Applied Geostatistics with SGeMS
eBook - PDF

Applied Geostatistics with SGeMS

A User's Guide

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Applied Geostatistics with SGeMS

A User's Guide

About this book

The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.

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Yes, you can access Applied Geostatistics with SGeMS by Nicolas Remy,Alexandre Boucher,Jianbing Wu in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Geophysics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. APPLIED GEOSTATISTICS WITH SGeMS
  3. Title
  4. Copyright
  5. Contents
  6. Foreword
  7. Preface
  8. List of Programs
  9. List of symbols
  10. 1 Introduction
  11. 2 General overview
  12. 3 Geostatistics: a recall of concepts
  13. 4 Data sets and SGeMS EDA tools
  14. 5 Variogram computation and modeling
  15. 6 Common parameter input interfaces
  16. 7 Estimation algorithms
  17. 8 Stochastic simulation algorithms
  18. 9 Utilities
  19. 10 Scripting, commands and plug-ins
  20. Bibliography
  21. Index