School of Mining Engineering (ETDs)
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Item A Data Science Framework for Mineral Resource Exploration and Estimation Using Remote Sensing and Machine Learning(University of the Witwatersrand, Johannesburg, 2023-08) Muhammad Ahsan, Mahboob; Celik, Turgay; Genc, BekirExploring mineral resources and transforming them into ore reserves is imperative for sustainable economic growth, particularly in low income developing economy countries. Limited exploration budgets, inaccessible areas, and long data processing times necessitate the use of advanced multidisciplinary technologies for minerals exploration and resource estimation. The conventional methods used for mineral resources exploration require expertise, understanding and knowledge of the spatial statistics, resource modelling, geology, mining engineering and clean validated data to build accurate estimations. In the past few years, data science has become increasingly important in the field of minerals exploration and estimation. This study is a step forward in this field of data science and its integration with minerals exploration and estimation. The research has been conducted to develop a state-of-the-art data science framework that can effectively use limited field data with remotely sensed satellite data for efficient mineral exploration and estimation, which was validated through case studies. Satellite remote sensing has emerged as a powerful modern technology for mineral resources exploration and estimation. This technology has been used to map and identify minerals, geological features, and lithology. Using digital image processing techniques (band ratios, spectral band combinations, spectral angle mapper and principal component analysis), the hydrothermal alteration of potential mineralization was mapped and analysed. Advanced machine learning and geostatistical models have been used to evaluate and predict the mineralization using field based geochemical samples, drillholes samples, and multispectral satellite remote sensing based hydrothermal alteration information. Several machine learning models were applied including the Convolutional Neural Networks (CNN), Random Forest (RF), Support Vector Machine (SVM), Support Vector Regression (SVR), Generalized Linear Model (GLM), and Decision Tree (DT). The geostatistical models used include the Inverse Distance Weighting (IDW) and Kriging with different semivariogram models. IDW was used to interpolate data points to make a prediction on mineralization, while Kriging used the spatial autocorrelation to make predictions. In order to assess the performance of machine learning and geostatistical models, a variety of predictive accuracy metrics such as confusion matrix, a receiver operating characteristic (ROC) curve, and a success-rate curve were used. In addition, Mean Absolute Error, Mean Square Error, and root mean square prediction error were also used. The results obtained based on the 10 m spatial resolution show that Zn is best predicted with RF with significant R2 values of 0.74 (p < 0.01) and 0.7 (p < 0.01) during training and testing. However, for Pb, the best prediction is made by SVR with significant R2 values of 0.72 (p < 0.01) and 0.64 (p < 0.01) for training and testing, respectively. Overall, the performance of SVR and RF outperforms the other machine learning models with the highest testing R2 values. The experimental results also showed that there is no single method that can be used independently to predict the spatial distribution of geochemical elements in streams. Instead, a combinatory approach of IDW and kriging is advised to generate more accurate predictions. For the case study of copper prediction, the results showed that the RF model exhibited the highest predictive accuracy, consistency and interpretability among the three ML models evaluated in this study. RF model also achieved the highest predictive efficiency in capturing known copper (Cu) deposits within a small prospective area. In comparison to the SVM and CNN models, the RF model outperformed them in terms of predictive accuracy and interpretability. The evaluation results have showed that the data science framework is able to deliver highly accurate results in minerals exploration and estimation. The results of the research were published through several peer reviewed journal and conference articles. The innovative aspect of the research is the use of machine learning models to both satellite remote sensing and field data, which allows for the identification of highly prospective mineral deposits. The framework developed in this study is cost-effective and time-saving and can be applied to inaccessible and/or new areas with limited ground-based knowledge to obtain reliable and up- to-date mineral information.Item Slope Failure Prediction at Husab Open Pit Mine in Namibia(University of the Witwatersrand, Johannesburg, 2023-12) Thikusho, Christine Runguro; Watson, Bryan P.The study is focused on Domain D at Husab Mine in Namibia. The purpose of the study was to improve prediction of pending slope failures for planar and wedge configurations. Planar and wedge failures are similar in that little strain is required to initiate failure. Slope monitoring systems such as ground based radars, interferometric synthetic aperture radar and prisms were reviewed from the available literature. The data from the mine’s satellite monitoring data and the ground-based radar instruments was