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published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

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Accurate ore estimation processes are of crucial importance in the mining scenario. Over the last 20 years, one practical approach to improve ore grade estimation has encouraged the need to incorporate the geology of the ore deposit being estimated in the estimation process. The objective of this study is to investigate the impact of the geology on the kriging estimation of the ore grade of a portion of a porphyry copper deposit. Preliminary data analysis demonstrates the need to perform a subsequent variogram modeling and kriging estimation of the ore grade by rock type separation. Global and local estimations were done to assess the influence of the geology on the ore grade estimation at a global and local scales. The results obtained in this study demonstrated that for the portion of the deposit studied the incorporation of the geology does not produce substantial improvement on the ore grade estimation.

The success of rock fragmentation due to blasting depends on many variables, such as rock properties, in-situ fracturing, and blast design. Traditionally, the size distribution of fragmented rock particles has been determined through screen sieving. Modern techniques using video images and computer image processing techniques have the potential for analyzing rock fragmentation accurately and efficiently. A procedure has been developed for analyzing rock fragmentation which uses a high-resolution video camera for capturing images in the field, and specialized computer algorithms for processing these images. First of all, computer algorithms have been developed to delineate the individual rock fragments in the images. Secondly, a set of experiments have been conducted in the laboratory, in which the two dimensional information from the images is correlated with sieve results. Based on these experiments, a set of probabilities have been determined for correctly determining the size and volume of rock fragments from two dimensional images. Using these probabilities along with the particle delineation algorithm, the size distribution for the rock fragments is calculated. The computer algorithms can also combine information from many images to take into account sampling and images taken at different scales.

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