Methane Detection using Optical Gas Imaging: Passive Infrared Technology

Methane (CH 4 ) is the dominant constituent of natural gas and plays a significant role in climate change as a powerful greenhouse gas. CH 4 lingers 30 times more than CO 2 in the atmosphere and has a greater potency in trapping heat. Human activities such as Oil and Gas production, underground mining, and landfill activities contribute to 25% to 33% of global warming worldwide. Traditional methods often lack real-time and accurate monitoring capabilities. To reduce the effect of methane emissions on global warming, several research works have demonstrated the efficiency of Passive Infrared Optical Gas Imaging in methane detection and quantification, which is widely used in Leak Detection and Repair programs (LDAR) as a non-destructive and non-invasive method. The combination of Machine Learning procedures such as Faster Region Convolutional Neural Network (Faster R-CNN) along with thermal infrared cameras was proven to be effective for methane detection and quantification. However, challenges remain in accurately determining emission rates. Recent studies have also revealed that methane emissions estimates provided by agencies like the Environmental Protection Agency (EPA) are often significantly underestimated. Recently, several detection projects demonstrated that the estimates the Environment Protection Agency (EPA) provided are underestimated. This paper explores the integration of machine learning models with optical gas imaging, examining methodologies, results, and limitations in methane detection across the petroleum industry, underground mining, and landfill sectors. Future research directions include improving detection algorithms to enhance accuracy under varying environmental conditions, developing lower-cost sensor technologies for widespread deployment, and addressing regulatory challenges to ensure consistent and reliable methane reporting practices. This addition outlines promising future research areas and emphasizes key technical and regulatory challenges that must be addressed to advance methane monitoring capabilities. Keywords: Greenhouse gas emissions, methane detection and quantification, Optical Gas Imaging, Infrared Technology, Faster R-CNN. DOI : 10.7176/JETP/14-3-05 Publication date : October 30th 2024