Synopses & Reviews
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.
Review
'At last: here is a publisher who has prepared a thoroughly practical and well presented guide to geostatistics together with software in a form which can be run by most on their own computer.' Geoscientist
Synopsis
A step-by-step user guide to geostatistical modeling for Earth Science graduates and researchers, and professional practitioners.
Synopsis
This practical book provides a detailed guide to using algorithms from the Stanford Geostatistical Modeling Software (SGeMS), an open-source computer package for solving problems involving spatially related variables. Accompanied by a CD with the software, it's a useful user-guide for Earth Science graduates, and practitioners of environmental and petroleum engineering.
Table of Contents
1. Introduction; 2. General overview; 3. Geostatistics: a recall of concepts; 4. Data sets & SGeMS EDA tools; 5. Variogram computation and modeling; 6. Common parameter input interfaces; 7. Estimation algorithms; 8. Stochastic simulation algorithms; 9. Utilities; 10. Scripting, commands and plug-ins; List of programs; List of symbols; Bibliography.