Abstract
Underground mining at Obuasi in Ghana has been in operation since 1947. This paper uses geostatistical methods to evaluate gold ore blocks to ensure reliable grades for mining large tonnage and low-grade resources. Historically, the principal ores were low tonnage, high grade and relatively homogeneous quartz stockwork with simple geometry and average bulk grades in the range of 20-30 g/t that were evaluated using conventional polygonal methods and mined by semi-mechanized means. Currently, the ore is a shear-hosted mixed quartz vein and disseminated sulphide type deposit of low grade that is mined using highly mechanized means. The need therefore arises for a re-assessment of the estimation procedures to ensure prolonged and more profitable mining. Both diamond drill (DD) core and stope/cross-cut channel samples were taken from Block 1 at the mine for analyses and re-assessment. A wireframe model was used to constrain the three dimensional (3D) block model of the deposit. Ordinary kriging (OK) and multiple indicator kriging (MIK) geostatistical methods were used to estimate gold grades. Grade distribution is positively skewed with high spatial variability and extreme values while background values are established as <0.6 g/t. The Spatial variability is characterized by fitting models on experimental variograms. The MIK approach mitigates the effects of outliers and establish grades that are consistently lower than the OK and the weighted average method that are widely used at the mine. The MIK method, a non-linear, non-parametric method of local grade estimation are applicable to the deposit architecture. Profoundly, the MIK method is a more reliable approach considering the fact that the MCF based on the estimates at the mine are high despite operational deficiencies on the mine. The results from this study demonstrates usefulness of geostatistics to determine the architecture of Au mineralization at the deposit scale.
Highlights
Mining projects relating to precious metals such as gold (Au) deposits, require accurate information on tonnage and grade to ensure credible resource estimates and good project feasibility (Sinclair and Blackwell, 2002; Wellmer et al, 2007; Daya, 2012; Gol et al, 2017)
The coefficient of variation (CoV) is 1.63 (Table 7) which is higher than expected for a normal distribution (Al-Hassan and Annels 1994)
The study established that, the distribution of the Au grades from the Obuasi Mine is positively skewed with high variability and extreme values
Summary
Mining projects relating to precious metals such as gold (Au) deposits, require accurate information on tonnage and grade to ensure credible resource estimates and good project feasibility (Sinclair and Blackwell, 2002; Wellmer et al, 2007; Daya, 2012; Gol et al, 2017). At the Anglogold Ashanti mine in Ghana, the methods of ore reserve estimation have been mainly by polygonal method and a factor applied for error correction (Amadu, 2006) Though historically, these methods might have worked satisfactorily, there are many drawbacks due to inherent assumptions that leads to overestimation (Sinclair and Blackwell, 2002). This is because the Obuasi mine orebodies are characterised by nonuniform mineralization distribution and sharp boundaries (Baxter and Yates, 2001; Perrouty et al, 2012)
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