analysed. Slope prediction methods were used to back-analyse the failures, to determine if failure prediction times were possible. A case study was incorporated from the neighbouring Rössing Uranium mine, to supplement the data. The data utilised for the study was downloaded from the slope monitoring instruments on the mine i.e., the interferometric synthetic aperture radar, ground-based radar and tension crack data. The following slope failure predictive tools were investigated; the strain deformation approach; the inverse velocity method; the slope gradient method; the acceleration and velocity approach; and Displacement/Time plots. The back-analysis work done proves that the following slope failure predictive methods were able to predict failure at least 3 days before failure: velocity, cumulative displacement and inverse velocity. It appears that the Husab mine failure mechanism is not as brittle as previously assumed and failures are not necessarily instantaneous. Therefore, failures should be identified early, and the necessary risk mitigation measures implemented proactively. The ability of back analysing large volumes of stored data is important in the study of failure prediction.Item Pit Optimisation of Vondeling Quarry by Understanding Geotechnical Parameters Determined at Zoutkloof Quarry(University of the Witwatersrand, Johannesburg, 2023-11) Mukwevho, Tshinanne Matty; Pillay, OhveshlanThe purpose of the study was to investigate the geotechnical parameters at Zoutkloof quarry and how they affect stability and the mine planning process. The geological features of Zoutkloof and Vondeling are similar, hence the lessons learned while mining Zoutkloof quarry can be used when mining Vondeling quarry. Zoutkloof quarry has already reached its limits and is no longer operational. It is important that mine planning considers the critical geotechnical parameters. The main reason for this consideration is to keep slope walls stable, employees and equipment safe, and to continue mining the ore in an economical manner. The methodology of the research incorporated highlighting the literature in the public domain on geotechnical considerations in open pit mining. Evaluating geotechnical parameters such as groundwater, rock mass strength, slope angle and monitoring; and additionally, showed scheduling of mining blocks from 2007 to 2008 formed part of methodology in the research. The results analysis indicated that the strategies implemented to control groundwater were successful to keep the production benches dry and walls stable. Good understanding of the discontinuities and the rock mass strength enabled the quarry to be divided into ground control districts. Kinematics analysis for possible failures was done and the results showed that there was no probability of failure on planar mode. However, there were minor possibility that failure can occur on wedge and toppling mode. Yearly mining scheduling was completed, focusing on tonnage and quality requirements. During this period, Zoutkloof had minimum waste mined and the quarry had narrowed significantly which required the operational team to work within mine design specifications to maintain safety and slope angles. Some resources had to be compromised as it was not practical to exploit them safely. The research concluded its findings as successful because Zoutkloof quarry was mined completely with approximately 10 slope failures that resulted with no injuries to employees or damage to equipment. The factors of safety (FOS) were evaluated to be well above one and slopes remained stable until mining ceased. The research also made recommendations that can be implemented while the Pretoria Portland Cement (PPC) continue to mine Vondeling quarry to aid same success as Zoutkloof while being cost effective.Item Selection of an Optimal Tunnel Development Method for an Underground Mine Travelling Way Using an Analytic Hierarchy Process(University of the Witwatersrand, Johannesburg, 2024-01) Meyer, Berto; Musingwini, Cuthbert; Tholana, Tinashe; Sihesenkosi, NhlekoThis research study was conducted at the Marikana Operations (Marikana) which are situated within the Western Limb of the Bushveld Complex (BC) located in the North West province of South Africa. The Marikana Operations mine platinum group metals (PGM) using conventional underground mining methods. The Marikana Operations are owned by Sibanye-Stillwater. The PGM conventional underground mining entails extracting a shallow-dipping narrow reef horizon which is accessed via a network of development workings. Within this layout, a travelling way is an inclined tunnel that connects lateral development workings with the workings on the reef horizon. At Marikana the conventional hand-held mining method is used to excavate travelling ways. However, there was a trial process completed that proved the viability of the inverse drop raising method of excavating travelling ways at Marikana. With more than one viable tunnelling method being available for travelling way development, the need arose to select an optimal travelling way development method for Marikana. The selection is a multi-criteria decision making (MCDM) process because it requires the simultaneous consideration of several factors when evaluating the different alternatives or options. Commonly applied tunnelling techniques were reviewed leading to the selection of both the hand-held drill and blasting method and the inverse drop raising method as applicable to the conventional