Electronic Theses and Dissertations (Masters)
Permanent URI for this collectionhttps://hdl.handle.net/10539/38012
Browse
8 results
Search Results
Item Characterisation of the Platinum Group Minerals in the Ombuku North intrusion peripheral to the Kunene Complex: Insights into its PGE potential(University of the Witwatersrand, Johannesburg, 2024-03) Mothobekhi, Lorraine Masoko; Milani, Lorenzo; Hayes, BenThe Kunene AMCG (Anorthosite-Mangerite-Charnockite-Granite) Complex, located in the southern part of Angola and northern part of Namibia, is known as one of the most extensive Proterozoic anorthosite complexes worldwide, with an extent of the area ≥ 18 000 km2, and positioned along the southwest margins of the Congo craton. The mafic-ultramafic intrusions within the vicinity of the Kunene Complex are mineralised with nickel, copper, and platinum group elements (PGEs). The area has not been extensively explored, and only minor exploration work has been conducted to search for magmatic sulphide deposits, particularly nickel deposits. The PGE potential of the mafic-ultramafic intrusions in the area and their potential mineral system has not previously been extensively studied. The available geochemical assay data of the Ombuku North intrusion in northern Namibia was sourced from African Nickel Limited (ANL) and was used in this study to assess its PGE potential and to better understand its potential mineral system. Petrographic work demonstrated Ombuku North intrusion was commonly associated with magmatic sulphides (pentlandite, pyrrhotite, chalcopyrite), formed from a Mono Sulphide Solution, and magnetite. Samples were selected for further detailed platinum group mineral (PGM) investigations on the basis of their PGE contents. Ombuku North is characterised by slightly anomalous PGE values and the available thin sections from Ombuku North with corresponding bulk rock PGE values of >80 parts per billion (ppb) were selected for the identification and characterisation of the PGMs, and for detailed petrographic analyses. In this study, PGM mineral analyses were done using a Tescan Integrated Mineral Analyser (TIMA) which is a fully automated instrument, whereas previous mineral analyses for PGMs in Ombuku North and some of the other mafic-ultramafic intrusions in this region were collected using Scanning Electron Microscopy Energy Dispersive Xray Spectroscopy (SEM-EDS) method, which is only partially automated. TIMA could identify the PGM in the selected samples from Ombuku North. The identified PGMs included sperrylite, michenerite, stibiopalladinite, and vincentite, all associated with serpentinised rocks. The platinum arsenides (sperrylite) are mainly hosted in magnetite and in pyrrhotite. The palladium bismuthotellurides (michenerite and vincentite) and a platinum antimonide (stibiopalladinite) are hosted in pentlandite. The origin of these PGMs can be associated with both magmatic and hydrothermal processes. Magmatic processes are primarily responsible for the initial formation and crystallisation of silicate minerals within the mafic-ultramafic intrusions, including primary magmatic sulphide assemblage. Late hydrothermal processes are related to the alteration of these rocks, where fluids circulated through the rock leading to the formation of secondary minerals such as serpentine, talc, and the redistribution of PGE. Although PGE data are also provided also for other intrusions, this study mainly focused on Ombuku North intrusion due to the limited availability of assay data. We infer that amongst all the mineralised mafic-ultramafic intrusions related to the Kunene Complex, the most prospective for PGE anomalies are the altered ultramafic lithologies at Ombuku North.Item Intergrated Geophysical Methods to Delineate R21 Sinkholes Near Olifantsfontein, Gauteng, South Africa(University of the Witwatersrand, Johannesburg, 2024-09) Mabele, Nondumiso; Manzi, MusaThe Gauteng province in South Africa is known for having a significant portion, at least 25%, of its land is underlain by dolomite rocks. An integrated approach of non-invasive geophysical methods was utilised to map the geometry (shape, size and extent) of the R21 highway sinkhole that formed near Olifantsfontein. These methods include seismic (reflection and refraction), multi-channel analyses of surface waves (MASW), electrical resistivity tomography (ERT), and ground penetrating radar (GPR). The objectives of the investigation were three-fold: (1) to