Browsing by Subject "Methane emissions from oil and gas operations"

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Uncertainty and reconciliation of multi-scale measurements of methane emissions from oil and gas facilities
(2024-05) Schissel, Colette; Allen, David T.; Hildebrandt Ruiz, Lea; Korgel, Brian; Tullos, Erin; Ravikumar, Arvind
Methane emissions from oil and natural gas facilities contribute significantly to global greenhouse gas emissions. Identifying pathways for emission reductions relies on accurate emission accounting across different spatial and temporal scales, from the source-level, which guides mitigation strategies, to the global-level in order to benchmark reduction progress. Regulatory and voluntary reporting initiatives are moving towards measurement-informed methane emission inventories, as recent studies have determined that generic estimation methods tend to underestimate emissions. Methane measurements can be used to account for changes in operation or equipment that lead to emission reductions, and to identify and quantify large emission events that contribute significantly to overall emissions. Measurement technologies span a wide spatiotemporal range, providing many different types of data. Measurement data can range from weekly satellite column concentration measurements to near-continuous source-level flowmeter data. Multi-scale measurements are an important part of advancing methane reporting and mitigation initiatives, as different forms of technology are optimal for observing different types of emissions. Estimates from different measurements will likely never precisely agree, which is both a function of technology diversity and the underlying variability of the emissions themselves. Uncertainty quantification of methane measurements is a necessary step in reconciling multi-scale measurements for the construction of measurement-informed inventories. Accurate interpretation of measurement data requires uncertainty quantification, which can contextualize measurements and estimates against one another. This thesis identifies the types of uncertainty that arise when methane measurements are used in the construction of annual inventories. This work proposes frameworks to quantify different types of extrapolation uncertainty through a series of case studies in the Barnett Shale, Permian Basin, and Green River Basin. This work also proposes metrics that can be used to inform methane measurement campaign design in order to minimize extrapolation uncertainty and improve the statistical significance of collected data.