Unmasking the Hidden Threat: Conductive Under-Deposits and Their Role in Preferential Weldment Corrosion of Carbon Steel under Sour Conditions

This work incorporates precorrosion conditioning and conductive deposits (FeS or FeS<sub>2</sub>) to explore corrosion mechanisms across base metal (BM), weld metal (WM), and heat-affected zone (HAZ) regions under simulated sour conditions (NaCl (3.5 wt %), Na<sub>2</sub>S<sub>2</sub>O<sub>3</sub> (1000 ppm), CH<sub>3</sub>COOH (100 ppm), CO<sub>2</sub>, 60 °C, pH ∼ 4, and 1000 rpm). Electrochemical studies demonstrated various corrosion rates (CR) hierarchies (CS-BM (0.34-0.42 mmpy) < CS-WM (0.38-0.73 mmpy) < CS-HAZ (0.48-1.75 mmpy)), which were exacerbated by FeS or FeS<sub>2</sub> deposition. This was ascribed to a variety of potential variations and localized acidification. Also, there were notable changes in the welded CS areas' compositions and microstructures both before and after corrosion testing. By creating protective layers that reduce microgalvanic interactions, the commercial amine-based inhibitor CRW11 (200 ppm) showed remarkable potency by lowering the CRs (<0.1 mmpy) threshold with inhibition efficiency (IE = >80%). Corrosion products (α-Fe<sup><sub>2</sub></sup>O<sub>3</sub>, γ-FeOOH, and Fe<sub>3</sub>O<sub>4</sub>) were most significant, identified by Raman spectroscopy. 1D artificial pit tests showed varied pit propagation dynamics, especially under FeS-induced heterogeneity, with CS-BM-FeS having the highest pit depth (71.4 ± 11.8 μm), but increased pit density (568.0 mm<sup>2</sup>) was recorded for CS-HAZ-FeS<sub>2</sub>. This proves the impact of conductive deposits on the pitting of welded CS regions. These findings corroborated deposit-induced electrochemical heterogeneity with localized attack, which was most significant with FeS<sub>2</sub> deposit. Machine learning (ML) models, like random forest (RF), decision tree (DT), and extreme gradient boost (XGBoost), demonstrated excellent IE predictive ability (<i>R</i><sup>2</sup> = 0.99) for welded CS without/with conductive deposits. However, RF and XGBoost are ideal with the least RMSE/MAE (0.2/0.2 and 0.1/0.1) for welded CS without/with FeS and FeS<sub>2</sub>, respectively. These results provide a practical foundation for pitting and PWC in preconditioned welded CS with conductive deposits, allowing for the best material selection and corrosion control techniques in sour service applications.

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Publication Details

Journal
Langmuir
Published
2025-08-27
DOI
https://doi.org/10.1021/acs.langmuir.5c02733
Citations
3
Primary Topic
Hydrogen embrittlement and corrosion behaviors in metals
Type
article
Field-Weighted Citation Impact
1.95

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article

Unmasking the Hidden Threat: Conductive Under-Deposits and Their Role in Preferential Weldment Corrosion of Carbon Steel under Sour Conditions

Mostafa H. Sliem, Dana Abdeen, Nicholas Laycock, Adewale K. Ipadeola et al.
3 citations
Langmuir
Hydrogen embrittlement and corrosion behaviors in metals
1.95
article

Unmasking the Hidden Threat: Conductive Under-Deposits and Their Role in Preferential Weldment Corrosion of Carbon Steel under Sour Conditions

Mostafa H. Sliem, Dana Abdeen, Nicholas Laycock, Adewale K. Ipadeola, Phaneendra K. Yalavarthy, Aboubakr M. Abdullah, Ashwin RajKumar
article en
3 citations

Abstract

This work incorporates precorrosion conditioning and conductive deposits (FeS or FeS<sub>2</sub>) to explore corrosion mechanisms across base metal (BM), weld metal (WM), and heat-affected zone (HAZ) regions under simulated sour conditions (NaCl (3.5 wt %), Na<sub>2</sub>S<sub>2</sub>O<sub>3</sub> (1000 ppm), CH<sub>3</sub>COOH (100 ppm), CO<sub>2</sub>, 60 °C, pH ∼ 4, and 1000 rpm). Electrochemical studies demonstrated various corrosion rates (CR) hierarchies (CS-BM (0.34-0.42 mmpy) < CS-WM (0.38-0.73 mmpy) < CS-HAZ (0.48-1.75 mmpy)), which were exacerbated by FeS or FeS<sub>2</sub> deposition. This was ascribed to a variety of potential variations and localized acidification. Also, there were notable changes in the welded CS areas' compositions and microstructures both before and after corrosion testing. By creating protective layers that reduce microgalvanic interactions, the commercial amine-based inhibitor CRW11 (200 ppm) showed remarkable potency by lowering the CRs (<0.1 mmpy) threshold with inhibition efficiency (IE = >80%). Corrosion products (α-Fe<sup><sub>2</sub></sup>O<sub>3</sub>, γ-FeOOH, and Fe<sub>3</sub>O<sub>4</sub>) were most significant, identified by Raman spectroscopy. 1D artificial pit tests showed varied pit propagation dynamics, especially under FeS-induced heterogeneity, with CS-BM-FeS having the highest pit depth (71.4 ± 11.8 μm), but increased pit density (568.0 mm<sup>2</sup>) was recorded for CS-HAZ-FeS<sub>2</sub>. This proves the impact of conductive deposits on the pitting of welded CS regions. These findings corroborated deposit-induced electrochemical heterogeneity with localized attack, which was most significant with FeS<sub>2</sub> deposit. Machine learning (ML) models, like random forest (RF), decision tree (DT), and extreme gradient boost (XGBoost), demonstrated excellent IE predictive ability (<i>R</i><sup>2</sup> = 0.99) for welded CS without/with conductive deposits. However, RF and XGBoost are ideal with the least RMSE/MAE (0.2/0.2 and 0.1/0.1) for welded CS without/with FeS and FeS<sub>2</sub>, respectively. These results provide a practical foundation for pitting and PWC in preconditioned welded CS with conductive deposits, allowing for the best material selection and corrosion control techniques in sour service applications.

LangmuirVol. 41(35)
Shell (Qatar) (QA), Qatar University (QA)
Qatar Shell Research and Technology Center, Qatar National Research Fund
Openalex Percentile: Top 15%
Hydrogen embrittlement and corrosion behaviors in metals
1.95
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