understand the geology and formation of sinkholes in Gauteng; (2) to use geophysical techniques to map and characterize sinkholes in the study area, including determining their geometry, lateral and vertical extents; and (3) to determine the effectiveness of each method in mapping sinkholes. Despite the high level of noise along the highway, the geophysical surveys were conducted successfully and provided a good basis for the integrated interpretations. This study showcases the importance of utilising multiple geophysical methods to obtain a comprehensive understanding of sinkholes and their subsurface characteristics. It also demonstrates the practical application of these methods in real-world scenarios for improved hazard assessment and risk mitigation. The GPR results suggest that a sinkhole extends by ~2.5 m further into the R21 highway surface with a depth of ~8-10 m (top to bottom). The refraction seismic method suggests that the sinkhole is ~20 m wide, while the ERT results suggest that the sinkhole starts at 10 m and extends to 15 m depth. The results from reflection seismics indicate that the R21 sinkhole is structurally controlled and it is characterised by fracturing and faulting that manifest as diffractions on the seismic sections. Understanding the extent and characteristics of sinkholes is crucial for infrastructure planning and hazard mitigation, especially in areas prone to subsidence and sinkhole formation like in Gauteng. These findings can inform decision-making processes related to road maintenance, construction, and land use planning in sinkhole-prone regions. The success of the integrated geophysical approach in this study highlights its potential for similar investigations in other areas with karst geology and sinkhole risks.Item The nature and characteristics of sulphide mineralisation at the Kamoa - Kakula copper deposit of the Katanga basin, Central African Copperbelt, Lualaba, Democratic Republic of Congo(University of the Witwatersrand, Johannesburg, 2024-08) Kaemba, Robert Ntokwa; Yudovskaya, Marina A.The Kamoa-Kakula deposit is a world-class stratiform copper deposit located in the southern part of the Democratic Republic of Congo (DRC) approximately 25 km from Kolwezi town and close to the border of DRC and Zambia. The ore deposit is in the southern area of the western foreland domain of the Congolese Copperbelt (Central African Copperbelt). The structural setting of the deposit is characterised by the West scarp fault, binding Kamoa to the west whilst it is bounded by faults of the Kansoko Sud trend to the east. The mineral resource footprint of the deposit envelopes the Makulu dome and wraps around the southern edge of the Kamoa dome. The main sedimentary lithologies hosting copper mineralisation are diamictite and interbedded siltstones of the Grand Conglomérat Formation at the base of the Nguba Group overlying sandstones of the Mwashya Subgroup (Roan Group). Previous studies within DRC and Zambia showed that the glaciogenic diamictite (Grand Conglomérat Formation) is a laterally extensive regional marker. The geological interpretation and literature data reveals a distinct stratigraphic correlation of several copper deposits across the Central African Copperbelt confirming multiple occurrences at various stratigraphic levels. Furthermore, this analysis identifies the Fishtie deposit (Lusale basin, Zambia), which occurs on the eastern margin of the Katanga basin, as the closest geological analogue to Kamoa – Kakula. At Kamoa-Kakula, hydrothermal sulphide mineralisation occurs mainly towards the base of the Grand Conglomérat with the dominant sulphide mineral assemblage composed of pyrite – chalcopyrite – bornite - chalcocite, and minor covellite . Optical microscopy demonstrates the multi-stage crystallisation of few generations of pyrite including the earliest diagenetic framboidal pyrite. The widespread development of the symplectic texture linked to bornite and chalcocite intricate intergrowths and regular rimming of clasts by sulphide overgrowth, as well as the occurrences of framboidal chalcopyrite and bornite argue for the sulphide paragenesis being linked to sulphide replacement. This is consistent with the apparent mineral zonation progressing downwards from pyrite → chalcopyrite → bornite ± covellite → chalcocite. The S isotope variations suggest that a significant portion of S at Kamoa originated from early bacterial sulphate reduction, which resulted in