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Based on a postgraduate course that has been successfully taught for over 15 years, the underlying philosophy here is to give students an in-depth understanding of the relevant theory and how to put it into practice. This involves going into the theory in more detail than most books do, and also discussing its applications. It is assumed that readers, students and professionals alike are familiar with basic probability and statistics, as well as the matrix algebra needed for solving linear systems; however, some reminders on these are given in an appendix. Exercises are integrated throughout, and the appendix contains a review of the material.Linear Geostatistics covers basic geostatistics from the underlying statistical assumptions, the variogram calculation and modelling through to kriging. The underlying philosophy is to give the students an indepth understanding of the relevant theory and how to put it into practice. This means going into the theory in more detail than most books do, and also linking it with applications. It is assumed that readers, students and professionals alike, are familiar with basic probability and statistics, and matrix algebra needed for solving linear systems. Some reminders on these are given in an appendix at the end of the book. A set of exercises is integrated into the text.1 Introduction.- 1.1 Summary.- 1.2 Introduction.- 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 Estimating block reserves.- 1.3.5 Gridding and contour mapping.- 1.3.6 Simulating a deposit to evaluate a proposed mine plan.- 1.3.7 Estimating the recovery.- 1.4 The $64 question: does geostatistics work?.- 1.5 Introductory exercise.- 1.5.1 Selective mining.- 1.5.2 Optimal recovery.- 1.5.3 Information effect.- 1.5.4 Support effect.- 1.6 Does geostatistics work in the real world?.- 1.6.1 Early coal case studies.- 1.6.2 Gold case studies.- 1.6.3 More recentlÓ"
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