Predicting pressure losses in the water-assisted flow of unconventional crude with machine learning-Reference-Cited by-同舟云学术

Predicting pressure losses in the water-assisted flow of unconventional crude with machine learning

Published:2021-09-25 Issue:21-22 Volume:39 Page:926-943
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Rushd Sayeed¹^ORCID,Rahman Moklesur²,Arifuzzaman Md³,Ali Sherif Abdulbari⁴,Shalabi Faisal³,Aktaruzzaman Md⁵

Affiliation:

1. Department of Chemical Engineering, King Faisal University, Al Ahsa, Saudi Arabia

2. Department of Computer Science and Engineering, The People’s University of Bangladesh, Dhaka, Bangladesh

3. Department of Civil Engineering, King Faisal University, Al Ahsa, Saudi Arabia

4. School of Chemical Engineering, Universiti Teknologi MARA, Shah Alam, Malaysia

5. Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2021.1980012

Reference25 articles.

1. Review of the Applications of Decision Tree Analysis in Petroleum Engineering with a Rigorous Analysis

2. Machine learning technique for the prediction of shear wave velocity using petrophysical logs

3. Application of ANN to the water-lubricated flow of non-conventional crude

4. A review of technologies for transporting heavy crude oil and bitumen via pipelines

5. Flow patterns and pressure gradient correlation for oil–water core–annular flow in horizontal pipes

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