Geostatistics Wollongong 96

The papers in this volume 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, and Bayesian framework.

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.

The papers in this volume 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, and Bayesian framework.

This volume contains selected contributions from geoENV III - the Third European Conference on Geostatistics for Environmental Sciences, held in Avignon, France in November 2000. This third book of the geoENV series illustrates the new methodological developments in geostatistics, as applied to environmental sciences, which have occurred during the last two years. It also presents a wide variety of practical environmental applications which will be of interest to both researchers and practitioners. The book starts with two keynote papers on hydrogeology and on climatology and atmospheric pollution, followed by forty contributions. The content of this book is foremost practical. The editors have endeavored to compile a set of papers in which the readers could perceive how geostatistics is applied within environmental sciences. A few selected methodological and theoretical contributions are also included. The papers are organised in the following sections: Air Pollution / Climate; Environment; Health / Ecology; Hydrology; Methods; Soil Science / Site Remediation. presenting applications varying from delineation of hazardous areas, monitoring water quality, space-time modeling of sand beaches, areal rainfall estimation, air pollution monitoring, multivariate conditional simulation, soil texture analysis, fish abundance analysis, tree productivity index estimation, radionuclide migration analysis, wombling procedure, tracer tests modeling, direct sequential co-simulation to stochastic modeling of flow and transport. Audience: This publication will be of great interest and practical value to geostatisticians working both in academia and in industry.

Geostatistics is used not only in reservoir characterization but also in velocity analysis, time-to-depth conversion, seismic inversion, uncertainty quantification, and data integration in earth models. This book includes covariance and the variogram, interpolation, heterogeneity modelling, uncertainty quantification, and geostatistical inversion.

Geostatistics Rio 2000 includes fifteen contributions, five of which are on applications in petroleum science and ten are on mining geostatistics. These contributions were presented at the 31st International Geological Congress, held in Rio de Janeiro, Brazil, from 6-17 August, 2000. Stochastic simulation was the key theme of these case studies. A wide range of methods was used: truncated gaussian and plurigaussian, SIS and SGS, boolean methods and multi-point attractors. Audience: The volume will be of value to scientists, researchers, and professionals in geology, mining engineering, petroleum engineering, mathematics and statistics, as well as those working for mining and oil companies.

The return of the congress to North America after 20 years of absence could not have been in a more ideal location. The beauty of Banff and the many offerings of the Rocky Mountains was the perfect background for a week of interesting and innovative discussions on the past, present and future of geostatistics. The congress was well attended with approximately 200 delegates from 19 countries across six continents. There was a broad spectrum of students and seasoned geostatisticians who shared their knowledge in many areas of study including mining, petroleum, and environmental applications. You will find 119 papers in this two volume set. All papers were presented at the congress and have been peer-reviewed. They are grouped by the different sessions that were held in Banff and are in the order of presentation. These papers provide a permanent record of different theoretical perspectives from the last four years. Not all of these ideas will stand the test of time and practice; however, their originality will endure. The practical applications in these proceedings provide nuggets of wisdom to those struggling to apply geostatistics in the best possible way. Students and practitioners will be digging through these papers for many years to come. Oy Leuangthong Clayton V. Deutsch ACKNOWLEDGMENTS We would like to thank the industry sponsors who contributed generously to the overall success and quality of the congress: De Beers Canada Earth Decision Sciences Maptek Chile Ltda. Mira Geoscience Nexen Inc. Petro-Canada Placer Dome Inc.