Application and Research of Corrosion Data Comprehensive Analysis Method inIntegrity Management of Long-Distance Crude Oil Pipelines

SU Zhihua

doi:10.11973/fsyfh-202312018

Corrosion & Protection > 2023 > 44(12): 114-123. > DOI: 10.11973/fsyfh-202312018

SU Zhihua. Application and Research of Corrosion Data Comprehensive Analysis Method inIntegrity Management of Long-Distance Crude Oil Pipelines[J]. Corrosion & Protection, 2023, 44(12): 114-123. DOI: 10.11973/fsyfh-202312018

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Application and Research of Corrosion Data Comprehensive Analysis Method inIntegrity Management of Long-Distance Crude Oil Pipelines

SU Zhihua^,

Shanghai Anchor Technology Co., Ltd., Shanghai 200030, China

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Received Date: January 12, 2022

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Abstract

Abstract

According to the methods given in Q/SY 1180. 4-2015 and SY/T 0087. 5-2016 criterion, taking a foreign long-distance crude oil pipeline as the research object, the completion data, in-line inspection data, operation and maintenance data, magnetic flux leakage detection, and corrosion protection layer detection, cathodic protection test, excavation verification, corrosion evaluation and integrity evaluation data were collected. 18 types of data related to pipeline integrity management were aligned and the main pipeline corrosion data were comprehensively analyzed. Combining with the elevation along the pipeline, the range of the anti-corrosion coating, the insulation resistance of the anti-corrosion coating and the integrity evaluation, totally 11 internal corrosion defects in the pipeline magnetic flux leakage test and 15 external corrosion defects in the pipeline magnetic flux leakage test that need a positive response and 7 double height pipe sections were identified. For different types of pipeline defects and pipe sections, corresponding risk prevention and control measures were proposed to provide references for the safe operation and integrity management of the pipeline.
- corrosion data,
- magnetic flux leakage detection,
- excavation verification,
- data alignment,
- comprehensive analysis,
- integrity management

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