Spatiotemporal Variability of Methane Emissions at Oil and Natural Gas Operations in the Eagle Ford Basin

• Main Authors: Lavoie, Tegan, Shepson, Paul B, Cambaliza, Maria Obiminda L, Stirm, Brian H, Conley, Stephen A, Mehrota, Shobhit, Faloona, Ian C, Lyon, David
• Format: text
• Published: Archīum Ateneo 2017
• Subjects: Wind; Lipids; Natural resources; Cluster chemistry; Computer simulations; Atmospheric Sciences
• Online Access: https://archium.ateneo.edu/physics-faculty-pubs/36; https://pubs.acs.org/doi/10.1021/acs.est.7b00814
• Institution: Ateneo De Manila University

Methane emissions from oil and gas facilities can exhibit operation-dependent temporal variability; however, this variability has yet to be fully characterized. A field campaign was conducted in June 2014 in the Eagle Ford basin, Texas, to examine spatiotemporal variability of methane emissions using four methods. Clusters of methane-emitting sources were estimated from 14 aerial surveys of two (“East” or “West”) 35 × 35 km grids, two aircraft-based mass balance methods measured emissions repeatedly at five gathering facilities and three flares, and emitting equipment source-types were identified via helicopter-based infrared camera at 13 production and gathering facilities. Significant daily variability was observed in the location, number (East: 44 ± 20% relative standard deviation (RSD), N = 7; West: 37 ± 30% RSD, N = 7), and emission rates (36% of repeat measurements deviate from mean emissions by at least ±50%) of clusters of emitting sources. Emission rates of high emitters varied from 150–250 to 880–1470 kg/h and regional aggregate emissions of large sources (>15 kg/h) varied up to a factor of ∼3 between surveys. The aircraft-based mass balance results revealed comparable variability. Equipment source-type changed between surveys and alterations in operational-mode significantly influenced emissions. Results indicate that understanding temporal emission variability will promote improved mitigation strategies and additional analysis is needed to fully characterize its causes.