Field data analysis and risk assessment of gas kick during industrial deepwater drilling process based on supervised learning algorithm-Reference-Cited by-同舟云学术

Field data analysis and risk assessment of gas kick during industrial deepwater drilling process based on supervised learning algorithm

Published:2021-02 Issue: Volume:146 Page:312-328
ISSN:0957-5820
Container-title:Process Safety and Environmental Protection
language:en
Short-container-title:Process Safety and Environmental Protection

Author:

Yin Qishuai,Yang Jin,Tyagi Mayank^ORCID,Zhou Xu^ORCID,Hou Xinxin,Cao Bohan^ORCID

Funder

National Natural Science Foundation of China

National Major Science and Technology Projects of China

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,General Chemical Engineering,Environmental Chemistry,Environmental Engineering

Reference55 articles.

1. Hybrid particle swarm optimization with genetic algorithm to train artificial neural networks for short-term load forecasting;Abeyrathna;Int. J. Swarm Intelligence Research (IJSIR),2019

2. The Regression Tsetlin Machine: a Novel Approach to Interpretable Nonlinear Regression;Abeyrathna,2019

3. Monitoring Early Kick Indicators at the Bottom Hole for Blowout Prevention;Ayesha,2014

4. Drilling engineering;Azar,2007

5. Development and Application of a Real-Time Drilling State Classification Algorithm with Machine Learning. Unconventional Resources Technology Conference;Ben,2019

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