Prioritizing Action on Pipe Joints with High ILI Call Density
In pipeline integrity management, it’s common to see high densities of corrosion calls on certain pipeline joints after an in-line inspection (ILI) run — sometimes thousands of features within a short section of pipe. Many of these calls may be relatively shallow, but the cumulative effect of widespread corrosion presents a serious challenge
How do operators prioritize action when no single feature exceeds repair thresholds, but the data indicates general degradation? Making the right decision requires looking beyond simple feature depth.
Look Beyond Depth — Use Probability of Exceedance (PoE)
[1],[2]:
Traditional approaches often focus solely on individual feature size or percent wall loss. But with dense ILI data, this method risks missing what matters most: the likelihood of failure considering both defect size and uncertainty.
The Probability of Exceedance (PoE) provides a more meaningful prioritization tool. PoE quantifies the chance that a corrosion feature or interacting group of features exceeds a critical failure threshold — like 80% wall loss or burst pressure limits. This approach incorporates:
• ILI sizing error and measurement uncertainty
• Material strength variability
• Defect length and geometry
• Potential for feature interaction
Prioritizing based on PoE allows operators to focus on what is most likely to fail, rather than chasing every shallow feature.
Be Aware of ILI Limitations — Especially with MFL Tools in Dense Corrosion
[4],[5],[8]:
While Magnetic Flux Leakage (MFL) tools are widely used for detecting metal loss, they often struggle in environments with high feature density. In these scenarios, operators should carefully consider:
• Under-sizing or mischaracterization of deeper features due to magnetic saturation
• Feature interaction leading to signal distortion or missed metal loss
• Difficulty in distinguishing between individual pits and general metal loss
• Reduced accuracy in sizing depth, particularly for large, shallow general corrosion areas
MFL tools tend to perform best when detecting discrete, isolated pits — not when faced with clusters of overlapping features or widespread external corrosion. As feature density increases, confidence in the reported depth and sizing accuracy decreases.
Operators should evaluate whether their MFL data is understating the true severity of the corrosion and, if necessary, consider follow-up inspections using high-resolution UT tools or direct assessment.
Prioritize with PoE and Feature Interaction Analysis
[1],[2]:
Once PoE is calculated, operators should also assess feature clustering and metal loss interaction. A collection of smaller defects spaced closely together can behave like one large defect, potentially lowering the burst capacity of the pipe.
Use industry guidance, such as API 1160 and ASME B31.8S, to evaluate interaction rules. Feature clusters should be prioritized for assessment when they:
• Appear within three times the defect size of each other
• Are located in High Consequence Areas (HCAs)
• Contribute to a cumulative probability of failure that exceeds risk thresholds
Reassess Corrosion Growth and Re-Inspection Intervals
[3],[7]:
Dense ILI call areas — especially when combined with known tool performance limitations — often signal a systemic corrosion issue rather than isolated defects. This may be a result of:
• Coating failure
• Ineffective cathodic protection (CP)
• Environmental conditions promoting corrosion
Operators should re-examine corrosion growth rates, review re-inspection intervals, and consider field verification digs or alternative inspection methods. In many cases, validating ILI results with ultrasonic (UT) inspection tools or direct examination may reveal deeper metal loss than originally reported.
Document the Engineering Assessment and Risk-Based Decisions
[6],[7]:
Even if regulatory repair thresholds aren’t technically met, the situation demands a well-documented engineering assessment. PHMSA’s integrity regulations (49 CFR 192.712) and industry standards require clear, defensible decision-making.
That assessment should include:
• Evaluation of ILI tool limitations in dense corrosion areas
• PoE calculations and feature interaction analysis
• Plans for verification, mitigation, or re-inspection
• A risk-based rationale supporting continued operation or further action
Final Thoughts
High volumes of corrosion calls — especially from MFL ILI runs — are common but challenging. Operators must look past raw defect counts and focus on probabilistic failure risks, feature interaction, and tool performance limitations.
Prioritizing action based on PoE and risk helps operators:
• Avoid costly, unnecessary digs
• Focus resources where failure is most likely
• Maintain safety and compliance with PHMSA and industry expectations
When ILI data density is high and confidence in tool performance drops, supplementing with field verification or ultrasonic inspection may be the best path forward.
Bibliography
American Petroleum Institute. API Recommended Practice 1160: Managing System Integrity for Hazardous Liquid Pipelines. 3rd ed., API, 2021.
American Society of Mechanical Engineers. ASME B31.8S: Managing System Integrity of Gas Pipelines. ASME, 2020.
DNV. Recommended Practice DNV-RP-F101: Corroded Pipelines. DNV, 2010.
Gas Technology Institute. Assessment of ILI Sizing Uncertainty and Reliability. GTI, 2016.
NACE International. NACE SP0502-2018: Pipeline External Corrosion Direct Assessment (ECDA) Methodology.NACE, 2018.
Pipeline and Hazardous Materials Safety Administration (PHMSA). 49 CFR Part 192 – Transportation of Natural and Other Gas by Pipeline: Minimum Federal Safety Standards. U.S. Department of Transportation, 2023. Accessed at: https://www.phmsa.dot.gov/pipeline.
Pipeline and Hazardous Materials Safety Administration (PHMSA). Integrity Management Frequently Asked Questions. U.S. Department of Transportation. Accessed at: https://www.phmsa.dot.gov/pipeline/integrity-management.
Rosen Group. Understanding MFL Inspection Data: Challenges with Complex Corrosion. Technical Paper, Rosen Group.
Clarion Technical Conferences. Pipeline Pigging and Integrity Management (PPIM) Conference Proceedings.Various Years.
The content of this article is provided for informational purposes only and reflects general industry practices related to pipeline integrity management. It is not intended to serve as professional engineering advice, regulatory guidance, or a substitute for a detailed engineering assessment based on project-specific conditions.
Pipeline integrity decisions should be made using qualified engineering judgment, appropriate standards, and regulatory requirements applicable to each unique system. Gustafson Integrity Services LLC does not assume any responsibility or liability for actions taken based on the information provided in this article.
For project-specific analysis or professional consulting services, please contact a qualified pipeline integrity professional.