underground mining environment and specifically to travelling way development. Thereafter, Multi Criteria Decision Analysis (MCDA) techniques were reviewed, and the Analytic Hierarchy Process (AHP) was selected as the MCDA technique to be used as the selection tool for the research, due to its several advantages such as the ability to detect inconsistencies in judgements and provision to remedy the inconsistencies. After the application of AHP, the inverse drop raising method scored 7.2% higher than the hand-held method with a 53.6% versus 46.4% score. The inverse drop raising method was therefore selected as the optimal method to develop travelling ways at Marikana. With the approach that both these methods are currently being executed at Marikana, the inverse drop raising method is nearly twice as expensive as the conventional hand-held method. If PGM prices become a constraint, the method might not be sustainable if executed the way that it is done at the Marikana Operations from a cost perspective. It is suggested that further research should be done to see how the method can be executed more cost-effectively.Item Support Design Approach for Crusher Chambers: A Case Study of Palabora Mining Company(University of the Witwatersrand, Johannesburg, 2023-01) Masole, Nyeleti Venus; Stacey, T.R.This report project aimed to design a support system for crusher chambers at Palabora. The research project focused mainly on the two crusher chambers (12m wide by 25m high and 61m long) planned for the Lift 2 project as part of the ore handling system. The main research questions that the researcher sought to answer were; what are the differences between Lift 1 & Lift 2 in rock mass characterisation, classification and the ground control district?; how suitable is the Lift 1 crusher chamber support system for Lift 2?; what could be support requirements for Lift 2 crusher chambers in terms of empirical, analytical and numerical design methods and what are the recommended support design approaches for Lift 2 crusher chambers? The methodology used to design support for the Lift 2 crusher chambers was based on determining the expected failure mode first and then selecting suitable design methods to cater for the extent of failure. This study combined empirical and analytical methods to determine the failure mode and required support system. The results were then validated using Finite Element Method numerical modelling software called RS2 (Phase 2) from RocScience. Research findings revealed that the ground control district, classification and characterisation of rock masses differ slightly between Lift 1 and Lift 2. Jointing in dolerite dykes (DOL) was slightly dense in Lift 2 compared to Lift 1 and was associated with increased mining depth. Furthermore, the Lift 1 crusher chamber support system was found to be suitable for Lift 2 but must incorporate dynamic support. Unwedge (RocScience) analysis simulated wedge type of failure in the crusher chamber walls. The empirical and analytical design approach proposed cable bolt lengths of between 6m and 9 m and 3-4 m for roof bolts with bolt spacing of 1.4 m and 1.0 m respectively. The simulation results using RS2 confirmed that the cable bolt length and spacing were appropriate. The recommended support system was expected to provide sufficient support to the crusher chamber in terms of controlling rock mass deformation and yielding. The general conclusion was that the design approach selected for crusher chambers must be able to adequately represent rock mass behaviour and the support required to maintain long-term stability.Item The Impact of Digital Technology in South African Coal Mining: A Financial Performance Analysis of Anglo Coal American, Bhp Billiton and Glencore(University of the Witwatersrand, Johannesburg, 2023-10-27) Maluleke, Reply; Neingo, Paskalia; Marshall, Tania R.Digital technology, typically, refers to electronic tools, resources, devices and systems that store, generate and process information rapidly. Digital technology and innovation are among the initiatives that can assist mining companies to realise productive, efficient, profitable and sustainable mines. As such, the mining industry is taking steps towards digital technology and innovations that have evolved in recent years. The objective of this report was to discuss the financial impact of digital technology of the selected South African thermal coal mining companies namely Anglo American Coal Division now operating as Thungela Resources, Glencore, and South32, previously spun out of BHP Billiton and now operating as Seriti Resources. Coal mines were selected for analysis, due to their importance with respect to energy generation in South Africa. Industry cost curves over the period 2013-2019 were constructed as part of the financial analyses to show the trend of the selected companies’ unit costs. The research also used other financial analysis methods such as operating profit, profitability ratios, Economic Value Add and Du Pont analysis to analyse the performance of these companies. There appeared to be no production and unit cost improvement directly linked with investment in digital technology, as breakdowns, commodity prices, depletion of reserves, selling of operations, mine closures, high contracting prices, inflations and other factors also affected these parameters. Results for Anglo Coal and South32 did not indicate consistent good or improved financial results in all the financial analysis