Data Integration is a Key to Maintaining Pipeline Integrity: Factors You Must Consider

摘要

Pipeline releases occur for a variety of reasons.The root cause of failures is often a combination of issues,such as fabrication anomalies exacerbated by sub-optimal operations.For example,a leak of gasoline in the summer of 2018 has been attributed to corrosion aggravated by elevated hoop stress.While the industry recognizes failures can be prevented by proactively integrating various datasets to identify potential problems,most pipeline operators struggle to combine datasets in meaningful ways.To detect and diagnose potential issues in their pipelines,many operators still rely extensively on cumbersome spreadsheets of in-line inspection(ILI)results.There are several problems with this approach,including the inability of ILI results to portray a total picture of the threat to pipeline integrity.For example,a crack within a dent near a pump station with very aggressive pres-sure cycling presents a much greater threat than a same-size crack without a dent or lighter pressure cycles.Manual updates such as updates to high consequence areas(HCA)within ILI results spreadsheets further compound the issue as engineers dedicate precious time on intermediate administrative tasks at the expense of value-added,high-level analysis.Moreover,the simplicity of the once trusty spreadsheet is insufficient in modeling geospatial data.The industry's drive towards using geographic information systems(GIS)is encouraging,but only in early stages as most systems do not include data that is critical to identifying integrity threats.As a result,integrity engineers are presented with a less than full picture of potential threats.