Abstract:

The capability of X-ray transmission (XRT) sensor to distinguish and identify mineral textures in copper gold porphyry on half drill core was investigated using a laboratory-scale XRT belt scanner. Results showed that XRT can detect the variations in mineral content and responds strongly to the textures associated with quartz, sulfide and iron oxide minerals. XRT has the capability of distinguishing between metal-bearing minerals and non-metallic minerals. The relative densities of samples were calibrated from XRT energy attenuation data. The surface mineral compositions of samples were calculated based on the element contents collected by Micro X-ray fluorescence (μXRF). The correlation and regression analysis of the relative densities and surface mineral compositions further validated the relationship between mineral compositions and XRT responses. The analysis showed that XRT responses had a very strong correlation with Fe-oxide, a strong correlation with white mica, quartz, plagioclase and chalcopyrite, and a moderate correlation with carbonates and biotite. With a coefficient of determination (R-squared, R2) of 0.92, the regression model is capable of explaining 91.2% of the variation in the relative density.

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Ms. JIAJIA DAI