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51317--9504-Validation of Corrosion Growth Rate Models

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Validation results of feature level and joint level CGR based on feature matching and signal matching. These results enable pipeline operators to establish defect repair schedules and re-inspection intervals with increased confidence.

Product Number: 51317--9504-SG
ISBN: 9504 2017 CP
Author: Yan Ping Li
Publication Date: 2017
Industry: Pipelines, Tanks, and Underground Systems
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$20.00

Corrosion growth rate (CGR) is one of the key elements in corrosion threat management. It is used to determine metal loss In-Line Inspection (ILI) re-assessment interval flag the high growth features that requires excavation before the next ILI and predict probability of failure of an unmitigated feature. Over-estimated CGR may result in unnecessary expenditures for excavations and remediation while under-estimated CGR could result in pipeline failure. In this paper several CGR methodologies used by Enbridge to manage corrosion on pipelines including historical CGR back-to-back CGR and ILI signal based CGR are discussed and validated. Historical CGR refers to the rate that is calculated based on the ILI reported depth and vintage of the line. Back to back CGR refers to the rate that is calculated based on ILI reported depths of two back-to-back ILIs. Signal based CGR refers to the rate that is determined based on ILI raw data review provided from the ILI vendor. Both feature level and joint level CGR have been used in corrosion threat management. A probabilistic CGR methodology that accounts for uncertainty of measurement tools is also included in this study. This new CGR methodology includes calibrating ILI reported depth based on the ILI tool performance. ILI tool performance is evaluated using field data and considers ILI and field measurement errors. In this CGR model ILI reported depth is also adjusted based on static features which are those that are not growing such as mitigated features and manufacturing anomalies.The various CGR methodologies are validated based on comparing the predicted depth using CGR with ILI reported depth as well as field measurements. This paper demonstrates the validation results of historical back-to-back signal based CGR and the new CGR method. Recommendation of the CGR methodology is made based on the study. The CGR validation study enables pipeline operators to establish defect repair schedule and re-inspection intervals with increased confidence.

Key words: Corrosion growth rate, CGR, inline inspection, ILI, metal loss, validation, threat management, re-inspection interval

Corrosion growth rate (CGR) is one of the key elements in corrosion threat management. It is used to determine metal loss In-Line Inspection (ILI) re-assessment interval flag the high growth features that requires excavation before the next ILI and predict probability of failure of an unmitigated feature. Over-estimated CGR may result in unnecessary expenditures for excavations and remediation while under-estimated CGR could result in pipeline failure. In this paper several CGR methodologies used by Enbridge to manage corrosion on pipelines including historical CGR back-to-back CGR and ILI signal based CGR are discussed and validated. Historical CGR refers to the rate that is calculated based on the ILI reported depth and vintage of the line. Back to back CGR refers to the rate that is calculated based on ILI reported depths of two back-to-back ILIs. Signal based CGR refers to the rate that is determined based on ILI raw data review provided from the ILI vendor. Both feature level and joint level CGR have been used in corrosion threat management. A probabilistic CGR methodology that accounts for uncertainty of measurement tools is also included in this study. This new CGR methodology includes calibrating ILI reported depth based on the ILI tool performance. ILI tool performance is evaluated using field data and considers ILI and field measurement errors. In this CGR model ILI reported depth is also adjusted based on static features which are those that are not growing such as mitigated features and manufacturing anomalies.The various CGR methodologies are validated based on comparing the predicted depth using CGR with ILI reported depth as well as field measurements. This paper demonstrates the validation results of historical back-to-back signal based CGR and the new CGR method. Recommendation of the CGR methodology is made based on the study. The CGR validation study enables pipeline operators to establish defect repair schedule and re-inspection intervals with increased confidence.

Key words: Corrosion growth rate, CGR, inline inspection, ILI, metal loss, validation, threat management, re-inspection interval

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