Aerial Survey Sample Size Requirements for Robust Methane Inventories in the Upstream Oil and Gas Industry

Abstract

Accurate and frequent measurement-based inventories of methane emissions from the upstream oil and gas (UOG) industry are crucial to developing and implementing effective regulations and achieving sustainable mitigation.  Recent advances in the analysis of large-scale survey data have enabled measurement-based basin/jurisdiction-level methane inventories from remote surveys of UOG infrastructure.  Treating like facility or well types as strata within a larger sample and leveraging analytics that consider measurement uncertainties, probabilities of detection, empirical (non-smooth) source distributions, and sample size effects, specific conclusions can be derived in the context of measurement sensitivities and uncertainties.  These analyses provide useful insights to regulators and industry, including but not limited to the individual contributions of equipment types to overall methane emissions.  However, a priori design and optimization of surveys to cost-effectively derive measurement-based inventories and ensure survey coverage can achieve acceptable levels of uncertainty remains a key challenge.  Here, we present an analysis of data from extensive aerial LiDAR and ground-based surveys of UOG facilities in Western Canada to provide much-needed guidance on source- and facility-specific sampling protocols for the UOG industry.  Insights into the temporal intermittency and variability of source rate magnitudes are derived using a statistically robust method that considers the quantification accuracy and probability of detection function of the aerial instrument.  Results provide important context regarding the required survey coverage of aerially detectable sources (greater than approximately 1 kg/h) to support the development of accurate inventories, defensible frequencies of regulated inspections, and alternative leak detection and repair programs.