Learn best practices in mining Geostatistics and become operational after a 5 week-course.

The Mining CFSG is a Specialized Training Cycle in Geostatistics (Cycle de Formation Spécialisée en Géostatistique). It covers key geostatistical concepts for block modeling and recoverable resource estimation, and goes beyond usual aspects addressing advanced issues such as extreme value and directionality management.

Why attending the Mining CFSG?

To learn, practice and return to work with a solid understanding of the theory and application of Geostatistics for resource estimation. Come with your data and leave with results.

To develop your geostatistics skills in only a few weeks
Quickly get the technical level required to build the block models that your company needs for confident mine planning. Expand your know-how by exploring original techniques.

To benefit from the label Ecole de Géostatistique de Fontainebleau
It means that you get the support of top-level Geostatisticians who gained their know-how from decades of experience working for major mining companies worldwide.

To connect with your pairs and trainers through networking evenings and discover a region of France during week-ends.

Why a new CFSG program?

Since 1979, the Cycle de Formation Spécialisée en Géostatistique (CFSG) has been a reference training program for the mining industry professionals to learn how to apply this set of concepts, tools, methods and practices incepted by Georges Matheron and his team in the 60’s – the prestigious Ecole de Géostatistique de Fontainebleau, a discipline which has spread all over the world.

After 40 years and 400 attendees from around the world, the CFSG format changes to better meet today’s needs of the mining industry. It is now reduced to 5 continuous weeks and attendees will develop a Professional Project all along this period. This project could typically be grade estimation for long or short-term mine planning block model.

Block Modeling at the heart of mining Geostatistics

Mining Geostatistics
A particular branch of spatial statistics – aims at predicting valuable quantities from partial information like grades measured or facies observed at samples along drillholes. The main issue is the block model, which guides the mining process throughout the mine life.

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