1.1 Plan of the 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 Gaussian 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 Non-Stationary 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 in Geostatistics.

10.1 Decision Making in Presence of Uncertainty.

10.2 Trend Model Construction.

10.3 Multiple Point Statistics.

11. Closing Remarks.

Bibliography.

Index.