Basic Linear Geostatistics

摘要: 1 Introduction.- 1.1 Summary.- 1.2 1.3 Applications of geostatistics in mining.- 1.3.1 Estimating the total reserves.- 1.3.2 Error estimates.- 1.3.3 Optimal sample (or drillhole) spacing.- 1.3.4 block 1.3.5 Gridding and contour mapping.- 1.3.6 Simulating a deposit to evaluate proposed mine plan.- 1.3.7 recovery.- 1.4 The $64 question: does work?.- 1.5 Introductory exercise.- 1.5.1 Selective 1.5.2 1.5.3 Information effect.- 1.5.4 Support 1.6 Does work real world?.- 1.6.1 Early coal case studies.- 1.6.2 Gold 1.6.3 More recent 1.7 Exercises.- 2 Regionalized Variables.- 2.1 2.2 Modelling regionalized variables.- 2.3 Random functions.- 2.4 Stationary intrinsic hypotheses.- 2.5 How decide whether variable is stationary.- 2.6 Spatial covariance function.- 2.7 3 Variogram.- 3.1 3.2 Definition variogram.- 3.3 Range zone influence.- 3.4 Behaviour near origin.- 3.5 Anisotropies.- 3.5.1 Geometric anisotropy.- 3.5.2 Zonal stratified) 3.6 Presence drift.- 3.7 Nested structures.- 3.8 Proportional 3.9 Hole effects periodicity.- 3.10 Models for variograms.- 3.10.1 Variance admissible linear combinations.- 3.11 Admissible models.- 3.12 Common variogram 3.12.1 Nugget 3.12.2 Spherical model.- 3.12.3 Exponential 3.12.4 Power 3.12.5 Gaussian 3.12.6 Cubic 3.12.7 2D hole effect 3.12.8 Cardinal sine 3.12.9 Prismato-magnetic 3.12.10 Prismato-gravimetric 3.13 Simulated images obtained using different 3.14 4 Experimental Variograms.- 4.1 4.2 calculate experimental 4.3 In plane.- 4.4 three dimensions.- 4.5 Example 1: regular 1D data.- 4.6 2: calculating variograms 2D.- 4.7 Variogram cloud.- 4.8 Fitting 4.9 Troublesome 4.9.1 Outliers.- 4.9.2 Pseudo-periodic hiccups.- 4.9.3 Artefacts.- 4.10 5 Structural Analysis.- 5.1 5.2 Steps study.- 5.2.1 Step Collect check 5.2.2 decisions be made.- 5.2.3 Standard statistics.- 5.3 Case 5.4 An iron ore deposit.- 5.4.1 Vertical 5.4.2 5.4.3 model vertical 5.4.4 Horizontal 5.4.5 3D 5.5 Second study: an archaean gold (M. Harley).- 5.6 Third Witwatersrand Thurston).- 6 Dispersion as Function Block Size.- 6.1 6.2 support variable.- 6.2.1 versus size.- 6.3 point within volume.- 6.4 v V.- 6.5 Krige's additivity relation.- 6.6 Exercise: stockpiles homogenize production.- 6.6.1 Solution.- 6.7 Change support: regularization.- 6.8 regularized 6.8.1 6.9 7 Theory Kriging.- 7.1 7.2 purpose kriging.- 7.3 Deriving kriging equations.- 7.4 Different estimators.- 7.5 Ordinary 7.6 OK equations 7.7 block.- 7.7.1 7.8 Kriging value mean.- 7.9 Simple 7.10 theorem.- 7.11 Slope regression.- 7.12 exact interpolator.- 7.13 exercise showing minimization procedure.- 7.13.1 Quadratic form minimized.- 7.14 8 Practical Aspects 8.1 8.2 8.3 Negative weights.- 8.4 choice affects 8.4.1 Similar looking 8.4.2 nugget 8.5 Screen 8.6 Symmetry 8.7 Testing quality configuration.- 8.7.1 Example: Adding extra samples improves estimate.- 8.8 Cross-validation.- 9 Study 9.1 9.2 Iron 9.2.1 Grid size 9.3 Point large neighbourhood.- 9.4 9.5 smaller neighbourhoods.- 9.5.1 What causing ugly concentration lines?.- 9.5.2 eliminate these concentrations lines.- 9.6 small blocks from sparse grid.- 9.6.1 can kriged?.- 10 Total Reserves.- 10.1 10.2 Can used estimate global reserves?.- 10.3 Extension variance.- 10.4 Relationship dispersion 10.5 Area known mineralized.- 10.5.1 Direct composition terms.- 10.5.2 Composition by line slice 10.6 When limits orebody are not priori.- 10.7 sampling grids.- 10.7.1 Forthe 1km 10.7.2 For 500m 10.8 Appendix Review Basic Maths Concepts.- A1 maths skills required geostatistics.- A1.1 Means variances.- A1.2 Single double summations.- A1.3 Exercises Due Diligence its Implications.- A2.1 Stricter controls on evaluation.- A2.2 diligence.- A2.3 logbook.- References.- Author Index.