Quantifying methane emissions from oil and gas operations in the New Mexican Permian Basin with airplane-based hyperspectral detection

Abstract:

Methane emissions from oil and gas production, a major contributor to climate change, largely come from a small number of so-called super-emitter sites. Traditional techniques for detecting methane emissions generally must measure a subsample of the population of oil and gas infrastructure, potentially missing rare but highly consequential large emissions. This study employs a hyperspectral airplane-based methane remote sensing approach to survey the vast majority of the New Mexico Permian Basin, which has experienced major growth in oil production in the past ten years. From 2018 to 2020, the survey covered over 29,000 active wells (~87% of all active wells in the survey region) and over 10,000 miles of gas pipelines. We estimate total detected methane emissions, accounting for temporal intermittency and multiple coverage but not accounting for extrapolation to the full study area or emissions below the detection threshold, to be higher than most basin-wide fractional loss rates in the literature. After extrapolating to include emissions from all assets in the survey region and emissions below the minimum detection threshold of the system, estimated emissions grow by about 50%. These results suggest that in this oil-heavy basin with underdeveloped gas transmission infrastructure, emissions are substantially higher than most estimates in the literature. About 3% of the largest sources contribute over 50% of total emissions above minimum detection, indicating substantial opportunities for emission reductions by detecting and fixing these super-emitters.