Value of geologically derived features in machine learning facies classification

DOI10.1007/S11004-019-09838-0zbMath1428.86024OpenAlexW2985504740MaRDI QIDQ2284090

Vasily Demyanov, Julie Halotel, Andy Gardiner

Publication date: 14 January 2020

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-019-09838-0

zbMATH Keywords

machine learningrandom forestsupport vector machinelithofacies

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Geostatistics (86A32)

Related Items (1)

Diagenetic facies classification in the Arbuckle formation using deep neural networks

Cites Work

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• Support-vector networks
• An Introduction to Statistical Learning
• The elements of statistical learning. Data mining, inference, and prediction
• Random forests

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