What did Enview find?

During a deployment with one of the world’s largest energy providers, Enview automatically identified bank erosion at a water crossing of a liquids pipeline. Enview’s 3D Geospatial Analytics AI Engine compared LiDAR and imagery data sets to detect meaningful changes along the bank slope of a tributary, which was also obscured by vegetation.

Why is this important?

Pipelines are typically buried underground and occasionally cross water bodies along their routes. Pipeline operators monitor those water crossings because any damage to the pipelines that results in a spill could be particularly devastating. To enhance safety, operators inspect water crossings for any changes that might increase the risk for damage, such as bank erosion, debris, loss of depth of cover, and channel avulsion. The Pipeline and Hazardous Materials Safety Administration (PHMSA) has regulations that require operators to address risks at water crossings. Accurate and timely identification of changes helps operators with regulatory compliance and enhances safety.

What actions were taken?

Given access to findings such as the above, the operator is able to identify potential threats quickly and confidently prioritize water crossings for field inspection. The operator is now aware of the erosion along the tributary which is otherwise obscured by vegetation and impossible to determine via imagery alone.

 

Article originally published on LinkedIn: https://www.linkedin.com/pulse/river-bank-erosion-identified-change-detection-krassimir-piperkov/