Geostatistical Software Library and User's Guide
Contents
1. GSLIB Geostatistical Software Library and User s Guide Second Edition Clayton V Deutsch Department of Petroleum Engineering Stanford University Andr G Journel Department of Geological and Environmental Sciences Stanford University New York Oxford OXFORD UNIVERSITY PRESS 1998 Contents I Introduction L1 About the Source Code ele II Getting Started II 1 Geostatistical Concepts A Review ls IL1 1 The Random Function Concept IL1 2 Inference and Stationarity 11 1 3 V riogr mi 3 0265 030 ke Rae Gow eee oe ILLIA Kriglng sineme eana a a ee ee Tee RU RR rg IL1 5 Stochastic Simulation IL2 GSLIB Conventions 00000008 IL2 1 Computer Requirements 4 1 2 2 Data Files eee m RS 1 2 3 Grid Definition 2 lle IL2 4 Program Execution and Parameter Files IL2 5 Machine Precision les IL3 Variogram Model Specification IL3 1 A Straightforward 2D Example 1L3 2 A 2D Example with Zonal Anisotropy 11 4 Search Strategies 2 eee ILS DataSets 2 en Be we ee Rd II 6 Problem Set One Data Analysis IH Variograms IIL1 Measures of Spatial Variability IIL2 GSLIB Variogram Programs 0 IIL3 Regularly Spaced Data gam ee II 4 Irregularly Spaced Data gamv sess IIL5 Variogram2. Maps varmap 004 IIL6 Application Notes ao tesgiyada aeons s IIL7 Problem Set Two Variograms vii 12 13 14 18 20 20 21 22 23 24 24 29 30 32 37 40 viii IV Kriging IV 1 Kriging with GSLIB sss IV 11 Simple Kriging IV 12 Ordinary Kriging IV 1 3 Kriging with a Trend Model IV 1 4 Kriging the Trend IV 1 5 Kriging with an External Drift IV 1 6 Factorial Kriging IV L T Cokriging ios sage aoe eh ee i IV 1 8 Nonlinear Kriging IV 1 9 Indicator Kriging IV 1 10 Indicator Cokriging IV 1 11 Probability Kriging IV 1 12 Soft Kriging The Markov Bayes Model IV 113 Block Kriging IV 1 14 Cross Validation IV 2 A Straightforward 2D Kriging Program kb2d IV 3 A Flexible 3D Kriging Program kt3d IV 4 Cokriging Program cokb3d_ IV 5 Indicator Kriging Program ik3d IV 6 Application Notes IV 7 Problem Set Three Kriging IV 8 Problem Set Four Cokriging IV 9 Problem Set Five Indicator Kriging V Simulation V 1 Principles of Stochastic Simulation V 1 1 Reproduction of Major Heterogeneities V 1 2 Joint Simulation of Several Variables V 1 3 The Sequential Simulation Approach V 1 4 Error Sim
3. Partial Solutions to Problem Sets 241 A 1 Problem Set One Data Analysis 241 A 2 Problem Set Two Variograms 253 A 3 Problem Set Three Kriging 008 266 A 4 Problem Set Four Cokriging 00 271 A 5 Problem Set Five Indicator Kriging 283 A 6 Problem Set Six Simulations 296 B Software Installation 325 Bt Installation som eed Wow a Scale ages a Da ea eS 325 B 2 Troubleshooting 0002 ee eee 327 C Programming Conventions 329 GL General cocuts ise Hoe eel ex eo haa we ae 329 C 2 Dictionary of Variable Names 04 330 C 3 Reference Lists of Parameter Codes 336 D Alphabetical Listing of Programs 339 E List of Acronyms and Notations 341 Eid Acronyms 2 cccu aen RR RU Ex RE 341 E 2 Common Notation leen 342 Bibliography 347 Index 363
4. es V 12 Problem Set Six Simulation sss VIOther Useful Programs VI 1 PostScript Display llle VI 1 1 Location Maps locmap esee VI1 2 Gray and Color Scale Maps pixelplt VL1 3 Histograms and Statistics histplt VL1 4 Normal Probability Plots probplt VL1 5 Q Q and P P plots qpplt VL1 6 Bivariate Scatterplots and Analysis scatplt VI1 7 Smoothed Scatterplot Display bivplt VI 1 8 Variogram Plotting vargplt VI2 Utility Programs lees VI 2 1 Coordinates addcoord and rotcoord VI 2 2 Cell Declustering declus o VI 2 3 Histogram and Scattergram Smoothing VI 2 4 Random Drawing draw VI 2 5 Normal Score Transformation nscore VI 2 6 Normal Score Back Transformation backtr VI 2 7 General Transformation trans VI 2 8 Variogram Values from a Model vmodel VI 2 9 Gaussian Indicator Variograms bigaus VI 2 10 Library of Linear System Solvers VI 2 11 Bivariate Calibration b calib VI 2 12 Postprocessing of IK Results postik VI 2 13 Postprocessing of Simulation Results postsim 158 159 166 167 169 169 170 174 175 175 181 182 183 183 187 189 191 199 199 201 202 204 206 207 208 210 211 211 211 213 214 222 223 226 227 230 231 232 235 236 239 x CONTENTS Appendices A
5. ulation V 2 6 Multiple Truncations of a Gaussian Field V 3 Indicator Based Algorithms V 3 1 Simulation of Categorical Variables V 3 2 Simulation of Continuous Variables V 1 5 Questions of Ergodicity V 1 6 Going Beyond a Discrete CDF V 2 Gaussian Related Algorithms V 2 1 Normal Score Transform V 2 2 Checking for Bivariate Normality V 2 3 Sequential Gaussian Simulation V 2 4 LU Decomposition Algorithm V 2 5 The Turning Band Algorithm V 4 p Field Simulation V 5 Boolean Algorithms CONTENTS CONTENTS V 6 Simulated Annealing es V 6 1 Simulation by Simulated Annealing V 6 2 Postprocessing with Simulated Annealing V 6 3 Iterative Simulation Techniques V 7 Gaussian Simulation Programs sse V 7 1 LU Simulation lusim sss V 7 2 Sequential Gaussian Simulation sgsim V 7 3 Multiple Truncations of a Gaussian Field gtsim V 8 Sequential Indicator Simulation Programs V 8 1 Indicator Simulation sisim V 8 2 p Field Simulation pfsim V 9 A Boolean Simulation Program ellipsim V 10 Simulated Annealing Programs V 10 1 Simulated Annealing sasim V 10 2 An Annealing Postprocessor anneal V 11 Application Notes le
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