precipitation of fine-grained framboidal and sooty pyrite with the negative δ34S values as low as -19.9 ‰. The similar, while narrower, range of δ 34S values for chalcopyrite is due to inheritance and homogenization of the S isotopic signature of diagenetic sulphides during ore stage replacement, whereas the highly negative δ 34S values for chalcocite (down to -35.1 ‰) indicate the subsequent extreme isotope fractionation under low-temperature conditions. The study includes a comprehensive overview of the regional stratigraphic and geological correlation, in conjunction with detailed mineralogical and isotopic observations, contributing to further understanding of Cu mineralisation at Kamoa-Kakula as well as on a scale of the entire Central African Copperbelt.Item Assessing the Magmatic Ni-Cu-(Co-PGE) Sulphide Potential of the Kunene AMCG Complex(University of the Witwatersrand, Johannesburg, 2024-08) Manuel, Agex Cordeiro Ferreira; Bybee, Grant; Hayes, BenNot AvailableItem South Africa’s earliest giant: The systematics and palaeobiology of a new species of sauropodomorph(University of the Witwatersrand, Johannesburg, 2023) Moopen, Atashni; Choiniere, Jonah N.; Botha, JenniferSauropodomorph dinosaurs are characterized by their gigantic body size and quadrupedal postures, but they evolved from small, bipedal ancestors. Transitional non sauropodan sauropodomorphs from the Norian are key to understanding this evolutionary transition. A new Norian sauropodomorph (BP/1/8469) discovered in 2018 in the lower Elliot Formation of Qhemegha, Eastern Cape consists of a well-preserved, well-represented associated postcranial skeleton of a relatively large individual. This specimen provides novel information about the Norian transition in sauropodomorph body plan. This study presents the results of BP/1/8469, using comparative anatomical study, quantitative body mass and postural estimation, osteohistological enquiry, and phylogenetic systematics assessment. BP/1/8469 is a 1.8 to 3.1 metric tonne, facultative quadrupedal sauropodomorph. It was an adult that displays rapid, interrupted growth, similar to other sauropodiforms. Phylogenetic analysis of BP/1/8469 highlights incongruencies in sauropodomorph character datasets, flags considerable homoplasy in sauropodomorph evolution, and underscores the need for accurate homology statements.Item Physical property studies, tunnel numerical simulations and in-mine seismic experiments to image the gold orebody at South Deep Gold Mine(University of the Witwatersrand, Johannesburg, 2024-09) Mulanduli, Omphulusa; Manzi, MusaThe investigation endeavors to assess the physical characteristics of deep borehole cores within the Upper Elsburg Reefs (UER) of the South Deep gold mine of the West Rand goldfield. Specifically, these cores are sourced from three boreholes situated approximately 2.6 km beneath the surface within the confines of the South Deep gold mine. The focal point of this study lies in non-destructive testing methods aimed at elucidating the intrinsic attributes of these rocks, with particular attention directed towards seismic velocities and densities. These measurements hold paramount importance in conducting numerical simulations to designing the in-mine (or tunnel) seismic reflection surveys acquired at South Deep gold mine, as part of the ERA-Min3 FUTURE (Fiber-optic sensing and UAV-platform techniques for innovative mineral exploration) project. Cultivating a profound comprehension of the seismic velocities and densities across diverse rock formations can significantly augment the interpretation of seismic reflections, thereby facilitating more refined assessments of subsurface geology and structural configurations. In pursuit of this goal, our study endeavors to delve into the fundamental acoustic properties of the gold-rich UER, with the overarching aim of deepening our understanding of its seismic reflectivity. To realize this objective, a comprehensive array of physical measurements, encompassing ultrasonic velocities and bulk densities, were conducted on drill-core specimens. To accurately portray the physical attributes of the lithological units under scrutiny, a total of twenty-four samples were subjected to exhaustive analysis for density and seismic velocity utilizing a spectrum of methodologies. Density determinations were procured through a diverse set of techniques, including dimensional assessments, employment of the KT20 MagSus tool, and utilization