Chandler Kemp, Arvind P Ravikumar 

Reducing methane emissions from oil and gas systems is a central component of US and international climate policy. Leak detection and repair (LDAR) programs using optical gas imaging (OGI) based surveys are routinely used to mitigate fugitive emissions or leaks. Recently, new technologies and platforms such as planes, drones, and satellites promise more cost-effective methane mitigation than existing approaches. To be approved for use in LDAR programs, new technologies must demonstrate equivalent emissions mitigation to existing approaches. In this work, we use the FEAST modeling tool to (a) identify cost vs. mitigation trade-offs that arise from the use of new technologies, and (b) provide a framework for effective design of alternative LDAR programs. We identify several critical insights. First, new technologies and tiered LDAR programs can achieve equivalent emissions reductions at lower cost as current OGI-based approaches by varying survey frequency. Second, low median detection threshold technologies can trade sensitivity for speed without sacrificing mitigation outcomes. Third, emissions mitigation from technologies with high median detection thresholds have an effective upper bound independent of the survey frequency. Finally, vented emissions play a critical role in the cost-effectiveness of tiered detection programs that direct ground crews based on site-level emissions detection. The FEAST model will enable operators and regulators to systematically evaluate the role of new technologies in next generation LDAR programs.