Damage mechanisms like internal and external corrosion, dents and cracks can now be accurately quantified. The combination of better inspection and superior assessment procedures is rapidly demonstrating the weaknesses in older procedures.

Using these more advanced assessment technologies – validated and supported through extensive field research – operators can now assess defects in pipelines and determine fitness-for-service (FFS) quickly and confidently.

FFS assessments have become increasingly accepted across the pipeline industry over the past few years. FFS standard API 579/ASME FFS-1 (API 579-2007) provides guidelines for assessing types of damage affecting pipelines across all industries. These damage mechanisms include corrosion, weld misalignment, dents, laminations and cracks, among others. Of particular interest are cracks forming near welds where residual stresses from the welding process have the potential to rapidly progress crack growth.

Quest Integrity Group’s powerful Signal FFS Version 4 software was designed by industry experts and allows engineers to quickly perform FFS and fracture mechanics analyses, thereby reducing equipment and operational safety risks. The software adheres to all API 579 standards and is capable of assessing hundreds of flaws at once as well as computing a range of critical flaw sizes. An automation tool such as this allows the computation of the ‘what if’ conditions in a matter of minutes.

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Assessing crack-like flaws with hydrostatic testing has been a common practice in the pipeline industry for decades. While this method often detects the worst of the cracks existing in the pipeline at the time of testing, hydrostatic testing is not a reliable method for determining inspection intervals and it provides an indication of FFS only at a single point in time.

Moreover, it is an inefficient way of detecting cracks as the detection method requires a failure of the line which leads to costly reactive repairs. Rapid assessment of cracks with advanced software such as Signal is a quality method in terms of confidence, accuracy and efficiency.