Home Isatis for resource classification and confidence intervals

## Isatis for resource classification and confidence intervals

Classification of the resources in different categories, measured, inferred, or indicated, implies reliable calculations of the confidence level in the grade estimates, at a local scale (SMU) and at greater scales (quaterly or yearly exploitation areas).
ISATIS provides several tools to calculate reliable and realistic Confidence Intervals of these different estimates. Among them, the exclusive and rapid application Confidence Intervals.

The kriging variance is certainly not the best way to classify your deposit’s resources. There are two main reasons for this. The error distribution is unlikely to be gaussian and the kriging variance is data-independent (though greater uncertainty is expected in high grade areas than in low ones). The distribution of mining data is, by nature, skewed; standard linear Confidence Intervals are, consequently, not relevant since they are not consistent with the data.

A better approach would be to obtain the error distributions from simulations. But this is extremely time-consuming, only to get two numerical values. A shortcut involving similar hypothesis is proposed in Isatis.

This original methodology was first applied in 1996 by Roth and Armstrong (from the Centre of Geostatistics of the “Ecole des Mines de Paris”) on gold grades of the Witwatersrand basin.

A more recent application has been succesfully made by Rio Tinto and has reduced drastically the time required for updating reserve classifications.

The basic idea is to use the Discrete Gaussian Model to calculate the Confidence Intervals directly from the gaussian grade estimates.

The figures above compare these Confidence Intervals to standard linear Confidence Intervals and to those derived from stochastic simulations.

### training

Geostatistics for Geophysicists

November 25 - 29, 2013

November 25 - 29, 2013

February 17 - 21, 2014

March 3 - 7, 2014

March 24 - 28, 2014

Learn how to enhance the quality of your seismic data to get consistent and reliable velocity volumes - 5-day course.

Isatis Essentials for Oil and Gas

December 16 - 18, 2013

January 13 - 15, 2014

Gain the skills you need to start using Isatis with confidence - 3-day course.

Reservoir Characterization

January 20 - 24, 2014

January 27 - 31, 2014

February 24 - 28, 2014

Learn the state-of-the art in property and geological facies modeling using the stochastic simulations for reliable and accurate assessment of uncertainties - 5-day course.

Geostatistical Gridding

February 10 - 12, 2014

Learn how performing insightful data geostatistical analysis provides accurate and reliable solutions for geology or property mapping - 3-day course.

Fundamentals of Oil & Gas Geostatistics

February 17 - 21, 2014

Get a comprehensive overview of commonly geostatistical methods applied to geophysical and geomodeling workflows, from seismic data QC to reservoir characterization - 5-day course

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Conference: Capturing Uncertainty in Geomodels - Best Practices and Pitfalls

December 11 - 12, 2013

Geovariances' consultant Renaud Meunier is giving a paper: "Model-derived uncertainties or uncertainty about models?". Be there to find out more about the importance of the model uncertainty quantification according to the reservoir study stag

Webinar Isatis:
A reliable geostatistical software for a reliable resource estimation

December 12, 2013