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Methane leak near real time quantification with a hyperspectral infrared camera

高光谱成像 甲烷 像素 遥感 环境科学 云计算 泄漏 无组织排放 点云 计算机科学 温室气体 计算机视觉 地质学 环境工程 化学 操作系统 海洋学 有机化学
作者
Xavier Watremez,Stéphanie Doz,Pierre‐Yves Foucher
标识
DOI:10.1117/12.2304819
摘要

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
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