Addressing Diverse Petroleum Industry Problems Using Machine Learning Techniques: Literary Methodology─Spotlight on Predicting Well Integrity Failures-Reference-Cited by-同舟云学术

Addressing Diverse Petroleum Industry Problems Using Machine Learning Techniques: Literary Methodology─Spotlight on Predicting Well Integrity Failures

Published:2022-01-07 Issue:3 Volume:7 Page:2504-2519
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Salem Adel M.¹,Yakoot Mostafa S.²,Mahmoud Omar³^ORCID

Affiliation:

1. Suez University, Suez 43511, Egypt

2. Gulf of Suez Petroleum Co. (GUPCO), Cairo 11511, Egypt

3. Future University in Egypt (FUE), New Cairo 11835, Egypt

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c05658

Reference108 articles.

1. Well integrity management in mature fields: a state-of-the-art review on the system structure and maturity

2. bYakoot, M. S.; Elgibaly, A. A.; Ragab, A. M. S.; Mahmoud, O. A Comprehensive Review and Analysis of Maturity Model for Well Integrity in Brownfield. IADC Drilling Middle East 2020 Conference & Exhibition (Virtual), 2020; https://www.iadc.org/wp-content/uploads/2020/12/ME20-Mostafa-Yakoot.pdf (accessed 2022-01-06).

3. Data as an asset: What the oil and gas sector can learn from other industries about “Big Data”

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