Methane emission detection, localization, and quantification using continuous point-sensors on oil and gas facilities
Date:
Abstract: Reducing methane emissions is a key component of short-term climate action. The oil and gas sector provides a promising avenue for methane emission reduction, as it accounts for 22% of global anthropogenic methane emissions and 32% within the U.S. We propose a generic, modular framework for emission event detection (estimate emission start and end time), localization (estimate emission source), and quantification (estimate emission rate) on oil and gas facilities. The framework uses methane concentration and wind speed and direction data collected by continuous point-sensors. The framework is separated into four steps: 1) background removal and event detection, 2) atmospheric transport simulation, 3) source localization, and 4) emission rate quantification. We evaluate our framework by testing it on a set of 85 controlled releases that vary in duration and size. The framework identifies all controlled releases, with 82% being localized correctly. 90% of small events (<= 1kg/hr) are quantified within an error range of [-78.1%, 178.6%], while 90% of large events (> 1kg/hr) are quantified within an error range of [-49.6%, 77.4%]. Based on the framework’s performance, it appears to be useful for near real- time alerting for rapid emissions mitigation and emission quantification for data-driven inventory estimation on oil and gas production sites.
Poster