From Event: SPIE Commercial + Scientific Sensing and Imaging, 2017
This paper reports a novel quantitative gas plume imaging tool, based on active near-infrared Backscatter Tunable Diode Laser Absorption Spectroscopy (b-TDLAS) technology, designed for upstream natural gas leak applications. The new tool integrates low-cost laser sensors with video cameras to create a highly sensitive gas plume imager that also quantifies emission rate, all in a lightweight handheld ergonomic package. It is intended to serve as a lower-cost, higherperformance, enhanced functionality replacement for traditional passive non-quantitative mid-infrared Optical Gas Imagers (OGI) which are utilized by industry to comply with natural gas infrastructure Leak Detection and Repair (LDAR) requirements. It addresses the need for reliable, robust, low-cost sensors to detect and image methane leaks, and to quantify leak emission rates, focusing on inspections of upstream oil and gas operations, such as well pads, compressors, and gas plants. It provides: 1) Colorized quantified images of path-integrated methane concentration. The images depict methane plumes (otherwise invisible to the eye) actively interrogated by the laser beam overlaid on a visible camera image of the background. The detection sensitivity exceeds passive OGI, thus simplifying the manual task of leak detection and location; and 2) Data and algorithms for using the quantitative information gathered by the active detection technique to deduce plume flux (i.e. methane emission rate). This key capability will enable operators to prioritize leak repairs and thereby minimize the value of lost product, as well as to quantify and minimize greenhouse gas emissions, using a tool that meets EPA LDAR imaging equipment requirements.
Richard T. Wainner, Nicholas F. Aubut, Matthew C. Laderer, and Michael B. Frish, "Scanning, standoff TDLAS leak imaging and quantification," Proc. SPIE 10210, Next-Generation Spectroscopic Technologies X, 1021006 (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 10, 2017; Published: 5 May 2017); https://doi.org/10.1117/12.2264799.
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