Multiscale Oil and Gas Methane Emissions Data: From Measurements to Mitigation

Abstract

Abstract Methane (CH4) is a potent greenhouse gas, responsible for at least a quarter of Today's global warming. Thus, reducing CH4 emissions from global oil and gas infrastructure represents a key opportunity to significantly slow the rate of climate change—with several recent studies highlighting that readily available and cost-effective technologies can reduce a large fraction of current emissions from this industry. Operators have announced ambitious pledges to reduce CH4 emissions from the oil and gas supply chain. For these targets to be effective, it is critical to improve the understanding in terms of how much methane emitted, identify where it is being emitted, and to empirically track progress as mitigation strategies are implemented. Here, we have synthesized results from recent multi-scale scientific studies across geographies (i.e., North America, Europe, Australia), highlighting the role of empirical data in improving emission reporting, and guiding mitigation action. We illustrate how emissions data collected at different spatial and temporal scales can be integrated to provide a clear characterization across the different segments of the oil and gas supply chain. Measurement-based approaches are now being successfully implemented, and the integration and reconciliation of data at different scales can provide useful information to reduce the uncertainty in terms of magnitude and location of emissions. As more operators incorporate these approaches and compile improved emissions data, it will be plausible to improve equipment and system design, perform root cause analysis and reduce the frequency of large emission events. Measurement-based CH4 emissions data is essential to an efficient and effective implementation of CH4 mitigation strategies. This paper highlights how a diversity of robust measurement approaches can be deployed in concert—further identifying mitigation opportunities and tracking changes in emissions over time.