Alvaro Chaveste & Thomas Chaparro | Geophysical Insights | Webinar | 24-25 July 2024
Alvaro Chaveste and Thomas Chaparro unveiled a groundbreaking Machine Learning (ML) based methodology for Lithofacies Prediction. This new approach is faster than traditional seismic inversion techniques, leveraging the power of Self Organized Maps (SOM), an unsupervised form of machine learning. Using SOM, we can create detailed 3D volumes of classified data down to a sampling interval. These volumes are then combined with lithofacies from well logs, merging two independent data sources for more accurate predictions.