of the SNOWREX AHW-3 Professional Weighing Scale boasting a heightened sensitivity of 0.01 g. Ultrasonic measurements were undertaken employing the Proceq Pundit PL 2000 ultrasonic pulser velocity tester, equipped with two pairs of transducers boasting a center frequency of 54 kHz. The in-mine seismic survey was acquired to delineate geological structures that crosscut and displace the orebody. The study locale encompasses three distinct rock formations: the UER, gold-bearing conglomerate units (termed reefs), basaltic lava, and dyke specimens. The UER primarily comprises quartzites, exhibiting a P-wave velocity range of 5202-5802 m/s, an S-wave range of 3037-4768 m/s, and bulk densities spanning from 2.66 - 2.71 g/cm³. Conglomerate reefs exhibit a P-wave velocity range of 4467-5970 m/s, an S-wave range of 4040-4854 m/s, and bulk densities ranging from 2.67-2.94 g/cm³. Lava samples extracted from the boreholes showcase a P-wave velocity range of 5916 - 6711 m/s, an S-wave range of 3275-5659 m/s, and bulk densities spanning from 2.75-2.90 g/cm³. Singular dyke samples were encountered, exhibiting a P-wave velocity of 5921.5 m/s, an S-wave velocity of 5385 m/s, and a density of 2.85 g/cm³. The study employed the synth-seis code to simulate 1D seismic responses based on borehole data collected from the mine, aiming to validate findings from velocity and density measurements. Analysis of the seismograms indicated notable contrasts between conglomerates and quartzites, particularly evident in density and S-wave measurements, suggesting potential for improved rock discrimination with alternative seismic sources. Additionally, 2D numerical simulations were conducted to model wave propagation in the Upper Elsburg Reef (UER), revealing discrepancies between simulated and synthetic seismogram results, indicating potential limitations in seismic imaging. Furthermore, ray tracing was used to design a seismic survey inside the mine along the tunnel floor to image VCR (Ventersdorp Contact Reef) orebody and other geological structures. The real seismic survey was finally conducted inside the tunnel (SDT1), demonstrated the value of in-mine reflection seismic surveys for mapping geological structures at significant depths, which would otherwise be costly and logistically challenging. Despite noise interference from mine operations, processing algorithms enabled extraction of reflections and structural mapping from the dataset, underscoring the importance of such surveys in mining exploration and planning.Item Machine Learning Algorithms-Based Classification of Lithology using Geophysical Logs: ICDP DSeis Project Boreholes, South Africa(University of the Witwatersrand, Johannesburg, 2024-09) Atita, Obehi Chapet; Durrheim, Raymond; Saffou, EricOne of the most significant geosciences tasks is the accurate classification of lithologies for metal and mineral resources exploration, characterization of oil/gas reservoir(s), and the planning and management of mining operations. With the availability of abundant, huge and multidimensional datasets, machine learning-based data-driven methods have been widely adopted to assist in solving geoscientific problems such as the efficient evaluation and interpretation of large datasets. The adoption of machine learning-based methods aims to improve lithological identification accuracy and extract information required for accurate and objective decision-making with respect to activities such as exploration, drilling, mine planning and production. Practically, this helps to reduce working time and operating costs. We aim to evaluate the feasibility of machine learning-based algorithms application to geophysical log data for the automated classification of lithologies based on the stratigraphic unit at the formation level for the purpose of distinguishing and correlating the quartzites between boreholes, and mapping key radioactive zones within the mining horizon. This study implemented four different machine learning algorithms: gradient boosting decision trees, random forest, support vector machine, and K-means clustering models. Analyzed features and labelled datasets are multivariate downhole geophysical and lithology logs from the two ICDP DSeis project boreholes drilled in the Klerksdorp gold field, respectively. To mitigate misclassification error and avoid model overfitting/underfitting, the optimal combination sets and optimal values for each implemented supervised model’s hyperparameters