Resource Classification

3 days

June 2-4, 2008 « Register
Lecturer: Jacques Deraisme
Venue: Geovariances offices in Avon (Paris area)
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OBJECTIVE

The course presents what is at stake in resources classification and assessment of the estimates uncertainty. The kriging variance is a convenient tool for comparing different sampling strategies, but it is not an appropriate tool for the derivation of a true confidence interval, because the kriging variance is not conditioned to the data. A better solution consists in computing many conditional simulations, but this is time consuming. To obtain a confidence interval, simple models, like the discrete gaussian model may be sufficient and give an acceptable answer for the purpose of resources classification.

KEY FEATURES

The course starts with a review of the main definitions of resources and reserves according to the standards as CIM or JORC. The limitations of the kriging variance is then discussed using simple examples. The change of support model available in the frame work of the gaussian discrete model is then detailed and applied on real 3D data for calculating confidence intervals. The interpretation of the results and their comparison with kriging variance and simulations is then discussed.

WHO SHOULD ATTEND

Managers, exploration geologists, mining engineers involved in feasibility studies or medium to long term planning. A good knowledge of geostatistics, including an understanding of non linear techniques (gaussian anamorphosis, simulations) is recommended.

COURSE CONTENT

Reminders on resources and reserves notions.
Concepts of variances calculated in geostatistics (dispersion variance, estimation variance).
The kriging variance and its properties.
Data distribution and kriging.
Gaussian based methods: normal score transformation using the anamorphosis function.
Change of support within the discrete gaussian model.
Calculation of the confidence intervals using the discrete gaussian model.
Geostatistical simulations for achieving the same tasks and comparison with the previous results.
Available tools for analysing the results.
Discussion on the limitations of the method and solutions.

Half of the course is dedicated to practical computer exercises, using Isatis, that reinforce the previously presented theoretical notions.

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Tailored courses may be organized on client demand. Please contact your sales representative to request more information.