The study described in this paper involves the application of a conventional resource estimation method, inverse distance weighting (IDW), and univariate geostatistical technique, ordinary kriging (OK) to the gold grades data from the modified palaeoplacer Teberebie gold deposit, in Ghana. The deposit consists of 4 layered well-defined orebodies referred to as A reef, CDE reef, F24 reef and G reef at the mine environment. Simple, reliable, and adequately accurate resource/reserve estimation are essential to mining operations. Data used for the research were collected by diamond and reverse circulation (RC) drilling. A total of 19353 one-meter composite samples, consisting of 18962 RC chip samples from 695 RC drill holes, and 391 diamond drill core samples from 11 DD holes. Samples were analysed by atomic absorption spectrometry (AAS) for gold (Au). Descriptive statistical treatment was conducted on grade values for the reefs. To analyse for spatial structure of Au mineralisation, experimental downhole, and several horizontal directional semi-variograms were computed, and models fitted. Ore reserves were estimated by OK and IDW methods, and results of the various reefs compared. Regression analysis of estimated results indicate that, the inverse distance square (ID2) model produced estimates that compared well with the OK model in all the ore zones. It is therefore, appropriate to use ID2 as an alternative estimation method to the OK method for purposes of mine planning and grade control.
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.
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