Methods for spatial extrapolation of methane measurements in constructing regional estimates from sample populations

Reporting initiatives for methane emissions from oil and gas operations are broadly shifting towards measurement-informed inventories. Measurement campaigns typically measure a subpopulation of facilities, and these measurements are extrapolated to a larger region or basin. Methane emissions from oil and gas systems are inherently variable and intermittent, which makes it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work proposes a framework using a case study of an operator in the Green River Basin that assesses selection of sample populations, extrapolation of measurements to a larger region, and methods for estimating the error associated with extrapolation. This work also identifies a new metric, the capture ratio, which has a strong correlation with extrapolation error (Spearman’s correlation coefficient = -0.75). The strength of this correlation between the capture ratio, which takes into account the skewness of source-level emissions, and extrapolation error suggests that understanding the distributions of source-level emissions distributions is necessary when identifying sample populations and extrapolating measurements. The results from this work can be broadly applied to inform the selection and extrapolation of site measurements when developing methane emission inventories.