MESMEG / Department of Mining and Environmental Geology / Giyani Greenstone Belt is known to host significant amount of gold of which about 10 tonnes were extracted from the belt in the 19th century. Due to increased gold price and mining practices that make it economic to mine low-grade ore deposits, major gold deposits within the belt have been the main targets for exploration while Nebulas Prospect remain unnoticed. To make the Nebulas Prospect attractive for investment, its gold mineralization potential needed to be investigated.
The main purpose of this study was to conduct assessment of the probable gold mineralization in the Nebulas Prospect and its economic viability. The specific objectives were to establish the gold mineralized zones within the Nebulas Prospect, develop a geological model showing the geometry and placement of gold in the subsurface, establish gold grade distribution and its economic implication, and select the most appropriate and practical mining method for exploitation of the established gold deposit. The research approaches used in achieving these objectives comprised of knowledge driven predictive modelling of Nebulas Prospect to derive prospectivity map demarcating the area with the potential of hosting gold mineralization. Magnetic survey was conducted in geological permissive areas, thereby establishing boundaries of mineralization, both lateral and vertical. Geological and subsurface gold grade distribution were carried out by means of trenching and pitting. The integration of the geological, geophysical and geochemical data using Geosoft 8.5 and ArcGIS 10.5 assisted in development of a gold deposit model that model illustrates distribution and concentration of gold.
Results of the investigation reveals that Banded Iron Formation (BIF) dominates the southern part of the study area while quartz vein and schist dominate the northern part. The application of knowledge driven predictive modelling established mineral prospectivity map for Nebulas Prospect, which narrowed the potential area for further investigation. The area located outside the boundary of prospective area indicated low mineralization potential compared to highly mineralized zone within geological permissive boundary.
The two mineralize zones which exits in the Nebulas Prospect are separated by pegmatite intrusion which is observed from magnetic data presentation. The gold is hosted within BIF, schist and quartz vein. The highest concentration observed value of 10.65 g/t is hosted in serpentine schist and lowest significant of 1.24 g/t in BIF. The gold grades are higher in schists than in BIF and quartz veins. The Nebulas Prospect present significant measured
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gold mineral resource with substantial economic potential. The evaluation of the technical aspects of the Nebulas Gold Deposit, which include grade and tonnage was estimated through longitudinal vertical section method. The gold hosted within Banded Iron Formation (BIF) comprise a measured gold resource of 6957.6 t at an average weighted grade of 2.22 g/t Au. However, the gold mineralization hosted within tremolite-mica schist, serpentine schist and quartz veins comprise a measured gold resource of 3919.37 t with average grade of 3.8 g/t Au. The Nebulas Gold Deposit contain a significant grade and tonnage.
At an assumed currently economically mineable cutoff grade 1 g/t Au, Nebulas Prospect has a measured resource of 10877 t at a weighted average grade of 2.79 g/t Au. Analytical hierarchy process (AHP) was used to prioritize the factors affecting mining method selection and ranking of potential mining method, technically appropriate for the established gold deposit in Nebulas Prospect. Open pit mining method was identified as appropriated for extraction of the Nebulas Gold Deposit. / NRF
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:univen/oai:univendspace.univen.ac.za:11602/1093 |
Date | 18 May 2018 |
Creators | Mavhungu, Mbofholowo Emmanuel |
Contributors | Amponsah-Dacosta, Francis, Mhlongo, Siphiwe |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Dissertation |
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