Operational methane emission detection and quantification in oil and gas facilities through integrating multiple sources of data via scientific machine learning and physics-based techniques

This project aims to identify sources of fugitive methane emissions and quantify their magnitude. It is based on an integrated approach that augments measured data with other sources of information. The computational framework combines physics-based and scientific machine learning-based approaches to maximize the suitability of the developed tool.