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首页> 外文期刊>Journal of loss prevention in the process industries >Dispersion modeling approach for quantification of methane emission rates from natural gas fugitive leaks detected by infrared imaging technique
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Dispersion modeling approach for quantification of methane emission rates from natural gas fugitive leaks detected by infrared imaging technique

机译：弥散建模方法，用于量化红外成像技术检测到的天然气逃逸泄漏中的甲烷排放速率

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Recently, infrared optical imaging has been applied in the oil and gas industry as a method to detect potential leaks in pipelines, components and equipment. The EPA suggested that this impending technique is considered as a smart gas LDAR (leak detection, monitoring and repair) for its rapid recognition of leaks, accuracy and robustness. In addition, compared to the conventional method using Total Vapor Analyzer (TVA) or gas sniffer, it has several other advantages, such as the ability to perform real-time scanning and remote sensing, ability to provide area measurement instead of point measurement, and provide an image of the gas which is not visible to naked eye. However, there is still some limitation in the application of optical imaging techniques; it does not give any measurement of gas emissions rates or concentrations of the leaking gas. Infrared cameras can recognize a target gas and distinguish the gas from its surrounding up to a certain concentration, namely the minimum detectable concentration. The value of the minimum detectable concentration depends on the camera design, environmental conditions and surface characteristics when the measurement is taken. This paper proposed a methodology to predict gas emissions rates from the size of the dispersed gas plume or cloud to the minimum detectable concentration. The gas emissions rate is predicted from the downwind distance and the height of the cloud at the minimum detectable concentration for different meteorological conditions. Gas release and dispersion from leaks in natural gas pipeline systems is simulated, and the results are presented.
机译：近来，红外光学成像已在石油和天然气工业中用作检测管道，组件和设备中潜在泄漏的方法。 EPA建议将这种迫在眉睫的技术视为一种智能气体LDAR（泄漏检测，监视和维修），因为它可以快速识别泄漏，准确性和鲁棒性。此外，与使用总蒸气分析仪（TVA）或气体嗅探器的传统方法相比，它还具有其他一些优点，例如能够执行实时扫描和遥感，能够提供面积测量而不是点测量的功能以及提供肉眼不可见的气体图像。但是，光学成像技术的应用仍然存在一些局限性。它不提供任何气体排放率或泄漏气体浓度的度量​​。红外热像仪可以识别目标气体，并从周围环境中分辨出一定浓度（即最小可检测浓度）的气体。最小可检测浓度的值取决于相机设计，环境条件和进行测量时的表面特性。本文提出了一种方法来预测从散发的烟羽或云的大小到最小可检测浓度的气体排放率。在不同的气象条件下，可从顺风距离和最小检测浓度下的云层高度预测气体排放率。模拟了天然气管道系统中泄漏引起的气体释放和扩散，并给出了结果。

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