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 IC Product Champion and Technical Operations Manager, Catriona Penman for a show and tell of how our Interactive Correlations (IC) software can help you conduct confident exploration activities in both new and old basins.
Integrating log data, core data, pressure and production data can lead to practical and efficient correlation and mapping across a region. Building a more complete interpretation of your subsurface can lead to more efficient and productive outcomes.
With more than 15 years’ experience, a BSc Hons, Geoscience from the University of St Andrews, and a MSc in Petroleum Geoscience from the University of Edinburgh, Catriona Penman leads our team of technical experts and is responsible for Geoactive’s Interactive Correlations (IC) Well Interpretation software. IC enables confident insight through powerful visualisations and her role includes ensuring the integration of subsurface and geological data management requirements within the capabilities of the software and futureproofing through development for an ever-changing market and evolving in line with customer and industry needs.
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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