methods post the investment years in digital technology, in contrast to Glencore’s results which did. Glencore also invested more capital in digital technology as compared to Anglo Coal and South32. It is suggested that this may be one reason for its success. Consequently, it is recommended that companies looking to invest in digital technology follow the example of Glencore and invest as much capital as possible in this venture in order to maximise its potential.Item Verifying the Quality and Performance of Grout Using Sensor Technology(University of the Witwatersrand, Johannesburg, 2023-10) Hadebe, Menzi Bright; Mitra, RudrajitUnderground mines systematically install ground support to stabilize excavations and provide safe working environments. Support units, such as rock bolts and cables, are commonly filled with cementitious grout to effectively prevent corrosion, maintain bonding behaviour between the support unit and grout, and enhance the load transfer between the grout and surrounding rock mass. The grouting process is however time consuming and labour-intensive, which leads to haphazard installations. These substandard grout installations are only observed after rock fall instabilities occur when the quality and extent of grouting inside a support hole are exposed and can be observed. The need to monitor grout installations increased (provide assurance) but remained a challenge due to the invisibility of grout inside the support hole. The invisibility of the grout column inside the support hole renders the routine quality control inspections of installed support units ineffective. This ineffectiveness of quality control inspections has led to a growing need to monitor grout installations with smart technologies to provide quality assurance of full-column grouting. In its current state, grout technology in the mining industry can only measure the extent of grout inside a support hole directly after installation (limited battery life). It cannot measure the loss of grouting material into near borehole fractures, shrinkage, quality of grout inside the support hole or its impact on support performance. These factors are critical to the success of an effective support system and pose a significant safety risk when overlooked. This research report will describe how grout sensor technology data was recorded and used to verify the extent and quality of cementitious grout inside support hole installations at laboratory and deep-level mine study sites. Grout sensor technology, in practice, utilizes several grout sensors placed at predetermined positions along a support unit with a receiver attached to the collar of the support hole. Electrical resistivity data from each sensor is collected using a grout detector. Depending on the position of each grout sensor, the extent of grout inside a support hole can be confirmed, hence eliminating the need for speculative and ineffective visual observations. The non-destructive verification and prediction of the quality and performance of grout inside support holes using sensor technology forms an invaluable strata control tool that can be used to identify sub-standard grouting operations and significantly improve safety at underground mines. This novel and innovative technology is a mining industry first.Item Benefits of using Internet of Things technology for fuel management at a mechanised underground platinum bord and pillar mine: A Bathopele mine case study(University of the Witwatersrand, Johannesburg, 2024-01) Thema, Sephela Makete; Cawood, Frederick; Feroze, TariqThe advent of the fourth industrial revolution, Environmental Social and Governance (ESG), and push for green energy transition has propelled mining companies to reconsider their strategies. Over the past two decades, mining companies along the Bushveld Igneous complex in South Africa have been shifting towards mechanized mining methods which are generally safer and provide for the generation of greater volumes of output. Sibanye Stillwater’s Bathopele mine, which has a fleet of over two hundred and fifty (250) trackless mobile machinery (TMM) and a daily fuel consumption of approximately ten thousand (10 000) liters per day. The introduction of Internet of Things (IOT) technology in the fuel management system at Bathopele mine achieved benefits such as fuel consumption tracking, effective inventory management, prevention of fuel theft, detection of fuel leaks, determination of maintenance requirements and readily available access to fuel use data. This access to data enabled the mine to effectively apply for fuel use rebates from the South African Revenue Services (SARS) with ease. To determine the impact of the increased distance to underground working places on the refueling of TMM, the Theory of Constraints (TOC) method, qualitative and quantitative techniques were applied. A bivariate analysis conducted indicated a linear relationship between fuel consumption and production output at Bathopele mine, which suggests that an effective fuel management system had a positive impact on production output at the mine. A real-time or near real time model for fuel management in underground trackless bord and pillar mines in proposed.Item Application of derivative techniques to improve the forecasting of price volatility of copper, gold and platinum metals(2024) Veriyadi, VeriyadiThis research investigates the forecasted price volatility of copper, gold and platinum metals based on the selected companies; Palabora Copper