Augustine Okechukwu Chukwuemeka
Multi-criteria decision-making approach to material selection for abandonment of high-pressure high-temperature (HPHT) wells exposed to harsh reservoir fluids.
Chukwuemeka, Augustine Okechukwu; Oluyemi, Gbenga; Mohammed, Auwalu I.; Attar, Suhail; Njuguna, James
Authors
Dr Gbenga Oluyemi g.f.oluyemi@rgu.ac.uk
Associate Professor
Auwalu I. Mohammed
Dr Suhail Attar s.attar@rgu.ac.uk
Lecturer
Professor James Njuguna j.njuguna@rgu.ac.uk
NSC Director of Research and Innovation
Abstract
Portland cement is the primary barrier material for well abandonment. However, the limitations of cement, especially under harsh downhole conditions, are necessitating research into alternative barrier materials. While several alternatives have been proposed, the screening process leading to their selection is scarcely discussed in the literature, resulting in the non-repeatability of the selection process. This study develops a dynamic multi-criteria decision-making technique for assessing the material options for the abandonment of high-pressure high-temperature (HPHT) wells with exposure to harsh reservoir fluids. The material screening process is performed in ANSYS Granta and a combined technique for order of preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) approach is used for ranking the shortlisted material alternatives based on seven material properties proven in the literature to be critical to the long-term integrity of well barrier materials. Nine alternative materials are ranked against Portland cement and high alumina cement. The results show that the top-ranking materials are from the phenol formaldehyde and polyamide–imide groups. Of these, the primary production CO2 of the polyamide–imide is, on average, about 25 times higher than the primary production CO2 of the phenol formaldehyde material. A sensitivity analysis of the methodology confirms that the criteria with the highest initial weights are the most impactful in terms of the final rank. The material property values also have an impact on the extent to which variations in their weights affect the hierarchical position of the materials in the TOPSIS-AHP analysis. Despite their higher cost per unit volume, the alternative materials consistently outperformed cement—even when average price was weighted more heavily than the most influential mechanical property.
Citation
CHUKWUEMEKA, A.O., OLUYEMI, G., MOHAMMED, A.I., ATTAR, S. and NJUGUNA, J. 2025. Multi-criteria decision-making approach to material selection for abandonment of high-pressure high-temperature (HPHT) wells exposed to harsh reservoir fluids. Polymers [online], 17(10), article number 1329. Available from: https://doi.org/10.3390/polym17101329
Journal Article Type | Article |
---|---|
Acceptance Date | May 7, 2025 |
Online Publication Date | May 13, 2025 |
Publication Date | May 31, 2025 |
Deposit Date | May 14, 2025 |
Publicly Available Date | May 14, 2025 |
Journal | Polymers |
Electronic ISSN | 2073-4360 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 17 |
Issue | 10 |
Article Number | 1329 |
DOI | https://doi.org/10.3390/polym17101329 |
Keywords | Polymer resins; Oil and gas wells; Well integrity; Decommissioning; Well abandonment; Plug and abandonment; Materials selection; Multi-criteria decision-making |
Public URL | https://rgu-repository.worktribe.com/output/2836285 |
Files
CHUKWUEMEKA 2025 Multi-criteria decision-making approach (VOR)
(2.9 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Assessment of polymer resins as alternative abandonment barrier materials for high pressure high temperature (HPHT) wells: a multi criteria decision making approach.
(2024)
Presentation / Conference Contribution
Transport of nanoparticles in porous media and associated environmental impact: a review.
(2024)
Journal Article
An artificial lift selection approach using machine learning: a case study in Sudan.
(2023)
Journal Article
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search