Field Performance of New Methane Leak Detection Technologies at Upstream Oil and Gas Facilities

Abstract:

Reducing methane emissions from oil and gas activities can have positive climate impacts, improve local air quality, and save money. Currently, optical gas imaging (OGI) based cameras are the most widely used technology for conducting leak detection and repair programs for reducing methane emissions. While effective in detecting emissions, OGI-based surveys are time-consuming and expensive. In this context, emerging methane technologies promise faster and cost-effective approaches to detect methane emissions. While several recent studies have tested many new leak detection technologies under controlled conditions, there has been no systematic analysis of real-world performance at oil and gas facilities.

In this study, we conduct the first large-scale, concurrent field trial of alternative methane emissions detection and quantification technologies at operating oil and gas sites. We compared 10 fixed, hand-held, truck-, drone-, and plane-based technologies to conventional OGI-based leak detection surveys. The field trials were held in Alberta, Canada in two campaigns, one in June and the other in November.

We find that 8 of 10 teams were highly effective (>80%) at detecting site-level emissions but demonstrated varying capabilities in survey speed, localization (equipment-level), and emissions quantification. Plane- and truck-based teams showed distinct advantages over drones and hand-held teams in survey speed but require secondary inspection to find and potentially repair the emitting component. Truck- and drone-based teams were highly effective (>80%) in site-level and equipment-level detections but varied significantly in quantification capability compared to baseline OGI. We also explore the ability of technologies to classify site-level emissions based on rank order and their potential use as screening technologies. Even without full quantification, effective rank-based size discrimination (small, medium, or large) can help prioritizing sites for follow up and repair. Finally, we discuss the implications of our results for methane emissions regulations.