The Importance of Feature Selection for Machine Learning in Petrophysics
When planning and building machine learning models, a question often asked is, “What features should I use as input to my model?”.
Join our resident Geomechanics Product Champion, Frans Mulders, for this show and tell of the Geomechanics capabilities within our industry-leading subsurface log data interpretation software, Interactive Petrophysics (IP).
• A short history of geomechanics - Geomechanics principles date as far back as the late 19th century and some excellent and fundamental developments have been made during the 20th century.
• Current Geomechanics awareness - as wells get longer, and reservoir structures are getting more complex and unconventional, the awareness of geomechanical awareness has understandably increased.
• Geomechanics in the Energy Transition and beyond - as the world's energy supply is moving towards sustainable and zero emissions resources, the trend of increasing geomechanical awareness and application is expected to continue.
A long-standing member of the Geoactive team, Frans is an experienced Senior Engineer with a demonstrated history of working in operations, applied and fundamental research, and consultancy in Europe and the Asia Pacific Region. With a PhD in Technical Geoscience from Delft University of Technology (Netherlands) and MSc in Geology / Engineering Geology from RWTH Aachen University (Germany), there isn't much Frans doesn't know about the application of Geomechanics in a subsurface environment.
When planning and building machine learning models, a question often asked is, “What features should I use as input to my model?”.
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