Geostatistics Rio 2000
. Ed(S): Armstrong, M.; Bettini, C. (Universidade Federal do Rio de Janeiro, Brazil); Champigny, N. (Pricewaterhouse Coopers Llp, Montreal, Canada);
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Description for Geostatistics Rio 2000
Paperback. Editor(s): Armstrong, M.; Bettini, C. (Universidade Federal do Rio de Janeiro, Brazil); Champigny, N. (Pricewaterhouse Coopers LLP, Montreal, Canada); Galli, A. (Ecole des Mines de Paris, France); Remacre, A. (UNICAMP, Campinas, Brazil). Series: Quantitative Geology and Geostatistics. Num Pages: 237 pages, biography. BIC Classification: PDE; RBGB; TBJ; TNCC. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 13. Weight in Grams: 402.
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 ... Read more
Show LessProduct Details
Format
Paperback
Publication date
2011
Publisher
Springer Netherlands
Number of pages
237
Condition
New
Series
Quantitative Geology and Geostatistics
Number of Pages
237
Place of Publication
Dordrecht, Netherlands
ISBN
9789048159543
SKU
V9789048159543
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Geostatistics Rio 2000
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 ... Read more