Geostatistics Rio 2000: Proceedings of the Geostatistics Sessions of the 31st International Geological Congress, Rio de Janeiro, Brazil, 6-17

ISBN-13: 9781402004704 / Angielski / Twarda / 2002 / 237 str.

C. Bettini; N. Champigny; M. Armstrong

Opis

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. The five contributions on petroleum science focus on different aspects of reservoir characterisation. All use stochastic simulations to generate 3D numerical models that reproduce the key features of reservoirs. Five of the ten contributions on mining present ore-body simulations; the others address questions like reconciling reserve estimates with production figures.
None of these contributions present new theory. Instead they show readers how to incorporate geology into geostatistical case studies in a meaningful way. 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.

Recenzje

From the reviews:

"This book is a collection of papers presented at a conference in Rio de Janeiro in August 2000. ... A significant feature of all these papers, including the reservoir modeling papers, is the focus on the specific applications ... . All of the papers also have a wealth of visual displays. Because geostatistical modeling practitioners commonly use color as a significant characteristic of any display ... ." (Technometrics, Vol. 47 (4), November, 2005)

Spis treści

Preface; R. Olea. Introduction; M. Armstrong, et al. Petroleum Papers. Using Quantitative Outcrop Databases As a Guide for Geological Reservoir Modelling; R. Eschard, et al. Quantification of facies relationships via proportion curves; C. Ravenne, et al. Geologic Modelling of External and Internal Reservoir Architecture of Fluvial Depositional Systems; P.E. Patterson, et al. Impact of Seismic Constraints on a Stochastic Reservoir Model and Fluid Flow Simulation; I. Azpiritxaga, et al. Practical Workflows for Reservoir Modelling; J.M. Yarus, et al. Mining Papers. Simulating the Geometry of a Granite-hosted Uranium Orebody; T. Skvortsova, et al. Simulation of Weathered Iron Ore Facies: Integrating Leaching Concepts and Geostatistical Models; D.T. Ribeiro, R.M. Carvalho. Geostatistical Simulation of Structurally Controlled Low Grade High Tonnage Gold Ores: A Strategy for Targeting Genuine Enriched Zones; A.H.M. Silva, et al. Geostatistical Framework for Modelling Clay Deposits: Nova Veneza Case Study in Southern Brazil; R.L. Stangler, et al. Risk Assessment of Reserve Calculation during Milestones of a Mine Life; F. Silva, et al. Successful Incorporation of Geological Controls into Reserve Evaluation: Recent Examples from Giant Copper Mines in Chile; N. Champigny, et al. Geological Conditions for a Correct Geostatistical Evaluation: Example 177 from the Elatsite Copper Deposit in Bulgaria; J. Todorov, et al. Evaluation of Kriging and Cokriging for Asbestos Ore Reserve Estimation at the Cana Brava Mine, Goiás, Brazil; R.P. Conde, J.K. Yamamoto. Geostatistical Evaluation of the Mineral Resources of the Cajati Mine, State of Sao Paulo, Brazil; G. Barros, J.K. Yamamoto. Variographic Trends of Gold in the Alluvial Sediments Associated with the QuartzLodes in the Princesa Isabel Region, Paraiba, Brazil; S.R. Lanusse, T.R. Gopinath.