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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主要な著者:	Shengjie Jiao, Wei Li, Zhuolun Li, Jingming Gai, Linhao Zou, Yinao Su
フォーマット:	Artigo
言語:	Inglês
出版事項:	Nature Portfolio 2024-03-01
シリーズ:	Scientific Reports
主題:	Prediction of the rate of penetration Physical model Machine learning Hybrid model
オンライン･アクセス:	https://doi.org/10.1038/s41598-024-56640-y
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