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Hybrid physics-machine learning models for predicting rate of penetration in the Halahatang oil field, Tarim Basin

Abstract Rate of penetration (ROP) is a key factor in drilling optimization, cost reduction and drilling cycle shortening. Due to the systematicity, complexity and uncertainty of drilling operations, however, it has always been a problem to establish a highly accurate and interpretable ROP predictio...

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Auteurs principaux: Shengjie Jiao, Wei Li, Zhuolun Li, Jingming Gai, Linhao Zou, Yinao Su
Format: Artigo
Langue:Inglês
Publié: Nature Portfolio 2024-03-01
Collection:Scientific Reports
Sujets:
Prediction of the rate of penetration
Physical model
Machine learning
Hybrid model
Accès en ligne:https://doi.org/10.1038/s41598-024-56640-y
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