MINING GEOSTATISTICS SHORT COURSE:

New Info:

Participants will receive a CD with all necessary material and a free copy of Practical Geostatistics 2000 (retail value $US60).

Kriging is the name given to a particular group of techniques which model spatial processes and allow estimation of values at unsampled locations. In mining, geostatistics is extensively used in the field of reserve valuation - the estimation of grades and other parameters from a relatively small set of borehole or other samples. Originally developed in mining, geostatistics is now widely used in many other fields. Obviously there are geological and geographical applications. However, the techniques are also used in such diverse fields as hydrology, ground water and air pollution, soil science and agriculture, forestry, epidemiology and weather prediction.

About the course:
This course is aimed at any professionals dealing with the estimation from or interpolation between samples collected on a spatial basis.
No prior knowledge of statistics or geostatistics is assumed. A minimum of mathematics is necessary to explain the techniques - mainly simple algebra, up to the concepts of solving simple sets of simultaneous equations and differentiating x² Questions and discussions are actively encouraged and, indeed, form the basis of a successful course.

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For Whom is this Course Designed & Why?

This is not a course for specialist geostatisticians but intended rather for those who wish to enhance thier practical applications or research.

Course Topics Include:

• Basic assumptions of spatial estimation methods
• Statistical methods
• Geostatistical methods
• Geostatistical estimation
• Variations on kriging

Learn:

• Decision making in presence of uncertainty
• Kriging for optimal estimation of resources
• Multivariate modeling
• Variograms for spatial continuity modeling
• Simulation for uncertainty quantification

Day 1

Introduction to Geostokos Software, tutorial exercises on statistical and geostatistical analysis using datasets from Geostatistics Practical 2000

Day 2

Construction and interpretation of semi-variograms and choice of appropriate kriging techniques

Day 3

Case studies from Geostokos Ltd, general discussion of case studies and simulation techniques

Day 4

Bring your own data for geostatistical evaluation for geostatistical estimation using weighted averages, confidence levels, ordinary and simple kriging and cross validation

Day 5

Variations on kriging; lognormal methods, indicator methods, non-linear geostatistics, regression problems(continual bias); simulation