利用 CNN-LSTM 模型实时预测机械比能量，优化钻孔参数

IF 1.3 4区工程技术 Q4 ENERGY & FUELS

Petroleum Science and Technology Pub Date : 2024-08-05 DOI:10.1080/10916466.2024.2385727

Weiji Liu, Jiahao Feng, Xiaohua Zhu, Ke Li, Xinyv Shen, Xiaosong Wen

引用次数: 0

摘要

MSE 是钻井过程中的一个重要参数，因为它决定了钻井效率。因此，准确预测钻井过程中的 MSE 值，并实时调整钻井参数以提高钻井效率，是提高钻井效率的关键。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Real-time mechanical specific energy prediction for optimizing the drilling parameters using CNN-LSTM model

MSE is an important parameter in drilling process as it determines drilling efficiency. Therefore, accurately predicting the MSE during drilling and real-time adjusting the drilling parameters to e...

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来源期刊

Petroleum Science and Technology 工程技术-工程：化工

CiteScore

2.90

自引率

13.30%

发文量

277

审稿时长

2.7 months

期刊介绍： The international journal of Petroleum Science and Technology publishes original, high-quality peer-reviewed research and review articles that explore: -The fundamental science of fluid-fluid and rock-fluids interactions and multi-phase interfacial and transport phenomena through porous media related to advanced petroleum recovery processes, -The application of novel concepts and processes for enhancing recovery of subsurface energy resources in a carbon-sensitive manner, -Case studies of scaling up the laboratory research findings to field pilots and field-wide applications. -Other salient technological challenges facing the petroleum industry.