Integrating Emerging Corrosion Monitoring and Mitigation Technologies for Onshore and Offshore Oilfield Assets

Nduwuba George Obinna; Enyioko Nzenwa Dan; Izuwa Nkemakolam Chinedu; Duru; Ugochukwu Ilozurike; Uwaezuoke Nnaemeka; Dike Chukwuebuka Francis; Okalla; Christian Emelu; Chidi Chiemezuo David

doi:10.56201/ijemt.vol.12.no10.2026.pg149.167

Integrating Emerging Corrosion Monitoring and Mitigation Technologies for Onshore and Offshore Oilfield Assets

Nduwuba George Obinna, Enyioko Nzenwa Dan, Izuwa Nkemakolam Chinedu, Duru, Ugochukwu Ilozurike, Uwaezuoke Nnaemeka, Dike Chukwuebuka Francis, Okalla, Christian Emelu, Chidi Chiemezuo David

Abstract

Corrosion remains a life-cycle integrity threat to onshore and offshore oilfield assets because water wetting, acid gases, oxygen ingress, deposits, microorganisms and hydrodynamic forces interact across changing operating conditions. This critical review integrates established corrosion chemistry and control with recent developments in networked sensing, distributed fibre-optic monitoring, robotics, interpretable machine learning, digital twins, self-healing coatings and advanced repair. The synthesis distinguishes evidence generated by laboratory screening, field monitoring, inspection and engineering assessment. Recent literature shows that connected sensing and data-driven models can improve spatial coverage and risk prioritisation, but field transfer remains constrained by sparse defect labels, uncertain sensor location, changing multiphase flow, limited external validation and the tendency to infer localised damage from average corrosion rates. The review proposes a threat-led framework that begins with corrosion circuits and credible mechanisms, qualifies controls under representative chemistry and flow, validates new technologies against independent wall-thickness or defect measurements, and links uncertainty to auditable intervention decisions. Onshore and offshore assets share electrochemical mechanisms but differ substantially in access, communications, environmental loading and repair logistics. The principal conclusion is that emerging technology creates value only when it strengthens the evidence chain from exposure and damage mechanism to verified defect, fitness-for-service assessment and intervention. Priority research should focus on time-separated field validation, uncertainty-aware sensor fusion, transferability between assets and prospective comparison with existing integrity programmes.

Keywords

corrosion management; oilfield integrity; pipeline monitoring; digital twin; machine learning; smart coatings; offshore assets IJEMT

