. Erden

The corrosion properties of iron-based composite materials containing graphite and silicon carbide (SiC) reinforcement were investigated. The effects of silicon carbide reinforcement were investigated by adding 0.5% graphite and 1%, 2%, and 4% SiC. A powder metallurgy method was used to produce the composite samples. Iron, graphite, and silicon carbide powders were blended for one hour with a threeaxis mixer and then unidirectionally pressed under a pressure of 750 MPa. After pressing, the composite materials were sintered at 1100°C for one hour. The corrosion properties and microstructure, density, and hardness properties of the composite materials that can affect the corrosion properties were also investigated. It was determined that the pore ratio and hardness of the composite material increased, and corrosion resistance decreased, with increasing silicon carbide content.

Jun 2, 2022

By L. S. Bicalho, W. J. Rodrigues, P. M. A. Rollo, P. R. G. Brandão, W. C. da Silva

Quadrilátero Ferrífero is an important mineral province located in Minas Gerais state, responsible for a substantial amount of iron production in Brazil. Among the concentration methods for iron ore practised by the mining companies in this region, the most important is the reverse cationic flotation. Dolomite iron formations, with the presence of hematite, quartz and dolomite, occur in several areas of mining and, with the deepening of the deposits, this type of ore, with low iron content and more complex mineralogy occurs frequently. Carbonaceous minerals, mainly dolomite, present a technological challenge for the concentration of iron ore by flotation. In the present study, the concentration of iron ore with 6% of dolomite content was evaluated. Bench flotation trials indicated that conventional iron ore flotation is not selective to float dolomite, thus compromising the iron content in the final concentrate. Alternative flotation routes were evaluated, and a selective condition was reached to float both quartz and dolomite using the combination of the cationic collector Flotigam 16424 with an anionic collector Flotinor 16551. It was demonstrated that the flotation of dolomite was improved with the combined use of both collectors in the cleaner stage, and by a previous quartz flotation in the rougher stage. Zeta potential analysis indicated specific adsorption as the adsorption mechanism between Flotinor 16551 and dolomite, confirming the high selectivity observed in the bench flotation tests. Keywords: Flotation, iron ore, dolomite

Jan 1, 2020

By D. A. Phillips

A procedure for designing an optimum pit to yield maximum profit is described. The volume in which a possible pit is considered is divided into discrete blocks, each of which is assigned an economic value equivalent to its worth as a block of mineable material. The profitability of a pit can then be generated by summing the blocks within the pit. The optimizing procedure starts at the surface level and proceeds downwards level by level, to obtain the optimum pit at each level. The method makes use of the fact that an optimum pit at a particular level must be completely contained in any optimum pit at a lower level. Procedures for generating block costs, and pits with various slope angles under the restriction of complete block removal are considered briefly. The main description is of the theory of the method and the computer program based on this. The method is applicable to any type of mineral deposit, the only requirement being that the orebody should be represented accurately by a block model.

Jan 1, 2014