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  5. Methane Quantification Performance of the Quantitative Optical Gas Imaging (QOGI) System Using Single-Blind Controlled Release Assessment

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Preprint
en
2024

Methane Quantification Performance of the Quantitative Optical Gas Imaging (QOGI) System Using Single-Blind Controlled Release Assessment

0 Datasets

0 Files

en
2024
DOI: 10.26434/chemrxiv-2024-m7l0p

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Daniel Zimmerle
Daniel Zimmerle

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Chiemezie Ilonze
Jiayang Wang
Arvind Ravikumar
+2 more

Abstract

Quantitative optical gas imaging (QOGI) system can provide rapid quantification of leaks detected by optical gas imaging (OGI) cameras across the oil and gas supply chain. A comprehensive evaluation of the QOGI system’s quantification capability is needed for successful adoption of the technology. This study conducted single-blind experiments to examine the quantification performance of the FLIR QL320 QOGI system under near-field conditions at a pseudo-realistic, outdoor, controlled testing facility that mimics upstream and midstream natural gas operations. The study collected 357 individual measurements across 26 controlled releases with rates between 2 slpm to 88 slpm of compressed natural gas (CNG). The majority (75%) of measurements were within a quantification factor of 3 (quantification error of -67% to 200%) with individual errors between -90% and 831% (i.e. within a factor of 10). Quantification error decreased with increasing controlled release rates. Performance improved when viewing gas plumes against a clear sky as background and at calm wind speed conditions relative to other scenarios. Quantification error varied substantially when the same controlled releases were quantified from different camera positions.

How to cite this publication

Chiemezie Ilonze, Jiayang Wang, Arvind Ravikumar, Clay Bell, Daniel Zimmerle (2024). Methane Quantification Performance of the Quantitative Optical Gas Imaging (QOGI) System Using Single-Blind Controlled Release Assessment. , DOI: https://doi.org/10.26434/chemrxiv-2024-m7l0p.

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Publication Details

Type

Preprint

Year

2024

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.26434/chemrxiv-2024-m7l0p

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