Applied Geostatistics With Sgems
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Applied Geostatistics with SGeMS
Author: Nicolas Remy
language: en
Publisher: Cambridge University Press
Release Date: 2011-04-14
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.
Applied Geostatistics with SGeMS
Author: Nicolas Remy
language: en
Publisher: Cambridge University Press
Release Date: 2009-01-22
A step-by-step user guide to geostatistical modeling for Earth Science graduates and researchers, and professional practitioners.
Applied Geostatistics
Author: Edward H. Isaaks
language: en
Publisher: Oxford University Press, USA
Release Date: 1989
In this introductory text the authors demonstrate how simple statistical methods can be used to analyze earth science data. In clear language, they explain how various forms of the estimation method called kriging can be employed for specific problems. The book highlights an instructive case study of a simulated deposit. This model helps students develop an understanding of how statistical tools work in real situations, and serves as a tutorial guide to help the reader through what may be their first independent geostatistical study. Though the authors have avoided mathematical formalism, the presentation is not simplistic and readers should be familiar with basic calculus and be able to find the minimum of a function by using the first derivative.