Methane leak near real time quantification with a hyperspectral infrared camera
Abstract
In the case of accidental methane leakage on a gas production industrial site, it is essential that the risks associated with an explosion of escaped clouds are assessed. By combining spectral and spatial information, hyperspectral technology is an attractive solution for the detection of such a cloud and for the quantification of its concentration. Total has started in 2014 a research program in partnership with Onera, called NAOMI (New Advanced Observation Methods Integration) to develop new tools for remote characterization of accidental methane plumes, especially over areas inaccessible to the personnel. From one of the results of this partnership, Onera is developing an algorithm, IMGSPEC, especially designed for this purpose, using hyperspectral acquisitions in the LWIR domain. The principle of IMGSPEC consists of estimating the spectral transmission of the gas cloud using an image of the background. An acquisition image of the same scene without gas is not necessarily available however. The strong point of the algorithm is its ability to recover the signal of the background. The integrated concentration is subsequently estimated pixel by pixel constituting a ppm.m concentration map. Finally, the flow rate of the leak is calculated considering the mass of the cloud, combining concentration estimation and methane density, and the wind speed which is measured with a meteo-station for instance. This algorithm was tested in June during a specific test campaign on the Lacq platform, a Total R and D industrial site. Methane leaks have been performed regulating the following flow rates: 1g/s, 10 g/s and 100g/s. Flow rate was estimated by IMGSPEC in near real-time following hyperspectral datacube acquisitions. Acquisition and processing times were both 4s, constituting a global flow rate estimation time below 10s
- Publication:
-
Thermosense: Thermal Infrared Applications XL
- Pub Date:
- May 2018
- DOI:
- 10.1117/12.2304819
- Bibcode:
- 2018SPIE10661E..03D