Solved Problems in Geostatistics (eBook)

Oy Leuangthong, PhD, is Assistant Professor in the Department of Civil and Environmental Engineering at the University of Alberta, Canada. Dr. Leuangthong conducts extensive research on the use of geostatistical methods for improving mineral resources and petroleum reservoirs. K.Daniel Khan, PHD, is an Earth Scientist with Chevron Corporation, specializing in reservoir modeling. Dr. Khan's work focuses on modeling heterogeneity and fluid flow processes using geostatistical and inverse techniques. Clayton V. Deutsch, PHD, is Professor in the Department of Civil and Environmental Engineering at the University of Alberta, where he is also Director of the School of Mining and Petroleum Engineering. He has over twenty years of experience in both academia and industry. Dr. Deutsch has published over 100 articles in his areas of research interest, which include modeling heterogeneity and uncertainty in petroleum reservoirs and mineral deposits.

Preface and Acknowledgments.

1. Introduction.

1.1 Plan of this Book.

1.2 The Premise of Geostatistics.

1.3 Nomenclature.

2. Getting Comfortable with Probabilities.

2.1 Parametric Probability Distributions.

2.2 Variance of Linear Combinations.

2.3 Standardization and Probability Intervals.

3. Obtaining Representative Distributions.

3.1 Basic Declustering.

3.2 Debiasing with Bivariate Glaussian Distribution.

3.3 Comparison of Declustering Methods.

4. Monte Carlo Simulation.

4.1 Impact of the Central Limit Theorem.

4.2 Bootstrap and Spatial Bootstrap.

4.3 Transfer of Uncertainty.

5. Variograms and Volume Variance.

5.1 Geometric Anisotropy.

5.2 Variogram Calculation.

5.3 Variogram Modeling and Volume Variance.

6. Kriging.

6.1 Stationary Kriging.

6.2 Nonstationary Kriging.

6.3 Screening Effect of Kriging.

7. Gaussian Simulation.

7.1 Bivariate Gaussian Distribution.

7.2 Conditioning by Kriging.

7.3 Gaussian Simulation.

8. Indicators.

8.1 Variogram of Objects.

8.2 Indicator Variograms and the Gaussian Distribution.

8.3 Indicator Simulation for Categorical Data.

9. Multiple Variables.

9.1 Linear Model of Coregionalization.

9.2 Gaussian Cosimulation.

9.3 Multiscale Cokriging.

10. Special Topics.

10.1 Decision Making in the Presence of Uncertainty.

10.2 Trend Model Construction.

10.3 Multiple Point Statistics.

11. Closing Remarks.

Bibliography.

Index.

?The book is more than its title; it really is a treatise on how to
model data by two experienced and competent
analysts.?(Biometrics , September 2009)