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    • ISSN: 2010-0221 (Print)
    • Abbreviated Title: Int. J. Chem. Eng. Appl.
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    • DOI: 10.18178/IJCEA
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Editor-in-chief
Prof. Dr. Shen-Ming Chen
National Taipei University of Technology, Taiwan
 

IJCEA 2025 Vol.16(2): 86-92
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 and Xingyu Peng*
Southwest Petroleum University, Chengdu, Si Chuan, China
Email: 2158140050@qq.com (Q.G.); pengxy1949@163.com (X.Y.P.)
*Corresponding author

Manuscript received April 23, 2025; accepted June 3, 2025; published August 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 

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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.

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