References

ASTM International. (2025). ASTM G31-21(2025): Standard guide for laboratory immersion corrosion testing of metals. https://store.astm.org/g0031-21r25.html ASTM International. (2026). ASTM G170-26: Standard guide for evaluating and qualifying oilfield and refinery corrosion inhibitors in the laboratory. https://store.astm.org/g0170- 26.html Cao, G., Ruan, Y., Liu, J., Hu, Z., & Zhu, H. (2025). Preparation and properties study of self- healing anticorrosive coating based on MCM-41 nanocontainer and triazinyl corrosion inhibitor. Scientific Reports, 15, 22288. https://doi.org/10.1038/s41598-025-06528-2 Chen, J., Zhang, R., Li, Q., Wang, H., Ma, Q., Fan, Q., Fan, L., & Lin, Z. (2025). Non-uniform corrosion monitoring of steel pipes using distributed optical fiber sensors in the fluctuation zone of a coastal wharf. Sensors, 25(10), 3194. https://doi.org/10.3390/s25103194 DNV. (2021). DNV-RP-F116: Integrity management of submarine pipeline systems (edition December 2021). https://www.dnv.com/energy/standards-guidelines/dnv-rp-f116- integrity-management-of-submarine-pipeline-systems/ DNV. (2025). DNV-RP-F101: Corroded pipelines (2019 edition, amended September 2025). https://www.dnv.com/energy/standards-guidelines/dnv-rp-f101-corroded-pipelines/ Enning, D., & Garrelfs, J. (2014). Corrosion of iron by sulfate-reducing bacteria: New views of an old problem. Applied and Environmental Microbiology, 80(4), 1226–1236. https://doi.org/10.1128/AEM.02848-13 Farh, H. M. H., Ben Seghier, M. E. A., & Zayed, T. (2023). A comprehensive review of corrosion protection and control techniques for metallic pipelines. Engineering Failure Analysis, 143, 106885. https://doi.org/10.1016/j.engfailanal.2022.106885 Ge, Y., Wang, C., Nabuk Etim, I.-I., Khan, S., Li, C., Yang, L., Liu, J., Yi, P., Liu, J., Sand, W., & Zhang, R. (2025). Deep-sea microbially influenced corrosion and biomineralization. Frontiers in Microbiology, 16, 1605909. https://doi.org/10.3389/fmicb.2025.1605909 Hu, J. (2024). Prediction of the internal corrosion rate for oil and gas pipelines and influence factor analysis with interpretable ensemble learning. International Journal of Pressure Vessels and Piping, 212, 105329. https://doi.org/10.1016/j.ijpvp.2024.105329 International Organization for Standardization. (2010). ISO 21457:2010: Petroleum, petrochemical and natural gas industries—Materials selection and corrosion control for oil and gas production systems. https://www.iso.org/standard/45938.html International Organization for Standardization. (2020). ISO 15156-1:2020: Petroleum and natural gas industries—Materials for use in H2S-containing environments in oil and gas production, Part 1. https://www.iso.org/standard/79658.html Jones, J. F., Raj, V., Abas, P. E., Petra, M. I., Sivan, D., Satheesh Kumar, K., Jose, R., & Mathew, S. (2025). Application of artificial intelligence for asset integrity management of offshore oil and gas pipelines. Life Cycle Reliability and Safety Engineering, 14(4), 503–530. https://doi.org/10.1007/s41872-025-00353-2 Kermani, M. B., & Morshed, A. (2003). Carbon dioxide corrosion in oil and gas production—A compendium. CORROSION, 59(8), 659–683. https://doi.org/10.5006/1.3277596 Knisz, J., Eckert, R., Gieg, L. M., Koerdt, A., Lee, J. S., Silva, E. R., Skovhus, T. L., An Stepec, B. A., & Wade, S. A. (2023). Microbiologically influenced corrosion—More than just microorganisms. FEMS Microbiology Reviews, 47(5), fuad041. https://doi.org/10.1093/femsre/fuad041 IJEMT Laycock, N., Metri, V., Rai, S., Sabhapondit, A., Hartog, J., Ghosh, S., & Abdullah, A. M. (2024). Key challenges for internal corrosion modeling of wet gas pipelines. CORROSION, 80(12), 1146–1163. https://doi.org/10.5006/4532 Little, B. J., Blackwood, D. J., Hinks, J., Lauro, F. M., Marsili, E., Okamoto, A., Rice, S. A., Wade, S. A., & Flemming, H.-C. (2020). Microbially influenced corrosion—Any progress? Corrosion Science, 170, 108641. https://doi.org/10.1016/j.corsci.2020.108641 Lv, X., Wang, C., Liu, J., Sand, W., Nabuk Etim, I.-I., Zhang, Y., Xu, A., Duan, J., & Zhang, R. (2024). The microbiologically influenced corrosion and protection of pipelines: A detailed review. Materials, 17(20), 4996. https://doi.org/10.3390/ma17204996 Mouneir, S. M., & El-Shamy, A. M. (2026). A comprehensive review of corrosion in oil and gas pipelines: Mechanisms, mitigation strategies, and future directions. Multiscale and Multidisciplinary Modeling, Experiments and Design, 9, Article 131. https://doi.org/10.1007/s41939-026-01185-y NACE International. (2016). International measures of prevention, application, and economics of corrosion technologies . https://impact.nace.org/ Nešić, S. (2007). Key issues related to modelling of internal corrosion of oil and gas pipelines— A review. Corrosion Science, 49(12), 4308–4338. https://doi.org/10.1016/j.corsci.2007.06.006 Nešić, S. (2012). Effects of multiphase flow on internal CO2 corrosion of mild steel pipelines. Energy & Fuels, 26(7), 4098–4111. https://doi.org/10.1021/ef3002795 Okyere, M. S. (2025). Assessment of internal corrosion risk in wet sour gas pipeline systems utilizing computational fluid dynamics: A predictive framework for evaluating pipeline and structural integrity, with a case study of the Kashagan 28-inch offshore pipeline. Journal of Engineering and Applied Science, 72, 250. https://doi.org/10.1186/s44147- 025-00737-2 Papavinasam, S. (2014). Corrosion control in the oil and gas industry. Gulf Professional Publishing. https://shop.elsevier.com/books/corrosion-control-in-the-oil-and-gas- industry/papavinasam/978-0-12-397022-0 Parlak, B. O., & Yavasoglu, H. A. (2023). A comprehensive analysis of in-line inspection tools and technologies for steel oil and gas pipelines. Sustainability, 15(3), 2783. https://doi.org/10.3390/su15032783 Peng, W., Hou, J., Guo, W., Li, J., & Duan, T. (2025). Virtual-real combination evaluation method and digital twin technology exploration for deep-sea corrosion. npj Materials Degradation, 9, 125. https://doi.org/10.1038/s41529-025-00661-z Solovyeva, V. A., Almuhammadi, K. H., & Badeghaish, W. O. (2023). Current downhole corrosion control solutions and trends in the oil and gas industry: A review. Materials, 16(5), 1795. https://doi.org/10.3390/ma16051795 Wang, T., Feng, K., Ling, J., Liao, M., Yang, C., Neubeck, R., & Liu, Z. (2024). Pipeline condition monitoring towards digital twin system: A case study. Journal of Manufacturing Systems, 73, 256–274. https://doi.org/10.1016/j.jmsy.2024.02.006

Integrating Emerging Corrosion Monitoring and Mitigation Technologies for Onshore and Offshore Oilfield Assets

Abstract

Keywords

References

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