were obtained using the Grid search and 10-fold cross-validation optimization methods. The input dataset was randomly split automatedly into training and testing subsets that made up 80% and 20% of the original dataset, respectively. The models were trained and cross-validated using the training subset, and their performances were assessed using the testing subset. The classification performance of each model was evaluated using F1 scores and visualized using confusion matrices. The best supervised classification model for our study area was selected based on the testing subset F1 scores and computational cost of training models. The testing subset results shows that Random Forest and Support Vector Machine classifier models performed much better relative to the Gradient Boosting Decision Trees classifier model, with F1 scores over 0.80 in borehole A and B. In borehole A and B, Random Forest classifier has the least computational training time of about 14- and 6- hours, respectively. The feature importance results demonstrate that the logging feature P-wave velocity (Vp) is the highest predicting feature to the lithology classification in both boreholes. We find that the quartzite classes at different stratigraphic positions in each borehole are similar and they are correlated between the DSeis boreholes. The K-means clustering revealed three clusters in this study area and effectively map the radioactive zones. This study illustrates that geophysical log data and machine learning-based algorithms can improve the task of data analysis in the geosciences with accurate, reproducible and automated prediction of lithologies, correlation and mapping of radioactive zones in gold mine. This study outputs can serve as quality control measures for future similar studies both in the academic and industry. We identified that availability of large data is the major factor to high accuracy performance of machine learning-based algorithms for classification problems.Item Hydrogeological assessments and investigation of inflow sources at Lumwana Copper Mine, Zambia(University of the Witwatersrand, Johannesburg, 2023) Mbilima, Mike; Abiye, TamiruThis Research Report presents results of integrated field and desktop-based hydrogeological investigations at the Lumwana Mine, Zambia. Groundwater occurrence in the mine poses challenges with effective mining operations and slope stability. The primary aim of this study was to establish the sources of groundwater inflows and to establish the nature of surface water and groundwater interaction within the Lumwana Mine hydro-geotechnical units. The Lumwana hydrogeological investigation has been achieved through the integration of multi-disciplinary data types, which include geology, structures, hydrochemistry, meteorological data (rainfall, temperature, humidity and evapotranspiration), environmental isotopes, dewatering pumping records, groundwater level monitoring, water temperature, general hydrogeological data and surface hydrology. The investigation has confirmed the presence of hydraulic connections between different surface water bodies such as dams, diversion channels, streams and open pit excavation, and has proven to be a useful approach in tracing the source of mine inflows. Rainfall, groundwater and surface water samples have similar δ18O and δ2H isotopic signatures thus lamenting the existence of a hydraulic link between groundwater and surface water. Recharge estimation through Water Table Fluctuation method (WTF) determined 8% of mean annual precipitation (MAP). The dominant hydrochemical facies are Ca-Mg-HCO3 and Ca-Mg-SO4. The local geology and geochemistry of the tailings are the main controllers of groundwater chemistry through rock-water interaction. The geology of the study area consists of older metamorphosed gneisses, schists, migmatites, amphibolites and granitoids. Integrated assessment of the Lumwana hydrogeological environment has enabled the development of the Lumwana Mine hydrogeological conceptual model. In the shallow, highly to moderately weathered zones, groundwater flows from south towards low topographic regions in the northwest mimicking the general topography. The hydraulic test conducted at Lumwana Mine has revealed the saprock units have higher hydraulic conductivity by several orders compared to the saprolites and the fresh bedrock, where groundwater flow is mainly controlled by the occurrence and distribution of the fracture network.