Assessing Internal Pitting Corrosion With Encoded Ultrasonic Scanning

Abstract

Internal corrosion is one of the main threats to pipeline integrity. For in-line inspection (ILI) based integrity programs, in-the-ditch non-destructive examination (NDE) data quality is imperative for ILI validation. NDE feature misclassification and/or depth inaccuracy can lead to unnecessary integrity actions such as unnecessary excavations, more frequent ILI, or increased risk to system integrity. Therefore, it is critical to ensure the accuracy of NDE data. Ultrasonic Testing (UT) technology is the primary method to detect, characterize, and measure internal corrosion during in-ditch NDE. While studies have been conducted to understand various NDE technologies and capabilities associated with detecting, sizing, and classifying crack and external corrosion indications, less work has been published regarding field evaluation of internal corrosion indications. In this study, real cases of liquid pipelines will be used to demonstrate the challenges in detecting, characterizing and sizing internal corrosion using current UT technologies. The cases show that improper NDE technique selection triggered additional excavations or caused internal corrosion to be non-conservatively under-reported. This work also includes various UT technologies, such as encoded zero-degree UT scanning, manual zero-degree UT testing, encoded Phased Array Ultrasonic Testing (PAUT), and Time of Flight Diffraction (TOFD) for characterizing and sizing both natural and machined defects in pipe and plate samples. High-resolution laser scans using Creaform HandyScan technology are used to verify actual feature depth. Depth sizing accuracy of each technology is established using statistical analysis. In order to determine detection limits of the above technologies, tests are performed on pitting and inclusion of various sizes, ranging from 8 mm to 0.5 mm in diameter. This study will assist in establishing the limitations of current UT NDE technologies and recommendations to develop best practices for obtaining quality field NDE data from pipeline excavations for internal corrosion.