1. Equipment leak detection and quantification at 67 oil and gas sites in the Western United States
- Author
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Adam P. Pacsi, Tom Ferrara, Kailin Schwan, Paul Tupper, Miriam Lev-On, Reid Smith, and Karin Ritter
- Subjects
Methane emissions ,Oil and gas ,Fugitives ,Optical gas imaging ,Environmental sciences ,GE1-350 - Abstract
Emissions from equipment leaks from process components, such as valves and flanges, were measured at 67 sites in the oil and natural gas production and gathering and boosting segments in four different onshore production basins in the western United States. Component counts were obtained from 65 of the 67 sites where nearly 84,000 monitored components resulted in a leak detection rate of 0.39% when detection results using both optical gas imaging (OGI) and a handheld flame ionization detector (FID) were combined. OGI techniques identified fewer leaks but greater total emissions than surveys using an FID operated in accordance with United States Environmental Protection Agency (EPA) Reference Method 21. Many of the leaks that were identified only with an FID were on the lower end of the emission rate distribution in this study. Conversely, OGI identified several components on the higher end of the study emission rate distribution that were not identified with FID-based methods. The most common EPA estimation method for greenhouse gas emission reporting for equipment leaks, which is based on major site equipment counts and population-average component emission factors, would have overestimated equipment leak emissions by 22% to 36% for the sites surveyed in this study as compared to direct measurements of leaking components because of a lower frequency of leaking components in this work than during the field surveys conducted more than 20 years ago to develop the current EPA factors. Results from this study further support emerging evidence that methane detection technologies for oil and gas applications should be evaluated on a different framework than a simple comparison of the counts of leaks detected.
- Published
- 2019
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