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Detection Limits of Optical Gas Imaging for Natural Gas Leak Detection in Realistic Controlled Conditions Colorado
Citation:
Zimmerle, D., T. Vaughn, C. Bell, K. Bennett, R. Tullberg, E. Thoma, J. Dewees, AND P. Deshmukh. Detection Limits of Optical Gas Imaging for Natural Gas Leak Detection in Realistic Controlled Conditions Colorado. Presented at 2019 Air and Waste Management Association’s Air Quality Measurements and Methods Conference, Durham, NC, April 02 - 04, 2019.
Impact/Purpose:
Energy production operations, refineries, chemical plants, and other industries and waste facilities can emit air pollutants and odorous compounds from fugitive leaks, process malfunctions, and area sources that are hard to detect and manage. From the shared perspective of industries, regulators, and communities, improved understanding of stochastic industrial sources (SIS) can yield many benefits such as safer working environments, cost savings through reduced product loss, lower airshed impacts, and improved community relations. The emergence of lower-cost sensors and inverse modeling approaches, is enabling new cost-effective ways to detect and analyze SIS emissions. Under its next generation emissions measurement (NGEM) program, EPA is working with a range of partners to develop and test NGEM tools that can assist facilities in detection and management of sources. As described in the below abstract, the following product contributes to the general advancement and communication of NGEM concepts.
Description:
The following is an extended abstract supporting a presentation at the 2019 Air and Waste Management Association’s Air Quality Measurements and Methods Conference in Durham, NC, April 2-4 2019. Abstract: Optical gas imaging (OGI), primarily utilizing video cameras filtered to mid-IR wavelengths, is a well-accepted method of detecting leaks in natural gas systems. Several studies have assessed the ability of current cameras to visualize natural gas plumes in laboratory and field conditions. In practice, camera technology is deployed in a wide range of field conditions by operators who vary in training and experience. Few studies have quantified the leak detection capabilities of the camera-operator system in realistic conditions, and none have been completed in fully controlled conditions where leaks locations and rates were precisely known on realistic equipment. In this paper we summarize results from 30 days of OGI system testing at the Methane Emissions Technology Evaluation Center at Colorado State University. Camera operators from internal and contract teams, regulators, and manufacturers participated in single blind leak detection trials with leaks ranging from 1-20 scfh, emitted from realistic well pad equipment. We find that leak detection rates are lower than previously reported for small leak sizes, and 100% detection is not achieved for any of the emission rates tested. Detection rates also drop with increasing wind, across all leak sizes, but with disproportionate impact on smaller leak sizes. Some differences in detection rates between OGI operator groups were noted and are explained in part by training level and field protocols utilized. Results from this testing are critical to understand the efficacy of new, automated, lead detection methods which are proposed as replacements for current OGI surveys and to contribute to best practices and training for manual inspection.