Science Inventory

Detection Limits of Optical Gas Imaging for Natural Gas Leak Detection in Realistic Controlled Conditions August 2020

Citation:

Zimmerle, D., T. Vaughn, C. Bell, K. Bennett, E. Thoma, J. Dewees, AND P. Deshmukh. Detection Limits of Optical Gas Imaging for Natural Gas Leak Detection in Realistic Controlled Conditions August 2020. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY. American Chemical Society, Washington, DC, 54:18, (2020). https://doi.org/10.1021/acs.est.0c01285

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. Under its next generation emissions measurement (NGEM) program, the U.S Environmental Protection Agency (EPA), Office of Research and Development (ORD), Center of Environment Measurement and Modeling (CEMM) 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, Optical Gas Imaging (OGI) is an important NGEM technique for finding fugitive industrial emissions (leaks) of methane and volatile organic compounds. The ability of OGI to detect leaks depends on many factors including the skill and training of the OGI operator. This dataset was produced at the Colorado State University Methane Emissions Test and Evaluation Center (METEC) where simulated leaks of various sizes from oil and gas production equipment could be generated. Dozens of OGI operators from different organizations with various levels of experience participated in a test series to establish their ability to detect leaks under varying conditions using the protocols and procedures they normally employ. This Publication describes the results from this test series that advanced understanding of OGI methods and training.

Description:

Increasing production of natural gas has driven interest in identifying and reducing emissions of methane, the primary component of natural gas and a powerful greenhouse gas. Optical gas imaging (OGI) is commonly utilized as a leak detection method in the upstream and midstream sectors of the U.S. natural gas industry. The method utilizes a video camera filtered to an absorption band of methane to image and detect natural gas emissions. This study characterized the detection efficacy of OGI surveyors, using their own cameras and protocols, with controlled releases in an 8-acre outdoor facility that closely resembles upstream natural gas field operations. Professional surveyors from 16 oil and gas companies and 8 regulatory agencies participated in the testing, completing 488 tests over a 10 month period. Overall, detection performance in this study was significantly lower than prior studies: The leak size required to achieve a 90% probability-of-detection in this study is an order-of-magnitude larger than prior studies focused on camera performance. Study results indicate that prior OGI survey experience has a significant impact on leak detection rate: Surveyors from gas companies and their contractors who had surveyed more than 400 sites prior to testing detected 1.7 [1.5 to 1.9] times more leaks than surveyors who had completed 10 - 400 prior surveys. Qualitative and quantitative results suggest that more experienced operators better adjust their survey speed to site conditions, examine components from multiple view-points, and make other adjustments that improve their leak detection rate, indicating that adjustments to company survey protocols and targeted training could improve leak detection rates overall.

Record Details:

Record Type: DOCUMENT ( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date: 09/15/2020
Record Last Revised: 06/11/2021
OMB Category: Other
Record ID: 349745