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Spatial characterization and simulation of new defects in corroded pipeline based on In-Line Inspections

Author

Listed:
  • Amaya-Gómez, Rafael
  • Sánchez-Silva, Mauricio
  • Muñoz, Felipe
  • Schoefs, Franck
  • Bastidas-Arteaga, Emilio

Abstract

Onshore pipelines are exposed to corrosion degradation, facilitated by the pipeline’s management and surrounding aggressive environmental conditions. Every 2 to 6 years, pipeline operators often conduct In-Line (ILI) inspections to screen for pipe damage using magnetic or ultrasonic sensors. Considering soil and fluid aggressive conditions, and the possibility of false alarms or a miss-detections from the inspection device, new defects, i.e., metal loss at either the inner or outer wall, should be expected to occur between consecutive inspections. Considering the possibility of “corrosion colonies†and their significance in the pipeline’s reliability assessment, different authors have incorporated new corrosion defects in degradation and further reliability assessments using a Homogeneous Poisson Process. This process assumes that corrosion points are evenly distributed, which can be classified as conservative. This study aims to characterize the main spatial distribution of corrosion defects using the Complete Spatial Randomness (CSR) assumption under hypothesis testing. Additionally, it assesses how is the interaction between new and old defects from a repulsion–attraction perspective, and it proposes an alternative to simulate them for further reliability analyses. The suggested approach was applied in a real case study, obtaining that corrosion defects tend to be clustered and little repelled from those already detected.

Suggested Citation

  • Amaya-Gómez, Rafael & Sánchez-Silva, Mauricio & Muñoz, Felipe & Schoefs, Franck & Bastidas-Arteaga, Emilio, 2024. "Spatial characterization and simulation of new defects in corroded pipeline based on In-Line Inspections," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
  • Handle: RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023006117
    DOI: 10.1016/j.ress.2023.109697
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    References listed on IDEAS

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    1. Yazdi, Mohammad & Khan, Faisal & Abbassi, Rouzbeh & Quddus, Noor & Castaneda-Lopez, Homero, 2022. "A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
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    4. Rainer Winkelmann, 2000. "Seemingly Unrelated Negative Binomial Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 553-560, September.
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