IFPen/Collège de France EOR AI challenge

Students challenged to predict oil saturation from core imagery.

France’s IFP Energies Nouvelles R&D organization has teamed with the prestigious Collège de France (founded in 1530) on a machine learning challenge. The challenge involves predicting residual oil saturation in a porous media from a 500 sample labeled core dataset provided by IFPen.

Data science students are invited to demonstrate the application of statistical methods that best predict residual oil from the three-dimensional microstructure of a core. Sign up for the Challenge on the Collège de France website and or watch the video (both in French).

The IFPen 2018 Data Challenge is run by newly-elected professor of data science at the Collège de France, Stéphane Mallat.

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