World Geothermal Congress 2020+1
March - October, 2021

UAV-Based Thermal Imagery of Hot Water and Steam Pipelines for Internal Leakage Detection, SW Iceland


[Svarmi ehf., Iceland]

In Iceland, thousands of kilometers of pipelines transport hot water from boreholes to populated areas. Some of these pipelines are more than 50 years old, and corrosion and the rough climate can lead to leakage and thus to heat- and pressure loss. These leakages often occur inside of the insulation layer within the pipe casing and are therefore difficult to detect from the outside. A new approach was initiated to detect internal leakage through thermal anomalies on the pipeline surface. For this test project a major distribution pipeline was surveyed at an average ground sampling distance of 2.1 cm using a multicopter UAV (unmanned aerial vehicle) equipped with both a long-wave infrared sensor (0.05 K thermal sensitivity) and a normal color (RGB) sensor. The UAV followed a GPS track over the course of a pipeline, ~20 km in total. Using photogrammetry, detailed georeferenced thermal- and RGB maps of the pipelines were created. The locations of potential leakages were sent to the responsible engineers who could then assess the pipe in a more efficient manner. Using this method, it was possible to successfully locate at least one major internal leak which didn’t show any visible signs on the pipe casing. Multiple external leaks and other damage to the pipe casing were also identified using the UAV-based RGB and thermal imagery together. The main outcomes of this test project are: 1.) The method allowed for detection and location of internal leaks in geothermal pipelines which are invisible on the pipe casing, 2.) external damage to the pipes were also detected and located, 3.) the resulting thermal and RGB maps can be inspected and compared by the responsible engineers, reducing time spent in the field inspecting pipes and providing a more cost-effective and safe method for inspection.

        Topic: Exploration Paper Number: 11152

         Session 8P: Poster 2 [Tuesday 11th May 2021, 11:00 pm] (UTC-8)
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