Statistics for Spatial Data.

Thirty-seven programs that summarize data with histograms and other graphics, calculate measures of spatial continuity, provide smooth least-squares-type maps, and perform stochastic spatial simulation.

GSLIB: Geostatistical Software Library and User's Guide

1. Exploratory Data Analysis 2. The Random Functions Model 3. Inference and Modeling 4. Local Estimation: Accounting for a Single Attribute 5. Local Estimation: Accounting for Secondary Information 6. Assessment of Local Uncertainty 7. Assessment of Spatial Uncertainty 8. Summary

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Geostatistics for Natural Resources Evaluation

We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950-2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three-step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three-dimensional thin-plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years. Copyright 2008 by the American Geophysical Union.

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A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

Statistics and Data Analysis in Geology

Geostatistics can be defined as the statistical study of phenomena that fluctuate in space and time. Originally the objective of the field was to improve forecasts of ore grade and reserves, but the mathematical generality of the approach has led to the application of geostatistics to other areas, ranging from pest control to pollution monitoring. GSLIB provides a source code that can be used as a starting point for custom programs, advanced applications and research. GSLIB is addressed to the reasonably advanced practitioner or researcher who needs powerful, flexible and documented programs that are not confined to user-friendly menus. It offers the most advanced methods in the field, including co-kriging and several forms of conditional simulations, all developed in three-dimensions, which can be run on any kind of computer.

1. Introduction 2. Preliminary Statistical Concepts 3. Gridding Reservoir Layers 4. Quantifying Spatial Correlation 5. Preliminary Mapping Concepts 6. Cell-Based Facies Modeling 7. Object-Based Facies Modeling 8. Porosity and Permeability Modeling 9. Simulated Annealing 10. Uncertainty Management 11. Special Topics Glossary and Notation Bibliography Index

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Geostatistical Reservoir Modeling

This book will be an important text to most of geostatisticians, including graduate students and experts in the field of practical geostatistics. The guts of this volume are the two highdensity IBM disks which come with it and contain 37 programs which can be run in both UNIX and DOS environments but are not machine specific. The programs are aimed at three major areas of geostatistics: quantifying spatial variability (variograms), generalized linear regression techniques (kriging), and stochastic simulation. In all there are some 80 source files included with the distribution diskettes. The programs are not execuable but require to be compiled before running them. A machine with a fortran compiler is required. The intent of the authors is to make this suite of programs accessible to anyone who wants to use them. The source code of these programs has been assembled, developed, tested, and tried at Stanford University over a period of some 12 years. Though this library of programs is not intended as a commercial product it represents a gold mine to those who need a jump start into the field of geostatistics.

Geostatistical Software Library and User's Guide

The variogram is a critical input to geostatistical studies: (1) it is a tool to investigate and quantify the spatial variability of the phenomenon under study, and (2) most geostatistical estimation or simulation algorithms require an analytical variogram model, which they will reproduce with statistical fluctuations. In the construction of numerical models, the variogram reflects some of our understanding of the geometry and continuity of the variable, and can have a very important impact on predictions from such numerical models. The principles of variogram modeling are developed and illustrated with a number of practical examples. A three-dimensional interpretation of the variogram is necessary to fully describe geologic continuity. Directional continuity must be described simultaneously to be consistent with principles of geological deposition and for a legitimate measure of spatial variability for geostatistical modeling algorithms. Interpretation principles are discussed in detail. Variograms are modeled with particular functions for reasons of mathematical consistency. Used correctly, such variogram models account for the experimental data, geological interpretation, and analogue information. The steps in this essential data integration exercise are described in detail through the introduction of a rigorous methodology.

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Clayton V. Deutsch

Papers

GSLIB: Geostatistical Software Library and User's Guide

GSLIB: Geostatistical Software Library and User's Guide

Geostatistical Reservoir Modeling

Geostatistical Software Library and User's Guide

Teacher's Aide Variogram Interpretation and Modeling 1