Corrosion Prediction Model of Submarine Mixed Pipeline X65 Steel under a CO2/Cl− Synergistic System

Zhao, Shuai; Liao, Kexi; Liu, Ying; Miao, Chunjiang; Wei, Chenliang; He, Guoxi

doi:10.1007/s13369-021-06388-8

Cited by 5 publications

(1 citation statement)

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“…They created a corrosion rate prediction model specifically for sulfur-containing wet natural gas pipelines, accounting for diverse gas partial pressures, flow rates, and temperature scenarios. Zhao Shuai et al [12] integrated two crucial variables, CO 2 and chloride ions, into their corrosion prediction model. Their modify internal corrosion model exhibited a maximum error rate not exceeding 7%, which was 3226 times less than that of the Norsok M506 corrosion model.…”

Section: Introductionmentioning

confidence: 99%

Establishing and applying a remaining life prediction model for natural gas collection and transportation pipelines in the context of CO2/H2S/O2

Zhao,

Gao,

et al. 2024

Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024)

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Corrosive gases like CO 2 , H 2 S, and O 2 are commonly present in natural gas collection and transmission pipelines, leading to significant corrosion issues within the infrastructure. While the addition of quantitative corrosion inhibitors has traditionally helped slow down pipeline corrosion, instances of pipe perforation still occur. Currently, existing corrosion rate prediction models do not account for the effectiveness of protective measures, making it challenging to accurately calculate the remaining life of pipelines. Consequently, a novel approach has been developed to estimate the remaining life of gathering pipelines in the presence of CO 2 , H 2 S, and O 2 . The novel approach is rooted in a corrosion rate prediction model that incorporates factors such as chloride ion concentration, dissolved oxygen levels, pipeline routing, and the efficiency of corrosion inhibition in influencing the corrosion rate. This approach involves segmenting the natural gas gathering and transportation pipeline into multiple time nodes spanning from production to evaluation. By calculating the corrosion rate at each node and determining the accumulated wall thickness value of the pipeline, it becomes possible to assess the remaining life of the pipeline. In contrast to current technologies, the discrepancy between the wall thickness loss value predicted by this new method and actual internal inspections is less than 10%. This enhanced accuracy significantly improves the prediction of remaining pipeline life, offering a reliable basis for decision-making regarding pipeline inspection and maintenance schedules.

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Section: Introductionmentioning

confidence: 99%