Mineral Resource Estimation

<p>1  Introduction</p><p>1.1  Objectives and Approach</p><p>1.2  Scope of Resource Modeling</p><p>1.3  Critical Aspects</p><p>1.4  Historical Perspective</p><p>1.5 References</p><p> </p><p>2  Statistical Tools and Concepts</p><p>2.1  Basic Concepts</p><p>2.2  Probability Distributions</p><p>2.3  Spatial Data Analysis</p><p>2.4  Gaussian Distribution and Data Transformations</p><p>2.5  Data Integration and Inference</p><p>2.6  Exercises</p><p>2.7 References</p><p> </p><p>3  Geological Controls and Block Modeling</p><p>3.1  Geological and Mineralization Controls</p><p>3.2  Geologic Interpretation and Modeling</p><p>3.3  Visualization</p><p>3.4  Block Model Setup and Geometry</p><p>3.5  Summary of Minimum, Good and Best Practices</p><p>3.6  Exercises</p><p>3.7 References</p><p> </p><p>4  Definition of Estimation Domains</p><p>4.1  Estimation Domains</p><p>4.2  Defining the Estimation Domains</p><p>4.3  Case Study: Estimation Domains Definition for the Escondida Mine</p><p>4.4  Boundaries and Trends</p><p>4.5  Uncertainties Related to Estimation Domain Definition</p><p>4.6  Summary of Minimum, Good and Best Practices</p><p>4.7  Exercises</p><p>4.8 References</p><p> </p><p>5  Data Collection and Handling</p><p>5.1  Data</p><p>5.2  Basics of Sampling Theory</p><p>5.3  Sampling Quality Assurance and Quality Control</p><p> 5.4  Variables and Data Types</p><p>5.5  Compositing and Outliers</p><p>5.6  Density Determinations</p><p>5.7  Geometallurgical Data</p><p>5.8  Summary of Minimum, Good and Best Practices</p><p>5.9  Exercises</p><p>5.10 References</p><p> </p><p>6  Spatial Continuity</p><p>6.1  Concepts</p><p>6.2  Experimental Variograms and Exploratory Analysis</p><p>6.3  Modeling 3-D Variograms</p><p>6.4  Multivariate Case</p><p>6.5  Summary of Minimum, Good and Best Practices</p><p>6.6  Exercises</p><p>6.7 References</p><p> </p><p>7  Mining Dilution</p><p>7.1  Recoverable vs. In-Situ Resources</p><p>7.2  Types of Dilution and Ore Loss</p><p>7.3  Volume-Variance Correction</p><p>7.4  Information Effect</p><p>7.5  Summary of Minimum, Good and Best Practices</p><p>7.6  Exercises</p><p>7.7 References</p><p> </p><p>8  Recoverable Resources: Estimation</p><p>8.1  Goals and Purpose of Estimation</p><p>8.2  Kriging Estimators</p><p>8.3  CoKriging</p><p>8.4  Block Kriging</p><p>8.5  Kriging Plans</p><p>8.6  Summary of Minimum, Good and Best Practices</p><p>8.7  Exercises</p><p>8.8 References</p><p> </p><p>9  Recoverable Resources: Probabilistic Estimation</p><p>9.1  Conditional Distributions</p><p>9.2  Gaussian-based Kriging Methods</p><p>9.3  Indicator Kriging</p><p>9.4  Summary of Minimum, Good and Best Practices</p>9.5  Exercises</p><p>9.6 References</p><p> </p><p>10  Recoverable Resources: Simulation</p><p>10.1  Simulation versus Estimation</p><p>10.2  Continuous Variables: Gaussian-based Simulation</p><p>10.3  Continuous Variables: Indicator-based Simulation</p><p>10.4  Simulated Annealing</p><p>10.5  Simulating Categorical Variables</p><p>10.6  Co-simulation: Using Secondary Information and Joint Conditional Simulations</p><p>10.7  Post Processing Simulated Realizations</p><p>10.8  Summary of Minimum, Good and Best Practices</p><p>10.9  Exercises</p><p>10.10 Reference</p><p> </p><p>11  Resource Model Validations and Reconciliations</p><p>11.1  The Need for Checking and Validating the Resource Model</p><p>11.2  Resource Model Integrity</p><p>11.3  Resampling</p><p>11.4  Resource Model Validation</p><p>11.5  Comparisons with Prior and Alternate Models</p><p>11.6  Reconciliations</p><p>11.7  Summary of Minimum, Good and Best Practices</p><p>11.8  Exercises</p><p>11.9 References</p><p> </p><p>12  Uncertainty and Risk</p><p>12.1  Models of Uncertainty</p><p>12.2  Assessment of Risk</p><p>12.3  Resource Classification and Reporting Standards</p><p>12.4  Summary of Minimum, Good and Best Practices</p><p>12.5  Exercises</p><p>12.6 References</p><p> </p><p>13  Short Term Models</p><p>13.1  Limitations of Long-term Models for Medium-term Planning</p><p>13.2  Medium- and Short-term Modeling</p><p>13.3  Selection of Ore and Waste</p><p>13.4  Selection of Ore and Waste: Simulation-based Methods</p><p>13.5  Practical and Operational Aspects of Grade Control</p><p>13.6  Summary of Minimum, Good and Best Practices</p><p>13.7  Exercises</p><p>13.8 References</p><p> </p><p>14  Case Studies</p><p>14.1  The 2003 Cerro Colorado Resource Model</p><p>14.2  Multiple Indicator Kriging: São Francisco Gold Deposit</p><p>14.3  Modeling Escondida Norte’s Oxide Units with Indicators</p><p>14.4  Multivariate Geostatistical Simulation at Red Dog Mine</p><p>14.5  Uncertainty Models and Resource Classification: The Michilla Mine Case Study</p><p>14.6  Grade Control at the San Cristóbal Mine</p><p>14.7 Geometallurgical Modeling at Olympic Dam, South Australia</p><p>14.8 References</p><p> </p><p>15  Conclusions</p><p>15.1  Building a Mineral Resource Model</p><p>15.2  Assumptions and Limitations of the Models Used</p><p>15.3  Documentation and Audit Trail Required</p><p>15.4  Future Trends</p><p>15.5 References</p><p> </p><p>Index</p>