Estimating methane emissions from the upstream oil and gas industry using a multi-stage framework

Abstract Measurement-based methane inventories, which involve surveying oil and gas facilities and compiling data to estimate methane emissions, are becoming the gold standard for quantifying emissions. However, there is a current lack of statistical guidance for the design and analysis of such surveys. We provide a method for estimating inventories that are simple to interpret and compute by framing methane surveys in the context of multi-stage sampling designs. We contribute estimators of the total emissions along with variance estimators which do not require simulation, as well as stratum-level total estimators. We show that the variance contribution from each stage of sampling can be estimated to inform the design of future surveys. We also introduce a more efficient modification of the estimator. To model measurement error, we propose combining the multi-stage approach with a simple Monte Carlo procedure. The resulting methods are interpretable and require minimal computational resources. We conduct a simulation study to investigate the statistical properties of the proposed methods. Finally, we apply the methods to aerial survey data of oil and gas facilities in British Columbia, Canada, to estimate the methane emissions in the province. An R package is provided to facilitate the use of the methods.