Ultra-high resolution MFL Inspection for the Detection and Sizing of Pitting and Pinhole Corrosion in Gas Pipelines
Proceedings Publication Date
Alejandrino Ruiz
Alejandrino Ruiz, John Healy, Bradford Edwards
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Pinhole and pitting corrosion are localized forms of corrosion which are generally associated with accelerated corrosion growth rates. As defined by POF specification, a pinhole is localized corrosion with surface dimensions smaller than 1·t or 10 mm whichever is greater in length and width direction.  It can be caused by corrosion mechanisms such as internal/external MIC, or externally in areas of disbonded pipeline coating and CP shielding.  Pinhole features are often considered to be more critical with respect to pipeline integrity than uniform corrosion due to potentially high associated corrosion growth rates.

Moreover, traditional MFL and UT metal loss inspection technologies have had difficulty in reliably detecting and sizing pinhole corrosion with a resulting challenge for Operators to manage the associated integrity risk.

At the end of 2021 Pipecare was invited by a major USA gas pipeline operator to conduct a “blind” flow through test using an ultra-high resolution MFL tool to detect, size, characterize, and locate small diameter metal loss features (Pinholes), in an 8-inch flow string located at PRCI-TDC facility in Houston-Texas.  This test spool incorporated several natural pinhole type ML defects on the internal surface of the pipe wall.  The wall loss percentages, and dimensions, ranged between the usual upper and lower detection limits of the smart pigs.  There were some features on the extreme limits of tool detection limits to test the detection and reporting accuracies (at a 90% POD).

This paper provides an overview of the work involved and performed by Pipecare for detecting and sizing small diameter “Pinhole” type defects in gas pipelines and tool performance evaluation based on API-1163.  The results of the findings are discussed, and conclusions and recommendations are provided with the aim of providing Operators with enhanced data to support pipeline integrity decisions when dealing with these types of defects.

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