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The contributions in this volume were presented at the Fifth International Geostatistics Congress held in Wollongong, Australia, in September 1996. The papers provide a comprehensive account of the current methods and work in geostatistics, including recent theoretical developments and applications. Topics featured include: stochastic simulations, space-time modelling, Bayesian framework, marked point models, spatial sampling, image analysis, multifractal modelling, uncertainty assessment, support change and upscaling. The text should be of use to: researchers and practitioners working in quantitative modelling in earth sciences and engineering, including mining, petroleum, environmental sciences, hydrology, geotechnics, applied statistics and renewable resources.
Del 8 - Quantitative Geology and Geostatistics
Geostatistics Wollongong’ 96
Volume 2
Häftad, Engelska, 2012
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In diamond alluvial deposits, the information about the spatial distribution of stone size is of crucial importance for the quantitative characterisation of the different areas of the deposit. In fact, the value of the diamond reserves depends strongly on the distribution of stone sizes: between two areas with the same grade, the most valuable is the one with larger stones. The geological genesis of the mineralization, related with the transport and deposition of stones in trapsites, can create separated spatial areas, corresponding to different stone size. To characterise these distinct areas, the non smooth transitions between them should be accounted for, in the estimation of internal properties. An extended version of zonal control of geostatistical estimation (Soares et ai, 1995) proposed in this paper, aims to characterising the classes of size histogram for each geological unit, avoiding the smooth effect. For this purpose the morphology of each geological unit is obtained by using two distinct criteria: i) first, the points of each unit are classified according to the local and global probabilities of belonging to each unit (Soares, 1992); ii) in a second classification, the optimization technique of Simulated Annealing is used to rearrange the pre-classified points in order to impose, in the final morphological maps, the spatial variability of experimental samples (Goovaerts, 1994). A case study of a diamond alluvial deposit with two geological units with distinct stone size histograms is presented.