Mining Ltd, AngloGold Ashanti Ltd, Gold Fields Ltd, Sibanye-Stillwater, Anglo Platinum Ltd and Impala Platinum Ltd. In responding to the latter sentence, single price volatilities are dual volatilities, where dual volatilities comprise of financial and technical variables. The selected firms either have global operations or they are subsidiaries of global companies. Dual volatility is computed using a Sample Correlation Coefficient and in order to explore the dual volatility, this research introduces three hypotheses. The first hypothesis uses a Decision Tree Analysis to test dual volatility based on financial and technical variables (e.g., mineral commodity price, metal grade, operating cost and production rate) in improving the forecasting of price volatility of copper, gold and platinum metals. For validation, the first hypothesis uses the Markov-Regime Switching Model. The results of this hypothesis illustrate that dual volatilities are more accurate and robust than price only volatilities. Then, the second hypothesis examines dual volatility using a GBM model. This hypothesis tests dual volatility; which is computed based on financial and technical variables (e.g., oil price, copper price, oil production and consumption, copper production and consumption; and the exchange rate from U.S.$ to ZAR and gold and platinum price data). The chosen variables that affect the dual volatility are examined using a Multiple Regression Model and that model confirms that those variables are independent in principle. Finally, the third hypothesis estimates future profits based on a binomial tree, which has risk-neutral probabilities based on dual volatility using mineral commodity price, metal grade, operating cost and production rate. The results of risk-neutral probabilities using dual volatility are less optimal than a mineral commodity price volatility due to not accounting for the mean of logarithmic returns. The robustness test uses the VAR model, which indicates that the profits react differently to different shock stages from revenues, risk-free interest rates and profits. In conclusion, dual volatility can improve future price forecasting performance because duality is underpinned by different variables, which include independent variables from the global commodity markets. The forecasting performance improvement from dual volatility in predicting the future price can be shown by the lower value of the Root Mean Square Error and Mean Absolute Percentage Error results than a mineral commodity price volatility. The findings of this research apply to copper, gold and platinum metals for mining around the globe.Item Analysis of the developmental potential of artisanal and small-scale mining: a strategy for South Africa(2024) Twala, Pontsho FrancinahThe mining industry remains central to the socio-economic development of mineral economies. While this is the case, most African countries have been struggling to translate the benefits of mining into positive developmental outcomes. This has been attributed to several factors including the failure to leverage opportunities from the Artisanal and Small-Scale Mining (ASM) sector which has been growing in most countries. As is the case in other African countries, the mining industry continues to play a considerable role in South Africa’s economy. The industry is expected to contribute significantly to the country’s socio-economic agenda which aims to eradicate poverty and inequality by 2030. Despite the positive outlook, the performance of the industry has been declining resulting in the government identifying a series of interventions aimed at reviving the industry’s activities. Amongst these is the formalisation of the ASM which has been earmarked for job creation and poverty alleviation. The objectives of the Thesis were to establish the developmental potential of ASM in the country, and subsequently develop a strategy framework aimed at enabling the sector to contribute to the mining industry and national development plan. The study was conducted using multiple case studies with data collected and analysed using multiple methods. The major finding from the study is that the ASM sector has the potential to contribute towards the country’s development priorities. This is taken from the evidence that shows a direct link between the sector’s activities and the country’s socio-economic landscape. It was established that the main drivers of ASM are socio-economic challenges in the country, mainly growing unemployment and poverty levels. To this end, ASM is playing a role in providing livelihoods to country’s population is that most affected by poverty and unemployment. As a livelihood strategy, ASM has improved the poverty status as well as the living standards of those that participate in its activities. The evidence from the study revealed that most of the miners measure above the country’s subsistence level and can provide for themselves and their families. The benefits of the sector also extend to communities and overall, these can be linked to several objectives as captured in the country’s development plan. The conclusion from the study is that the developmental potential of ASM can only be leveraged if the challenges in the sector are addressed, and these encompass issues relating to the regulation of the sector, mining land and mineral resources; value chain constraints, and related support, responsible practices, institutional arrangements, and ASM stakeholder relationships.