Comparative machine learning facies prediction using ensemble boosting models and support vector machine versus unsupervised clustering

Abstract This study explores the application of machine learning for facies classification in complex sandstone formations with overlapping petrophysical features. Three boosting ensemble models, Random Forest, XGBoost and CatBoost, were compared with one non-ensemble supervised model, Support Vecto...

Volledige beschrijving

Bibliografische gegevens

Hoofdauteurs:	Muhammad Risha, Paul Liu
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Springer 2026-01-01
Reeks:	Discover Geoscience
Onderwerpen:	Facies classification Machine learning Geostatistics Synthetic data augmentation Ensemble models
Online toegang:	https://doi.org/10.1007/s44288-026-00398-5
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!