Because recent books focus on historical methods or details of geostatistical theory, there is a growing need to collect and synthesize the practice of modern mineral resource estimation into a book for undergraduate students, beginning graduate students, and young geologists and engineers. This comprehensive textbook and reference fills this need. It is especially fruitful that the book is written by authors with years of relevant experience performing mineral resource estimation and with years of relevant teaching experience.
Because recent books focus on historical methods or details of geostatistical theory, there is a growing need to collect and synthesize the practice of modern mineral resource estimation into a book for undergraduate students, beginning graduate students, and young geologists and engineers. This comprehensive textbook and reference fills this need. It is especially fruitful that the book is written by authors with years of relevant experience performing mineral resource estimation and with years of relevant teaching experience.
Zusammenfassung
Because recent books focus on historical methods or details of geostatistical theory, there is a growing need to collect and synthesize the practice of modern mineral resource estimation into a book for undergraduate students, beginning graduate students, and young geologists and engineers. This comprehensive textbook and reference fills this need. It is especially fruitful that the book is written by authors with years of relevant experience performing mineral resource estimation and with years of relevant teaching experience.
Inhaltsverzeichnis
1 Introduction1.1 Objectives and Approach1.2 Scope of Resource Modeling1.3 Critical Aspects1.4 Historical Perspective1.5 References 2 Statistical Tools and Concepts2.1 Basic Concepts2.2 Probability Distributions2.3 Spatial Data Analysis2.4 Gaussian Distribution and Data Transformations2.5 Data Integration and Inference2.6 Exercises2.7 References 3 Geological Controls and Block Modeling3.1 Geological and Mineralization Controls3.2 Geologic Interpretation and Modeling3.3 Visualization3.4 Block Model Setup and Geometry3.5 Summary of Minimum, Good and Best Practices3.6 Exercises3.7 References 4 Definition of Estimation Domains4.1 Estimation Domains4.2 Defining the Estimation Domains4.3 Case Study: Estimation Domains Definition for the Escondida Mine4.4 Boundaries and Trends4.5 Uncertainties Related to Estimation Domain Definition4.6 Summary of Minimum, Good and Best Practices4.7 Exercises4.8 References 5 Data Collection and Handling5.1 Data5.2 Basics of Sampling Theory5.3 Sampling Quality Assurance and Quality Control 5.4 Variables and Data Types5.5 Compositing and Outliers5.6 Density Determinations5.7 Geometallurgical Data5.8 Summary of Minimum, Good and Best Practices5.9 Exercises5.10 References 6 Spatial Continuity6.1 Concepts6.2 Experimental Variograms and Exploratory Analysis6.3 Modeling 3-D Variograms6.4 Multivariate Case6.5 Summary of Minimum, Good and Best Practices6.6 Exercises6.7 References 7 Mining Dilution7.1 Recoverable vs. In-Situ Resources7.2 Types of Dilution and Ore Loss7.3 Volume-Variance Correction7.4 Information Effect7.5 Summary of Minimum, Good and Best Practices7.6 Exercises7.7 References 8 Recoverable Resources: Estimation8.1 Goals and Purpose of Estimation8.2 Kriging Estimators8.3 CoKriging8.4 Block Kriging8.5 Kriging Plans8.6 Summary of Minimum, Good and Best Practices8.7 Exercises8.8 References 9 Recoverable Resources: Probabilistic Estimation9.1 Conditional Distributions9.2 Gaussian-based Kriging Methods9.3 Indicator Kriging9.4 Summary of Minimum, Good and Best Practices9.5 Exercises9.6 References 10 Recoverable Resources: Simulation10.1 Simulation versus Estimation10.2 Continuous Variables: Gaussian-based Simulation10.3 Continuous Variables: Indicator-based Simulation10.4 Simulated Annealing10.5 Simulating Categorical Variables10.6 Co-simulation: Using Secondary Information and Joint Conditional Simulations10.7 Post Processing Simulated Realizations10.8 Summary of Minimum, Good and Best Practices10.9 Exercises10.10 Reference 11 Resource Model Validations and Reconciliations11.1 The Need for Checking and Validating the Resource Model11.2 Resource Model Integrity11.3 Resampling11.4 Resource Model Validation11.5 Comparisons with Prior and Alternate Models11.6 Reconciliations11.7 Summary of Minimum, Good and Best Practices11.8 Exercises11.9 References 12 Uncertainty and Risk12.1 Models of Uncertainty12.2 Assessment of Risk12.3 Resource Classification and Reporting Standards12.4 Summary of Minimum, Good and Best Practices12.5 Exercises12.6 References 13 Short Term Models13.1 Limitations of Long-term Models for Medium-term Planning13.2 Medium- and Short-term Modeling13.3 Selection of Ore and Waste13.4 Selection of Ore and Waste: Simulation-based Methods13.5 Practical and Operational Aspects of Grade Control13.6 Summary of Minimum, Good and Best Practices13.7 Exercises13.8 References 14 Case Studies14.1 The 2003 Cerro Colorado Resource Model14.2 Multiple Indicator Kriging: São Francisco Gold Deposit14.3 Modeling Escondida Norte¿s Oxide Units with Indicators14.4 Multivariate Geostatistical Simulation at Red Dog Mine14.5 Uncertainty Models and Resource Classification: The Michilla Mine Case Study14.6 Grade Control at the San Cristóbal Mine14.7 Geometallurgical Modeling at Olympic Dam, South Australia14.8 References 15 Conclusions15.1 Building a Mineral Resource Model15.2 Assumptions and Limitations of the Models Used15.3 Documentation and Audit Trail Required15.4 Future Trends15.5 References Index
