Optimized inspection of upstream oil and gas methane emissions using airborne LiDAR surveillance. (1st October 2020) - Rashid, Kashif; Speck, Andrew; Osedach, Timothy P.; Perroni, Dominic V.; Pomerantz, Andrew E.
Graphical abstract: Highlights: Reducing oilfield methane emissions is among the fastest ways to slow climate change. Main technical challenge to reduce those emissions is locating emission sources. Here we describe a monitoring program based on aerial LiDAR surveillance. Solve vehicle routing problem to optimize routes covered by airborne sensors. Potential to reduce both methane emissions and inspection costs simultaneously. Abstract: Methane is a short-lived climate pollutant responsible for approximately 20% of anthropogenic global warming, and reducing methane emissions from the oil and gas (O&G) industry is considered among the most urgent and actionable measures to mitigate climate change. Recent reports suggest a large fraction of upstream O&G methane emissions result from a small number of super-emitter facilities, emphasizing the value of novel methods that inspect O&G facilities with greater frequency than is practical using existing techniques. Here we describe an optimized method wherein O&G facilities are inspected for emissions at high frequency and high sensitivity using active laser (LiDAR) sensors mounted to aircraft. The method relies on a hierarchical clustering and routing procedure to establish optimal routes to be flown by aircraft departing from local airports and equipped with LiDAR methane sensors. Routes are optimized to inspect all well sites subject to emissions regulation in three O&G intensive regions: the Permian basin, the state of Colorado, and the state of Pennsylvania. While some cost estimates require additional field data, these modeling results suggest the optimized inspections can be performed with comparable effectiveness and up to a factor of six lower cost per inspection compared to current detection methods. The cost per inspection required to achieve equivalent emissions reduction depends on factors such as the weather conditions during inspection (which impacts the limit of detection and therefore the inspection frequency required to achieve equivalency) and the well density (which impacts the flying distance), and the advantage of this program over traditional inspection will be reduced under unfavorable conditions. These modeling results suggest that optimized routing may enable frequent inspection of upstream O&G facilities at large scale and potentially lead to a substantial decrease in both oilfield methane emissions and compliance costs borne by industry.