Artificial Neural Networks in Drilling Troubles Prediction (Russian)-Reference-Cited by-同舟云学术

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Artificial Neural Networks in Drilling Troubles Prediction (Russian)

Published:2014 Issue: Volume: Page:
ISSN:
Container-title:SPE Russian Oil and Gas Exploration & Production Technical Conference and Exhibition
language:
Short-container-title:

Author:

Lind Yuliya B.,Kabirova Aigul R.

Publisher

Society of Petroleum Engineers

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial neural network prediction of wellbore stability in offshore shallow formations;Geoenergy Science and Engineering;2024-09

2. Application of Artificial Neural Networks in Geoscience and Petroleum Industry;Artificial Intelligent Approaches in Petroleum Geosciences;2024

3. An Improved Transformer Framework for Well-Overflow Early Detection via Self-Supervised Learning;Energies;2022-11-22

4. A Well-Overflow Prediction Algorithm Based on Semi-Supervised Learning;Energies;2022-06-13

5. Early Stuck Pipe Sign Detection with Depth-Domain 3D Convolutional Neural Network Using Actual Drilling Data;SPE Journal;2020-12-14

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