Large-Scale Controlled Experiment Demonstrates Effectiveness of Methane Leak Detection and Repair Programs at Oil and...

Most jurisdictions around the globe use leak detection and repair (LDAR) programs to find and fix methane leaks from oil and gas operations. In this work, we empirically evaluate the efficacy of LDAR programs using a large-scale, bottom-up, randomized controlled field experiment across ∼200 oil and gas sites in Red Deer, Canada. We find that tanks are the single largest source of emissions, contributing to nearly 60% of the total emissions. The average number of leaks at treatment sites that underwent repair reduced by ∼50% compared to the control sites. Although control sites did not see a reduction in the number of leaks, emissions reduced by approximately 36%, suggesting potential impact of routine maintenance activities to find and fix large leaks. By tracking tags on leaking equipment over time, we find a high degree of persistence; leaks that are repaired remain fixed in follow-up surveys, while non-repaired leaks remain emitting at a similar rate, suggesting that any increase in observed leak emissions following LDAR surveys are likely from new leaks. Our results show that a focus on equipment and sites that are prone to high emissions, such as tanks and oil sites, is key to cost-effective mitigation.