Geostatistical Simulations

Proceedings of the Geostatistical Simulation Workshop, Fontainebleau, France, 27–28 May 1993

  • M. Armstrong
  • P. A. Dowd

Part of the Quantitative Geology and Geostatistics book series (QGAG, volume 7)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Jean-Paul Chiles
    Pages 37-42
  3. Bjørn Kåre Hegstad, Henning Omre, Håkon Tjelmeland, Kelly Tyler
    Pages 43-55
  4. Alain Galli
    Pages 72-77
  5. R. Brémond, D. Jeulin
    Pages 89-105
  6. Margaret Armstrong
    Pages 106-109
  7. J. Jaime Gómez-Hernández, Eduardo F. Cassiraga
    Pages 111-124
  8. Peter Ravenscroft
    Pages 125-129
  9. Chantal de Fouquet
    Pages 131-145
  10. Peter Dowd
    Pages 178-184
  11. O. Jaquet, P. Y. Jeannin
    Pages 185-195
  12. Henning Omre
    Pages 212-215
  13. A. Galli, H. Beucher, G. Le Loc’h, B. Doligez, Heresim Group
    Pages 217-233
  14. Frode Georgsen, Thore Egeland, Ragnar Knarud, Henning Omre
    Pages 235-250

About these proceedings

Introduction

When this two-day meeting was proposed, it was certainly not conceived as a celebration, much less as a party. However, on reflection, this might have been a wholly appropriate gesture because geostatistical simulation came of age this year: it is now 21 years since it was first proposed and implemented in the form of the turning bands method. The impetus for the original development was the mining industry, principally the problems encountered in mine planning and design based on smoothed estimates which did not reflect the degree of variability and detail present in the real, mined values. The sustained period of development over recent years has been driven by hydrocarbon applications. In addition to the original turning bands method there are now at least six other established methods of geostatistical simulation. Having reached adulthood, it is entirely appropriate that geostatistical simulation should now be subjected to an intense period of reflection and assessment. That we have now entered this period was evident in many of the papers and much of the discussion at the Fontainebleau meeting. Many questions were clearly articulated for the first time and, although many ofthem were not unambiguously answered, their presentation at the meeting and publication in this book will generate confirmatory studies and further research.

Keywords

Kriging Reservoir Statistica algorithm digital elevation model environment simulation

Editors and affiliations

  • M. Armstrong
    • 1
  • P. A. Dowd
    • 2
  1. 1.Centre de GéostatistiqueFontainebleauFrance
  2. 2.Department of Mining and Mineral EngineeringUniversity of LeedsUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8267-4
  • Copyright Information Springer Science+Business Media B.V. 1994
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4372-6
  • Online ISBN 978-94-015-8267-4
  • Series Print ISSN 0924-1973
  • About this book