Engineering Statistical Analysis and Visualization of Excavated Oil and Gas Pipeline Anomaly Depths to Matched Inline Inspection Estimates Using Power BI

• Activity Number: 362 - Contributed Poster Presentations: Section on Physical and Engineering Sciences
• Type: Contributed
• Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): William Harper* and Tara P McMahan and Benjamin R Hanna and Adriana Nenciu
• Companies: DNV GL and DNV GL and DNV GL and Otterbein University
• Keywords: oil; gas; pipeline; visualization; in-line inspection; pig

Abstract

In-line inspection (ILI) tools are used to help assess areas of a pipeline considered to have the potential to contain critical defects. As the ILI tools move through the inside of the pipe, signals are sent via transducers to the inside pipe wall. These signals help identify different types of anomalies, such as internal/external corrosion, cracks, and manufacturing artifacts. The depth of the anomaly is a key characteristic estimated by the ILI tool that is used in integrity analyses. How much faith one may place in the ILI results is often assessed through validation efforts that compares ILI to field excavation measurements. The data are used in multiple metrics of an integrity analysis, such as whether the ILI tool passes the industry standard API 1163 or the data should be adjusted. Adjusting ILI data can provide an accurate, but perhaps slightly conservative, safety approach to using all of the ILI calls given that only a small subset of field excavations have been performed. This study used representative ILI results and the Power BI data integration software to create flexible interactive analyses (statistical and visual) that rapidly track pipeline integrity metrics.