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Multivariate simulation workflow
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Classroom Contents
Drillhole Spacing Analysis Using Simulated Information for Grade Control Optimization
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- 1 Drillhole Spacing analysis using simulated information. What is the optimum drill spacing for grade control?
- 2 Why is DHSA drillhole spacing analysis important? Drilling for grade control, minimise the drilling cost to achieve indicated resources
- 3 The principles of value optimisation: revenue, planned mining cost, ore loss, dilution
- 4 The consequences of misclassification - one model: drilling cost and opportunity cost
- 5 Why simulation? Histogram, variogram, equiprobable outcomes
- 6 What is a multivariate simulation MVS? Iron, silica, manganese, alumina, phosphorus
- 7 Multiple drilling grids from a simulation
- 8 Case study - Copper-nickel mineralisation
- 9 Multivariate simulation workflow
- 10 Simulation - Raw data inputs
- 11 Simulation - Gaussianisation
- 12 Simulation - Scatterplot of simulated factors
- 13 Simulation - Reproduction of sample histograms
- 14 Simulation resampling - Chosen realisation
- 15 Simulation resampling - Pseudo drillholes
- 16 Post-processing of OK models and value comparison
- 17 Misclassification maps - Example
- 18 Results - Drilling cost difference for various grids
- 19 Results - Misclassification example
- 20 Results - Drilling revenue to a drilling pattern
