doi: 10.18178/ijcea.2025.16.2.845
Research on SRB Corrosion Test Optimization and Internal Corrosion Rate Prediction Model for Shale Gas Gathering Pipeline
Qiwen Gong
,
Xingyu Peng*
- Southwest Petroleum University, Chengdu, Si Chuan, China
- Manuscript receivedApril 23, 2025
- acceptedJune 3, 2025
- publishedAugust 8, 2025
Abstract
Internal corrosion caused by Sulfate-Reducing Bacteria (SRB) poses a critical challenge to shale gas gathering pipelines. This study combines experimental analysis and a Bayesian network-based corrosion probability model to explore SRB corrosion mechanisms and predict corrosion rates. Experimental results demonstrate a direct correlation between SRB concentration and accelerated corrosion rates. The proposed Bayesian model integrates factors such as SRB concentration, temperature, flow rate, and pH, validated against field data with relative errors <35%. This research provides theoretical support for pipeline maintenance strategies.
Keywords
- shale gas pipeline
- SRB detection
- microbial corrosion
- bayesian network
How to Cite
Qiwen Gong and Xingyu Peng, "Research on SRB Corrosion Test Optimization and Internal Corrosion Rate Prediction Model for Shale Gas Gathering Pipeline," International Journal of Chemical Engineering and Applications, vol. 16, no. 2, pp. 86-92, 2025. https://doi.org/10.18178/ijcea.2025.16.2.845
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
