Combined Threats in Pipelines
Our industry has developed extensive integrity management plans and programs for corrosion, geometry, or crack like threats. However, when anomalies are combined or coinciding, threat detection, assessment, and risk management becomes more complex. The best way to manage combined threats in pipelines is by using in-line inspection and data analysis hand in hand and truly understanding the interactions.
Detecting coincident features using in-line inspection
When detecting combined features we must ask ourselves if they are in fact interacting, how this may effect the likelihood of failure, and how we can assess the risk. A wide array of technologies exist to identify features in pipelines which is essential for the data analysis needed to carefully dissect, identify and asses combined threats.
Identifying coincident threats of different types
Identifying coincident features from the same category, for example metal loss clusters, or crack colonies, can be relatively simple. Finding combined threats from different categories will require integrated data evaluation and integrity assessments from multiple data sets.
Dents with metal loss can be found by aligning MFL-A and caliper technologies (XT). For operators to make repair decisions, in this case sizing for both feature types, detection and classification will be key. Gouges with corrosion will appear similarly in the data, however experienced analysts and integrity engineers are able to classify these features using signal orientation, location of the metal loss in the dent, satellite imagining, coating surveys, and information from dig verifications.
These are considered some of the most challenging combined features to identify. Firstly, dents can cause sensor lift-off during in-line inspection, impacting data quality. To counter this, multiple in-line inspection technologies are generally utilized to best detect cracks with dents. EMAT and UT are generally used to identify cracking, however MFL is more tolerant to lift-offs and can provide enough data for detection. With both data sets again, evaluators come together to carefully review both data sets can identify critical features.
Although similar types of features, pipeline movement may cause significant bending strain on a pipeline, jeopardizing its integrity, and combined with a deformation such as a dent, buckle, or ovality may cause an acute risk for pipeline failure. In these scenarios a bending strain assessment combined with data from a caliper technology (XT) will allow for more targeted remedial action to take place.