AI-Based Methane Monitoring Boosts Oil and Gas Companies' Energy Transition
The launch in Europe in mid-April of a new gas cloud imaging system from US technology company Honeywell will reveal the ability of artificial intelligence systems to improve safety at oil and gas installations.
The launch in Europe in mid-April of a new gas cloud imaging (GCI) system from US technology company Honeywell will reveal the ability of artificial intelligence (AI) systems to improve safety at oil and gas installations.
The GCI system will provide automated and continuous monitoring for leaks of dangerous and polluting gases such as methane at oil and gas, chemical, and power-generation facilities across Europe.
Part of the Honeywell Rebellion gas cloud imaging product portfolio, the Mini GCI is a compact device designed for congested areas and small sites. These systems can be placed throughout an industrial facility to continuously monitor for gas leaks and provide alerts as soon as they occur.
The company said reducing gas emissions such as methane from hydrocarbon operations was one the most cost-effective and impactful methods to help reach global climate and environmental goals. Methane is more than 80 times more potent in trapping heat than carbon dioxide after 20 years, said the US Environmental Defense Fund.
Honeywell said the system, powered by proprietary hyperspectral gas analytics using AI, provides facility operators with an easy-to-interpret, colored visualization of the gas plume type, location, direction, size and concentration. This allows for an earlier and more effective response before leaks have the chance to grow into bigger emissions or safety issues.
Honeywell's system provides continuous monitoring and offers real-time analytics to see and measure concentrations of the leaked gases. Using hyperspectral sensors, the system can see an optical "fingerprint" of the gas cloud, which makes it possible to differentiate multiple gas types.
AI is key to its success, said Robert Kester, president and general manager, Honeywell Rebellion. “The machine learning analytics developed by our AI engineers use algorithms to combine the data from visual and hyperspectral sensors to provide an easy-to-interpret visualization of methane and other gas emissions, which are often invisible to the human eye. Additionally, the algorithms are able to provide location, size, and concentration data of the gas cloud emitted. Our analytics can see the infrared ‘fingerprint’ of a gas cloud, enabling it to differentiate between actual gas emissions and false alarms,” he said
Honeywell's gas cloud imaging system has been deployed by more than 25 major energy and chemicals customers globally.