{"title":"Characterizing Corrosion Defects With Apparent High Growth Rates on Transmission Pipelines","authors":"T. Dessein, B. Ayton, Travis Sera","doi":"10.1115/IPC2020-9572","DOIUrl":null,"url":null,"abstract":"\n Consecutive in-line inspections of transmission pipelines enable a comparison between the inspection results to characterize corrosion growth. Despite the high levels of in-line inspection tool accuracy and detection capabilities, corrosion defects with low calculated burst capacities may be detected on a subsequent inspection that were not reported in a previous inspection. These newly reported defects can pose a substantial challenge as the apparent growth rates between inspections of these defects can potentially drive unnecessary repair digs. This paper characterizes the contributing factors that can explain these phenomena, including:\n • Typical corrosion growth rates and their associated statistical frequency\n • The diminishing detection capability of inspection tools for smaller defects\n • The inspection tool minimum reporting threshold\n • The measurement accuracy of inspection tools.\n A statistical analysis was developed to quantify this interacting set of factors using Monte Carlo simulations that work retrospectively, covering a range of observed measured defect depths and then simulating the processes that could lead to newly reported defects being un-matched in a previous inspection.\n This analysis can be used to quantify the likelihood that a defect of a specific measured size would have been unreported in an earlier inspection due only to the performance characteristics of the inspection tool, and not as a result of defect growth that initiated since the time of the previous inspection. A set of case studies covering a range of pipeline inspection intervals ranging from 2 to 10 years are presented to demonstrate how this approach can be used to quantify appropriate growth rates that may be applied to these un-matched defects when assessing the remaining life or predicted probability of failure.","PeriodicalId":273758,"journal":{"name":"Volume 1: Pipeline and Facilities Integrity","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1: Pipeline and Facilities Integrity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/IPC2020-9572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Consecutive in-line inspections of transmission pipelines enable a comparison between the inspection results to characterize corrosion growth. Despite the high levels of in-line inspection tool accuracy and detection capabilities, corrosion defects with low calculated burst capacities may be detected on a subsequent inspection that were not reported in a previous inspection. These newly reported defects can pose a substantial challenge as the apparent growth rates between inspections of these defects can potentially drive unnecessary repair digs. This paper characterizes the contributing factors that can explain these phenomena, including:
• Typical corrosion growth rates and their associated statistical frequency
• The diminishing detection capability of inspection tools for smaller defects
• The inspection tool minimum reporting threshold
• The measurement accuracy of inspection tools.
A statistical analysis was developed to quantify this interacting set of factors using Monte Carlo simulations that work retrospectively, covering a range of observed measured defect depths and then simulating the processes that could lead to newly reported defects being un-matched in a previous inspection.
This analysis can be used to quantify the likelihood that a defect of a specific measured size would have been unreported in an earlier inspection due only to the performance characteristics of the inspection tool, and not as a result of defect growth that initiated since the time of the previous inspection. A set of case studies covering a range of pipeline inspection intervals ranging from 2 to 10 years are presented to demonstrate how this approach can be used to quantify appropriate growth rates that may be applied to these un-matched defects when assessing the remaining life or predicted probability of failure.