Better Data: Methodologies and Best-Practices for Achieving Higher Quality Inspection Results
When considering the in-line inspection process from a holistic point of view, one might conclude that the entire process, as intricate as it is, is really all about the data. The data collected forms the foundation of the remediation plans and provides the confidence for desired operations between successive inspections. Regardless of the perceived attributes, abilities, or accuracies of available ILI technologies, they all become muted if the data quality is negatively impacted due to poor application or preparation. For example, what’s the point of hundreds of sensors if the majority of them are rendered ineffective due to improper line preparations? Data, good or bad, (if accepted) will inevitably become information; but information derived from poor quality data can lead to inappropriate or detrimental actions. This paper will discuss: 1) how effectively managing the inspection process leads to better quality data; 2) where the responsibility should reside for such decisions; and 3) the consideration of new and emerging technologies with respect to pending PHMSA mandates for piggability of all hazardous liquid pipelines in HCAs. This also includes the extension of IM requirements to portions of pipelines (e.g., pump stations and breakout tanks) and not just the line pipe. Pipeline operators are significantly vested in obtaining quality information but too often the discovery of data degradation is either initially difficult to conclude or realized too late to remedy. Ensuring that the entire process is completely aligned – from project management, to data collection and inspection, to analysis and interpretation – allows operators to obtain the best data set possible.
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A Case Study for a New Approach to Manage the Risk of Girth Weld Cracking in a Modern NPS 40 X70/X80 Pipeline with a combination of high resolution MFL, AXISS™ and IMU In-Line Inspection Technology