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Workshop: NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning: Blending New and Existing Knowledge Systems

Artificial Intelligence for Methane Mitigation : Through an Automated Determination of Oil and Gas Methane Emissions Profiles

Jade Eva Guisiano · Thomas Lauvaux · Eric Moulines · Jérémie Sublime


The oil and gas sector is the second largest anthropogenic emitter of methane, which is responsible for approximately 25% of global warming since pre-industrial times. In order to mitigate methane atmospheric emissions from oil and gas industry, the potential emitting infrastructure must be monitored. Initiatives such as the Methane Alert and Response System (MARS), launched by the United Nations Environment Program, aim to locate significant emissions events, alert relevant stakeholders, as well as monitor and track progress in mitigation efforts. To achieve this goal, an automated solution is needed for consistent monitoring across multiple oil and gas basins around the world. Most methane emissions analysis studies propose post-emission analysis. The works and future guidelines presented in this paper aim to provide an automated collection of informed methane emissions by oil and gas site and infrastructure which are necessary to dress emission profile in near real time. This proposed framework also permits to create action margins to reduce methane emissions by passing from post methane emissions analysis to forecasting methods.

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