Mineral Resource Estimation (Hardcover)

1 Introduction 1.1 Objectives and Approach 1.2 Scope of Resource Modeling 1.3 Critical Aspects 1.4 Historical Perspective 1.5 References 2 Statistical Tools and Concepts 2.1 Basic Concepts 2.2 Probability Distributions 2.3 Spatial Data Analysis 2.4 Gaussian Distribution and Data Transformations 2.5 Data Integration and Inference 2.6 Exercises 2.7 References 3 Geological Controls and Block Modeling 3.1 Geological and Mineralization Controls 3.2 Geologic Interpretation and Modeling 3.3 Visualization 3.4 Block Model Setup and Geometry 3.5 Summary of Minimum, Good and Best Practices 3.6 Exercises 3.7 References 4 Definition of Estimation Domains 4.1 Estimation Domains 4.2 Defining the Estimation Domains 4.3 Case Study: Estimation Domains Definition for the Escondida Mine 4.4 Boundaries and Trends 4.5 Uncertainties Related to Estimation Domain Definition 4.6 Summary of Minimum, Good and Best Practices 4.7 Exercises 4.8 References 5 Data Collection and Handling 5.1 Data 5.2 Basics of Sampling Theory 5.3 Sampling Quality Assurance and Quality Control 5.4 Variables and Data Types 5.5 Compositing and Outliers 5.6 Density Determinations 5.7 Geometallurgical Data 5.8 Summary of Minimum, Good and Best Practices 5.9 Exercises 5.10 References 6 Spatial Continuity 6.1 Concepts 6.2 Experimental Variograms and Exploratory Analysis 6.3 Modeling 3-D Variograms 6.4 Multivariate Case 6.5 Summary of Minimum, Good and Best Practices 6.6 Exercises 6.7 References 7 Mining Dilution 7.1 Recoverable vs. In-Situ Resources 7.2 Types of Dilution and Ore Loss 7.3 Volume-Variance Correction 7.4 Information Effect 7.5 Summary of Minimum, Good and Best Practices 7.6 Exercises 7.7 References 8 Recoverable Resources: Estimation 8.1 Goals and Purpose of Estimation 8.2 Kriging Estimators 8.3 CoKriging 8.4 Block Kriging 8.5 Kriging Plans 8.6 Summary of Minimum, Good and Best Practices 8.7 Exercises 8.8 References 9 Recoverable Resources: Probabilistic Estimation 9.1 Conditional Distributions 9.2 Gaussian-based Kriging Methods 9.3 Indicator Kriging 9.4 Summary of Minimum, Good and Best Practices 9.5 Exercises 9.6 References 10 Recoverable Resources: Simulation 10.1 Simulation versus Estimation 10.2 Continuous Variables: Gaussian-based Simulation 10.3 Continuous Variables: Indicator-based Simulation 10.4 Simulated Annealing 10.5 Simulating Categorical Variables 10.6 Co-simulation: Using Secondary Information and Joint Conditional Simulations 10.7 Post Processing Simulated Realizations 10.8 Summary of Minimum, Good and Best Practices 10.9 Exercises 10.10 Reference 11 Resource Model Validations and Reconciliations 11.1 The Need for Checking and Validating the Resource Model 11.2 Resource Model Integrity 11.3 Resampling 11.4 Resource Model Validation 11.5 Comparisons with Prior and Alternate Models 11.6 Reconciliations 11.7 Summary of Minimum, Good and Best Practices 11.8 Exercises 11.9 References 12 Uncertainty and Risk 12.1 Models of Uncertainty 12.2 Assessment of Risk 12.3 Resource Classification and Reporting Standards 12.4 Summary of Minimum, Good and Best Practices 12.5 Exercises 12.6 References 13 Short Term Models 13.1 Limitations of Long-term Models for Medium-term Planning 13.2 Medium- and Short-term Modeling 13.3 Selection of Ore and Waste 13.4 Selection of Ore and Waste: Simulation-based Methods 13.5 Practical and Operational Aspects of Grade Control 13.6 Summary of Minimum, Good and Best Practices 13.7 Exercises 13.8 References 14 Case Studies 14.1 The 2003 Cerro Colorado Resource Model 14.2 Multiple Indicator Kriging: Sao Francisco Gold Deposit 14.3 Modeling Escondida Norte's Oxide Units with Indicators 14.4 Multivariat