Geostatistics Banff 2004

  • Oy Leuangthong
  • Clayton V. Deutsch

Part of the Quantitative Geology and Geostatistics book series (QGAG, volume 14)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Plenary

    1. Tingting Yao, Craig Calvert, Glen Bishop, Tom Jones, Yuan Ma, Lincoln Foreman
      Pages 23-33
    2. Alexandre Boucher, Roussos Dimitrakopoulos, J. A. Vargas-Guzmán
      Pages 35-44
    3. Odd Kolbjørnsen, Petter Abrahamsen
      Pages 45-54
    4. R. Mohan Srivastava, Roland Froidevaux
      Pages 55-64
    5. Xiaohuan Liu, Sanjay Srinivasan
      Pages 75-84
    6. John Manchuk, Oy Leuangthong, Clayton V. Deutsch
      Pages 85-94
    7. Denis Marcotte, Miro Powojowski
      Pages 115-124
    8. John Stephenson, Chris Holmes, Kerry Gallagher, Alexandre Pintore
      Pages 125-134
    9. Michael J. Pyrcz, Clayton V. Deutsch
      Pages 135-144
    10. Christophe Aug, Jean-Paul Chilès, Gabriel Courrioux, Christian Lajaunie
      Pages 145-154
    11. Christian Lantuéjoul, Helene Beucher, Jean-Paul Chilès, Christian Lajaunie, Hans Wackernagel, Pascal Elion
      Pages 165-174
    12. L. Y. Hu, M. Le Ravalec-Dupin
      Pages 175-184

About this book

Introduction

The conference proceedings consist of approximately 120 technical papers presented at the Seventh International Geostatistics Congress held in Banff, Alberta, Canada in 2004. All the papers were reviewed by an international panel of leading geostatisticians.

The five major sections are: theory, mining, petroleum, environmental and other applications. The first section showcases new and innovative ideas in the theoretical development of geostatistics as a whole; these ideas will have large impact on (1) the directions of future geostatistical research, and (2) the conventional approaches to heterogeneity modelling in a wide range of natural resource industries. The next four sections are focused on applications and innovations relating to the use of geostatistics in specific industries. Historically, mining, petroleum and environmental industries have embraced the use of geostatistics for uncertainty characterization, so these three industries are identified as major application areas. The last section is open for innovative geostatistical application to address the issues and impact of uncertainty in other industries.

Audience

Researchers and practitioners both in industry and academia, working in the fields of geology, petroleum, mining, and environmental science and engineering.

Keywords

3D Geostatistics Kriging Likelihood Markov Markov random field Theoretical Development digital elevation model knowledge linear optimization modeling simulation simulation model statistics uncertainty

Editors and affiliations

  • Oy Leuangthong
    • 1
  • Clayton V. Deutsch
    • 1
  1. 1.Department. of Civil & Environmental EngineeringUniversity of AlbertaCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4020-3610-1
  • Copyright Information Springer Science+Business Media B.V. 2005
  • Publisher Name Springer, Dordrecht
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4020-3515-9
  • Online ISBN 978-1-4020-3610-1
  • Series Print ISSN 0924-1973
  • About this book