Abstract
The internal corrosion of pipelines in the petroleum industry is highly risky, and induced pipeline cracking may give rise to potential injury to personnel and environmental issues. The oil-water two-phase flow and the oil-gas-water three-phase flow are often observed in gathering and transportation pipelines. It is generally accepted that corrosion is induced by the presence of water, although it is a complex hydrodynamic process in which the material is removed from the pipeline due to physicochemical reactions. Hence, it is necessary to determine the key parameters that dominate the corrosion phenomena and how they can be modeled. As the water phase that wets the steel surface determines the initiation of corrosion, several aspects are widely discussed here, such as corrosive medium, phase inversion, water-wetting behavior, the entrainment of water, and the wettability of steel, to explain the corrosion mechanism of multiphase flow and correlation with the corrosion behavior. Of course, empirical and mechanistic models for corrosion prediction in pipelines are discussed. Also, the mostly applied techniques of identifying flow patterns and attaining related parameters in experiments for the evaluation of the corrosiveness of oil-brine mixtures are introduced. Further studies must be undertaken to expand the knowledge of corrosion and find applicable models for corrosion damage prediction and prevention.
About the authors
Hao Zhang is a PhD candidate in vehicle operation engineering at Beijing Jiaotong University (BJU). He graduated from BJU in 2013 with a bachelor’s degree in mechanical design and automation. His research area focuses on the internal corrosion of pipelines in the petroleum industry.
Hui-qing Lan is a professor and a PhD supervisor at BJU. She completed her postdoctoral work at the University of Tokyo. She holds a PhD in engineering (2002) from the China University of Petroleum (Beijing) and is a member of the Petroleum Storage and Transportation Committee of the China Petroleum Society.
Acknowledgments
This project was supported by the National Key R&D Program of China (no. 2017YFC0805005) and the Special Fund for Quality Inspection Scientific Research in the Public Interest of China (no. 201410027).
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