Abstract
As integrity programs mature over the life of a pipeline, an increasing number of data points are collected from second, third, or further condition monitoring cycles. Types of data include Inline Inspection (ILI) or External Corrosion Direct Assessment (ECDA) inspection data, validation or remediation dig information, and records of various repairs that have been completed on the pipeline system. The diversity and massive quantity of this gathered data proposes a challenge to pipeline operators in managing and maintaining these data sets and records.
The management of integrity data is a key element to a pipeline system Integrity Management Program (IMP) as per the CSA Z662[1]. One of the most critical integrity datasets is the repair information. Incorrect repair assignments on a pipeline can lead to duplicate unnecessary excavations in the best scenario and a pipeline failure in the worst scenario. Operators rely on various approaches to manage and assign repair data to ILIs such as historical records reviews, ILI-based repair assignments, or chainage-based repair assignments. However, these methods have significant gaps in efficiency and/or accuracy. Failure to adequately manage excavation and repair data can lead to increased costs due to repeated excavation of an anomaly, an increase in resources required to match historical information with new data, uncertainty in the effectiveness of previous repairs, and the possibility of incorrect assignment of repairs to unrepaired features.
This paper describes the approach adopted by Enbridge Gas to track and maintain repairs, as a part of the Pipeline Risk and Integrity Management (PRIM) platform. This approach was designed to create a robust excavation and repair management framework, providing a robust system of data gathering and automation, while ensuring sufficient oversight by Integrity Engineers. Using this system, repairs are assigned to each feature in an excavation, not only to a certain chainage along the pipeline. Subsequently, when a new ILI results report is received, a process of “Repair Matching” is completed to assign preexisting repairs and assessments to the newly reported features at a feature level. This process is partially automated, whereby pre-determined box-to-box features matched between ILIs can auto-populate repairs for many of the repaired features.
The proposed excavation management system would provide operators a superior approach to managing their repair history and projecting historical repairs and assessments onto new ILI reports, prior to assessing the ILI and issuing further digs on the pipeline. This optimized method has many advantages over the conventional repair management methods used in the industry. This method is best suited for operators that are embarking on their second or third condition monitoring cycle, with a moderate number of historical repairs.
Decision-theoretic inspection planning using imperfect and incomplete data