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SPE Data Science Convention

April 04, 2019
Norris Convention Center
Houston, Texas
Emerson E&P Software is proud to be a gold sponsor of the SPE Data Science Convention, to be held in Houston, April 4.  The convention focus will be, "Transforming the Upstream Oil & Gas Industry with Advanced Data Science Solutions".  

The convention is intended for Upstream Oil & Gas professionals, academia scholars and students with interests in emerging data science, machine learning and artificial intelligence applications. The agenda will include presentations from leading professionals to showcase their recent advancements and applications of Data Sciences.

For more information about the Convention, click here.

Florian Basier, Senior R&D Product Developer at Emerson E&P Software, will present a paper, "Limitations of Naïve Machine Learning Approaches in Geosciences: The Example of Grain Size Prediction from Microresistivity Logs".


The growing adoption of Machine Learning in subsurface studies often naively re-uses existing “real world” architecture or pre-trained networks that are then retrained for a new task. While this is an efficient way to validate the applicability of an architecture to a task, there are often obstacles to producing a network of commercially acceptable quality. Such obstacles, and the need to design customized solutions for the G&G industry, are illustrated by the prediction of Grain Size from microresistivity image logs.

Florian_Basier_sm.jpgFlorian Basier works as a Senior R&D Product Developer in Emerson E&P Software Houston, assisting several teams with their Machine Learning needs. He has 10 years of experience in exploration and production, focusing mainly on modeling and automation. Before joining Paradigm in 2015, Florian worked for several E&P companies in France (Techsia, Total) and the US (Chevron, INT). He holds a MSc degree in Geomodeling and Computer Sciences from the National Superior School of Geology (ENSG) of Nancy, France, as well as a MSc degree in Petroleum Engineering from the National Polytechnics Institute of Lorraine (INPL) from Nancy, France.