The role(s) of remote sensing in reducing methane emissions from the oil and gas supply chain

Success in achieving the oil and gas methane emission reduction targets of industry, state and federal governments, and the Global Methane Pledge will critically depend on access to emissions data that is actionable, complete and trustworthy. Despite recent improvements, current methane monitoring systems are still limited in their ability to offer timely delivery of precise, quantitative, and reproducible emissions data to facility operators, regulators, front-line communities and other stakeholders. There are multiple use-cases for accelerating data-enabled methane mitigation including but not limited to leak detection and repair programs, diagnostics to guide process emission reductions and infrastructure model improvements, emissions trending, and supply-chain methane intensity certification. Each of these use-cases translate to specific requirements on methane data products and the observational and analytic frameworks that deliver them. Meanwhile, a nascent global system of systems for operational methane emissions monitoring is emerging that offers the potential to synergistically combine observations from multiple sensor types, vantage points, and quantification methods. Additionally, new programs offering improved data access, transparency, independent validation, 3rd party reporting, and user capacity-building are also gaining traction.

Methane remote sensing offers unique contributions to the expanding tiered observing system. Satellites in particular can complement continuous data from surface sensors at selected facilities and periodic regional airborne surveys by providing dense and sustained sampling of diverse jurisdictions globally without being constrained by access restrictions. We discuss the impact potential and limitations of the expanding global constellation of methane satellites with regards to reducing oil and gas emissions. We present use-cases including satellite contributions to a flexible "matrix approach" regarding alternative screening methods for super-emitters as well as improvements in timeliness, completeness and quantitative estimation. We also describe some pilot studies involving collaborative data sharing between researchers, regulators and operators that resulted in measurable and verifiable emission reductions.