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Bring Your Own data for Geostatistical evaluation - an advanced course for geostatistics
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Bring Your Own data for Geostatistical evaluation |
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WHO SHOULD ATTEND? This course allows participants to analyse their own data using the Geostokos Toolkit under supervision. The course is aimed at geologists, mining engineers,
surveyors, biologists, agriculturalists, statisticians, environmentalists and
any other professionals dealing with the estimation from or interpolation
between samples collected on a spatial basis. A basic level of knowledge of statistical and geostatistical methods is assumed. For example, previous participants in 'Zero to Kriging' will find this course eminently appealing. No mathematical expertise is necessary to carry out the analysis. All techniques are illustrated by exercises covering many different applications. Questions and discussions are actively encouraged and, indeed, form the basis of a successful course. Participants should, if possible, bring their own data for independent study. Basic computer skills and a familiarity with PC Windows systems are an advantage but not essential. Participants may take away copies of all software and data sets. |
COURSE OUTLINE Flexible! All sessions include a mixture of formal lecture, general discussion and hands on computer analysis. The timetable is flexible and is always adjusted to reflect the interests of the class participants. Day 1, morning: Introduction to Geostokos Software, Tutorial exercises on statistical and geostatistical analysis using the data sets from Practical Geostatistics 2000. Day 1, afternoon: Consideration of statistical distribution and its contribution to interpretation of sample data; identification of multiple components and likely indicator discriminators; lognormal and other distributions. Day 2, morning: Construction and interpretation of semi-variograms; identification of trends; multi-component models; confirmation of basic assumptions; outliers. Day 2, afternoon: Choice of appropriate kriging techniques; practical applications of kriging; confidence and standard errors. Day 3: Case studies from Geostokos Ltd and from course participants; general discussion of case studies; simulation techniques; multi-variable problems and co-kriging. |
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COURSE LEADER
Isobel Clark has taught, researched and consulted in the
field of geostatistics for almost 30 years. Possibly best known as the author
of the introductory text "Practical Geostatistics" (1979), she is
now co-author of a more complete textbook, Practical Geostatistics 2000
which is available as hypertext on CD and as a hardcopy
book. Software and data sets are available to all.
Short courses and seminars are offered on a regular
basis and, to date, have been hosted by companies and educational
institutions on four continents. Dr. Clark lectured for 11 years at the Royal
School of Mines, Imperial College, London, at the University of the Witwatersrand
in Johannesburg for 9 years and was Visiting
Professor at Camborne School of Mines for 2 years.
In between these academic engagements, she acts as Managing Director and senior partner of Geostokos (Ecosse) Limited, an international consultancy company based in Central Scotland.
Her recent consultancy assignments range from the evaluation of tantalite deposits in Mozambique to the study of protected sea-birds in the UK.
Geostatistics is the name given to a particular group of techniques which model spatial processes and allow estimation of values at unsampled locations. Geostatistical estimation is a two stage process:
i. studying the gathered data to establish the predictability of values from place to place in the study area;
ii. values at those locations which have not been sampled. This process "is known as 'kriging'.
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.
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, management of wildlife and weather prediction.