Editor & Publisher, Marcellus Drilling News (MDN)
[Editor’s Note: Great news! New technology in the form of software promises to help identify sources of methane leaks and continue their reduction.]
Researchers with the Dept. of Energy’s (DOE) Los Alamos National Laboratory (LANL) in New Mexico continue to make big oil and gas industry breakthroughs. Two weeks ago we told you about LANL’s breakthrough discovery about pressures used when fracking in the Marcellus (see DOE Marcellus Research Finds High Frack Pressure Keeps Gas Trapped). A different group of LANL researchers have discovered a way to sniff out fugitive methane leaks, perhaps cutting emissions up to 90%.
Believe it or not, the discovery made by the researchers is not new hardware, it’s not a new device but instead is new software/computer programming. Three LANL researchers are using “machine learning codes” (artificial intelligence) to analyze speed and wind direction of methane leaks and trace them back to the point of origin. The software uses existing equipment that detects the presence of methane.
Methane leaks, sometimes called fugitive methane, have been and continue to be an issue the gas industry is trying to address. This new discovery takes us leaps and bounds ahead toward solving the issue. Frankly, we don’t care two hoots about plugging methane leaks to save Mom Earth from toasting (cockamamie fairy tale). We care about finding and plugging leaks because every molecule of methane we save we can sell! From Forbes:
Scientists at Los Alamos National Laboratory have developed new technology that they say could reduce emissions of methane, a powerful greenhouse gas, by up to 90%.
In work funded by the US Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E), a team of three has devised machine learning codes that analyze the speed and direction of wind currents to trace methane leaks back to their sources.
The only real hardware involved is a small methane sensor developed by a California startup, Aeris Technologies, Inc. — although the scientists’ algorithms can be used to analyze the data coming off almost any gas and wind sensor, including, potentially, sensors attached to cars or drones.
Currently available methods to detect methane leaks, such as infrared scanners, are cost-prohibitive at scale. The new technology raises the possibility that a network of methane-sniffing sensors at oil and gas facilities could be used to generate real-time methane leak maps, giving firms the ability to dispatch technicians to stanch leaks almost as soon as they occur…
So far, the technology … can estimate the location and size of leaks anywhere inside roughly 100 meters, although its accuracy will improve as the algorithms receive more “training” through virtual simulations and actual use…
Currently available technologies used to detect methane leaks are too expensive to use with great frequency; oil and gas firms will often check for methane leaks in a given area of their facilities only once every few months. When they do, it may mean simply driving around with infrared sensors that make methane visible to the human eye — hardly an ideal strategy.
But growing attention on the problem is galvanizing new solutions. A number of firms are now exploring the use of drones to continually monitor and scan for emissions. And in an even more recent development, a handful of startups are now scanning for methane emissions from space. That technique has proved effective at identifying very large leaks and offers hope that the biggest methane releases can be stanched…
The oil and gas industry is ready to get on board. Unlike some aspects of their operations, a number of large oil and gas firms aren’t vigorously contesting the public pressure they face to take action on methane emissions. Rising publicity around the issue threatens to further damage their public image, and they also have a financial incentive: methane may not be as lucrative as natural gas or oil, but it can still make plenty of money when sold on the market…
The team is calling their technology Autonomous, Low-cost, Fast Leak Detection System (ALFaLDS).
The researchers recently published the results of their work in the journal Atmospheric Environment: X. And, here is the video: