Enbridge Pipelines Inc. operates one of the longest and most complex pipeline systems in the world. As such, thorough, system-wide understanding of defect behavior is a critical aspect of Enbridge’s Integrity Management Program (IMP). To enhance understanding of corrosion behavior, and aid in determination of in-line inspection revalidation intervals, a quantitative corrosion defect assessment approach has been developed and implemented for the Enbridge system. To date nine trap-to-trap pipeline sections have been completed using this approach. Utilizing defect data from consecutive high-resolution corrosion in-line inspection tool runs in correlation with pipe attribute information and environmental characteristics, a statistical approach has been developed to determine the distribution of the corrosion growth rates along these nine sections of pipeline. Validation was achieved through comparison with other corrosion growth rate assessment methods. This comparison was also used to develop refinements to the approach. The approach provided an upper-bound estimate of corrosion growth and was considered appropriate for system-wide application where other defect-by-defect comparison methods can be time, labour, and cost intensive. Use of this upper-bound estimate of corrosion growth in combination with field metrics, operational history of the pipeline, defect trending and, where available, additional sources of corrosion growth rate determination have provided the operator with an effective, practical, and defensible tool set for determining subsequent in-line inspection reassessment intervals across the pipeline system. Data integration inherent in the process has also provided valuable insight regarding corrosion growth rate drivers as affected by pipeline and environmental factors. While focusing on trap-to-trap sections of the Enbridge system that have been inspected with multiple high-resolution in-line inspection tools, this paper/presentation will also discuss a statistical corrosion growth rate approach for trap-to-trap sections with only one high-resolution in-line inspection run.
Skip Nav Destination
2004 International Pipeline Conference
October 4–8, 2004
Calgary, Alberta, Canada
Conference Sponsors:
- International Petroleum Technology Institute
ISBN:
0-7918-4176-6
PROCEEDINGS PAPER
Corrosion Defect Management Based on a Quantitative Growth Approach
R. W. Sillers,
R. W. Sillers
Enbridge Pipelines Inc., Edmonton, AB, Canada
Search for other works by this author on:
S. Kariyawasam,
S. Kariyawasam
GE Energy, PII Pipeline Solutions Canada Ltd., Calgary, AB, Canada
Search for other works by this author on:
B. S. Smith
B. S. Smith
Enbridge Pipelines Inc., Edmonton, AB, Canada
Search for other works by this author on:
R. W. Sillers
Enbridge Pipelines Inc., Edmonton, AB, Canada
S. Kariyawasam
GE Energy, PII Pipeline Solutions Canada Ltd., Calgary, AB, Canada
B. S. Smith
Enbridge Pipelines Inc., Edmonton, AB, Canada
Paper No:
IPC2004-0391, pp. 1265-1275; 11 pages
Published Online:
December 4, 2008
Citation
Sillers, RW, Kariyawasam, S, & Smith, BS. "Corrosion Defect Management Based on a Quantitative Growth Approach." Proceedings of the 2004 International Pipeline Conference. 2004 International Pipeline Conference, Volumes 1, 2, and 3. Calgary, Alberta, Canada. October 4–8, 2004. pp. 1265-1275. ASME. https://doi.org/10.1115/IPC2004-0391
Download citation file:
6
Views
Related Proceedings Papers
Related Articles
Deep Convolutional Neural Network Framework for Diagnostics of Planetary Gearboxes Under Dynamic Loading With Feature-Level Data Fusion
J. Vib. Acoust (June,2022)
Multisource Data Fusion for Classification of Surface Cracks in Steel Pipes
ASME J Nondestructive Evaluation (May,2018)
Fatigue Damage Diagnostics of Composites Using Data Fusion and Data Augmentation With Deep Neural Networks
ASME J Nondestructive Evaluation (May,2022)
Related Chapters
LARGE STANDOFF MAGNETOMETRY TECHNOLOGY ADVANCES TO ASSESS PIPELINE INTEGRITY UNDER GEOHAZARD CONDITIONS AND APPROACHES TO UTILISATION OF IT
Pipeline Integrity Management Under Geohazard Conditions (PIMG)
The Application of the Data Fusion to Forest-Fire Harm Degree
International Conference on Future Computer and Communication, 3rd (ICFCC 2011)
Vehicle Moving Status Classification in Vehicular Networks Based on Data Fusion
International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)