Geostatistical Case Studies

It is now nearly 25 years since the first textbook on geostatistics ("Traitj de gjostatistique appliquje" by G. Matheron) appeared in print in 1962. In that time geostatis tics has grown from an arcane theory regarded with scepticism by statisticians and miners alike, to a reputable scientific disci pline which is routinely used in the geosciences. In the mining industry, in particularly, comparisons between predicted reserve estimates and actual production figures have proved its worth. Few now doubt its usefulness as a statistical tool in the earth sciences. Over the past quarter of a century, many geostatistical case studies have been published but the vast majority of these are routine applications of kriging. Our objective with this volume is to present a series of innovative applications of geostatistics. These range from a careful variographic analysis on uranium data, through detailed studies on geologically complex deposits right up to the latest nonlinear methods applied to deposits with highly skew data distributions. Applications of new techniques such as the external drift method for combining well data with seismic information have also been included. Throughout the volume the accent has been put on how to apply geostatistics in practice. Notation has been kept to a mininmum and mathematical details have been relegated to annexes. We hope that this will encourage readers to put the more sophis ticated techniques into practice in their own fields.

GIS and Geostatistical Techniques for Groundwater Science provides a detailed synthesis of the application of GIS and geostatistics in groundwater studies. As the book illustrates, GIS can be a powerful tool for developing solutions for water resource problems, assessing water quality, and managing water resources. Beginning with an introduction to the history of GIS and geostatistical techniques in groundwater studies, the book then describes various spatial techniques, including case studies for various applications, from quality assessment, to resource management. This book assembles the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, one of our most important natural resources. Provides details on the application of GIS and statistics in groundwater studies Includes practical coverage of the use of spatial analysis techniques in groundwater science Bridges the gap between geostatistics and GIS as it relates to groundwater science and management Offers worldwide case studies to illustrate various techniques and applications in addressing groundwater issues

The aim of this book is to bring together a series of contributions from experts in the field to cover the major aspects of the application of geostatistics in precision agriculture. The focus will not be on theory, although there is a need for some theory to set the methods in their appropriate context. The subject areas identified and the authors selected have applied the methods in a precision agriculture framework. The papers will reflect the wide range of methods available and how they can be applied practically in the context of precision agriculture. This book is likely to have more impact as it becomes increasingly possible to obtain data cheaply and more farmers use onboard digital maps of soil and crops to manage their land. It might also stimulate more software development for geostatistics in PA.

This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers extensive geostatistical background information, including detailed descriptions of the main geostatistical tools traditionally used in Earth related sciences to infer the spatial distribution of a given property of interest. This framework is then directly linked with applications in the oil and gas industry and how it can be used as the basis to simultaneously integrate geophysical data (e.g. seismic reflection data) and well-log data into reservoir modeling and characterization. All of the cutting-edge methodologies presented here are first approached from a theoretical point of view and then supplemented by sample applications from real case studies involving different geological scenarios and different challenges. The book offers a valuable resource for students who are interested in learning more about the fascinating world of geostatistics and reservoir modeling and characterization. It offers them a deeper understanding of the main geostatistical concepts and how geostatistics can be used to achieve better data integration and reservoir modeling.

Based on a postgraduate course that has been successfully taught for over 15 years, the underlying philosophy here is to give students an in-depth understanding of the relevant theory and how to put it into practice. This involves going into the theory in more detail than most books do, and also discussing its applications. It is assumed that readers, students and professionals alike are familiar with basic probability and statistics, as well as the matrix algebra needed for solving linear systems; however, some reminders on these are given in an appendix. Exercises are integrated throughout, and the appendix contains a review of the material.