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Machine Learning in Geolog 18 – Utilizing Facimage and Python

September 18, 2018
This presentation is now available for viewing.

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Presented by:  Constantine Vavourakis, Team Lead Petrophysics Applications 
Featured Domain:  Formation Evaluation
Featured TechnologiesGeolog

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For comments or questions, please contact Constantine Vavourakis.


Abstract

Machine learning has been included for many years in Geolog software under the name of Facimage.  However, there have been many improvements in deep learning techniques in the past few years which have yet to be fully utilized in the realm of Petrophysics.  With the new Geolog 18 release, users can now process their well data using the Python language and take advantage of the tools that come with it, such as Scikit-Learn and Tensorflow.  This talk will cover what is currently available in Facimage and how to leverage Python to build custom machine learning tools in Geolog.

Biography

Constantine-Vavourakis1.jpegConstantine Vavourakis is a Petrophysics Team Lead at Emerson E&P Software.  He has a BS degree in Geological Sciences from the University of Texas at Austin and a MS degree in Petroleum Geology from the University of Houston.  He has more than 8 years’ experience in E&P as a Research Geologist, Exploration Geoscientist, and Petrophysicist.  He has recently been researching how advanced machine learning and deep learning techniques can be applied to optimize Formation Evaluation workflows.