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OIL PIPELINE STANDOFF LEAK DETECTION/A NOVEL APPROACH FOR AIRBORNE REMOTE DETECTION OF SMALL LEAKS

机译:石油管道梯级泄漏检测/小型泄漏空气远程检测方法

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While natural gas pipelines already benefit from airborne, remote detection of leaks [1, 2], oil pipeline leak detection has been for a long time reliant on SCADA systems limited in their capability to detect very small leaks, and/or visual inspection of the right of way (line flyers, pipeline employees or members of the public). This paper presents a novel and complementary way of detecting small leaks (i.e. sensitivity of 0.1 L/minute, 1 barrel/day) of oil (crude or refined products) using an optical detection system mounted on an airborne platform (UAV, plane or helicopter). The scope of this paper is based on the requirements provided by TransCanada, namely sensitivity (herein referred as LOD - Limit of Detection) and accuracy (herein referred as spatial resolution) as similar to their description in API 1130, while the topic of reliability is addressed in our noted concerns on the false alarms that may be generated in Infrared-DiAL based systems due to soil reflectivity. Robustness, as described in API 1130, was out of scope. Keeping in mind the requirement of airborne operation, three different approaches for the detection of leaks along long pipeline ROWs were studied. Infrared Differential Absorption lidar (IR-DiAL), UltraViolet Raman lidar (UV-Raman lidar) and UltraViolet Laser-Induced Fluorescence lidar (UV-LIF lidar) have been tested in realistic conditions. In the first round of tests, laboratory spectral measurements of vapors in a closed cell were performed. In the second round of tests, the breadboards were placed in a mobile laboratory and the light beams aimed at a large open at 40 to 50 meters and reflected off a sand target. Finally, the mobile laboratory with the breadboards was installed at ~40 meters from a leak simulator. The leak simulator was made by using a large sand container in which petroleum products were leaked. Intermediate scale leak simulator tests showed that it is clearly a challenge to correlate a measured concentration to an actual leak size. Tests have also shown that there is a strong concentration gradient in the air above a leak. This indicates that a better overall detection performance should be obtained with a measurement using the air next to the ground, and that it is feasible to detect a leak of less than 1 barrel/day. UV-Raman tests performed in the outdoors suggested a Limit Of Detection (LOD) of the system below 1 500 ppm-m when detecting all hydrocarbons. Because of the hardware that would be needed to lower this detection limit, results suggest abandoning the Raman technique for remote leak detection from an airborne platform. IR-DiAL showed the best sensitivity for the detection of hydrocarbons (<1 ppm-m of LOD). However the effective LOD will be reduced because of the soil spectral reflectance variations that may lead to a high false alarm rate for concentrations of hydrocarbons lower than 235 ppm-m. The UV-absorption approach was also briefly tested, suggesting a LOD for benzene of between 1.5 and 2.5 ppm-m. The UV absorption of benzene is not affected by ground spectral reflectance variations. This is an approach that will be investigated further.
机译:虽然天然气管道已经受益于空中,但远程检测泄漏[1,2],油管泄漏检测已依靠Scada Systems在其能力中依据以检测非常小的泄漏,和/或视觉检查路上(线传单,管道雇员或公众成员)。本文介绍了使用安装在机载平台(UAV,平面或直升机的光学检测系统(UAV,平面或直升机)检测油(即0.1L /分钟,1桶/分钟,1桶/天)的油(原油或精制产品)的小泄漏(即0.1升/分钟,1桶/天)的小说和互补方法)。本文的范围是基于Transcanada提供的要求,即敏感性(本文称为检测LOD限制)和准确性(这里称为空间分辨率),与API 1130中的描述类似,而可靠性的主题是由于土壤反射率,我们对可能在基于红外拨号系统中产生的误报的担忧。如API 1130中所述,鲁棒性超出了范围。请记住空中操作的要求,研究了三种不同的沿长管道行检测泄漏方法。在现实条件下测试了红外差分吸收激光雷达(IR-Direm),紫外线拉曼延伸率(UV-Raman Lidar)和紫外线激光诱导的荧光延长率(UV-LiF-LiF-LiF-LiF-LiDar)。在第一轮测试中,进行闭孔中的蒸汽的实验室光谱测量。在第二轮测试中,将面包板放置在移动实验室和光束上,该光束以40至50米的大开口,并反射砂靶。最后,移动实验室与面包板安装在距离泄漏模拟器40米处。通过使用大型砂容器来制造泄漏模拟器,其中石油产品泄漏。中间尺度泄漏模拟器测试表明,将测量的浓度与实际泄漏尺寸相关联而有。测试还表明,在泄漏的空气中存在强的浓度梯度。这表明应使用地面旁边的空气测量获得更好的整体检测性能,并且可以检测泄漏/天的泄漏是可行的。在户外进行的UV-Raman测试在检测到所有烃时,在100ppm-m以下的系统的检测(LOD)的极限表示。由于降低该检测限需要的硬件,结果表明,放弃了从空中平台遥控泄漏检测的拉曼技术。 IR表盘显示出检测烃的最佳敏感性(<1 ppm-m of lod)。然而,由于土壤光谱反射率变化,将减少有效的LOD可能导致高于235ppm-m的碳氢化合物浓度的高误报率。紫外线吸收方法也短暂测试,表明苯的苯含量为1.5和2.5ppm-m。苯的UV吸收不受地面光谱反射变化的影响。这是一种将进一步调查的方法。

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