Data-Visualization Approach Enhances Pipeline-Integrity Management

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 222521, “Enhancing Pipeline-Integrity-Data Management Through Power BI and PI Dashboard Approach, ” by Khateb I. A. Bulushi, Fahmi H. Al Mawali, and Issa S. Alrashdi, Occidental Petroleum. The paper has not been peer-reviewed. _ In aging facilities, maintaining pipeline integrity through proactive maintenance is vital. A data-centered approach allows stakeholders to prioritize critical assets, allocate resources efficiently, and ensure proactive integrity-maintenance measures. The novel approach presented in this study integrates massive amounts of data that affect pipeline integrity by providing visible analysis of all findings from different inspection techniques, thus prioritizing inspection and repair programs while minimizing downtime and disruption. Introduction The operator’s inspection and operational data-management software and its database faced limitations in integrating and communicating multiple data sources monitoring asset degradation, such as thickness-monitoring locations (TML), corrosion-inhibitor programs, smart pigging data, topography, cathodic protection (CP) surveys, direct current voltage gradients (DCVG), close-interval potential surveys (CIPS), laboratory results, and bacterial activity. To overcome this technical boundary, a central data-management system is proposed that uses Microsoft Power BI along with OSI PI Coresight to build graphs and patterns that communicate relationships between data points. Methodology In-Line Inspection (ILI) Analysis and Topographical Correlation. Correlation of two ILI data sets from different vendors is a time-consuming process, especially when a massive field is involved that has generated thousands of records. The following field data are involved in such a comparison: - Weld joint number - Pipeline features such as CP points, weld locations, and valves - Distance of defect from the weld joint - Types of anomalies - Surface location of anomalies - Wall loss - Position of detected anomalies Additionally, a common phenomenon is over- or underestimation of wall loss compared with verified results achieved with ultrasonic testing (UT). The locally developed analysis tool uses Power Query and Microsoft Excel Visual for Basic programming to accelerate the analysis of existing wall-loss records across the pipeline and presents a list of nondetected critical locations with new defects; later, these loss defects undergo UT verification. The analysis tool correlates the data points from old and new tally sheets that contain thousands of data points by aligning common features. The tool also reveals missing data points, new defects, and changes in corrosion growth. Furthermore, it detects changes in defect orientation, such as transitions from internal to external defects. Then, the data is integrated with topographical information based on construction surveys to match changes in topography and correlate with anomaly distributions across the pipeline. ILI Data Integration with CP, DCVG, and CIPS. The analyzed ILI data from the tally sheets, which show new defect locations and growth of existing defects in the pipeline, are aligned with CP, DCVG, and CIPS inspection reports. In addition, the engineer can see minimum acceptable potential limits above the natural potential of the metal.