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 Cased Hole Product Champion, Ross Brackenridge for this show and tell of the Cased Hole data analysis capabilities within our industry-leading Subsurface log data interpretation software, Interactive Petrophysics (IP).
• Overview of how our wide range of cased hole modules can be used to interpret all data types throughout the whole lifecycle of the well - in one package.
• No need for separate software packages to analyze open hole and cased hole data.
• IP's cased hole suite of tools includes Casing and Cement Evaluation, Production Logging, Pulsed Neutron, Carbon-Oxygen and much more.
A core member of the Geoactive team with over 28 years of oil and gas experience, Ross is the technical champion for Interactive Petrophysics (IP). Having previously project managed the creation of a whole new suite of Cased Hole applications which focus on the mature wells market, Ross also holds the role of Technical Manager for our IP product, which sees him co-ordinate a technical team of IP experts.
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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