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...

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Ngā kaituhi matua:	Muhammad Risha, Paul Liu
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	Springer 2026-01-01
Rangatū:	Discover Geoscience
Ngā marau:	Facies classification Machine learning Geostatistics Synthetic data augmentation Ensemble models
Urunga tuihono:	https://doi.org/10.1007/s44288-026-00398-5
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!