QOGI Resources

QOGI Validation & Studies

Quantitative Optical Gas Imaging (QOGI) has been evaluated through a range of controlled testing, independent field studies, and internal performance assessments. Together, these efforts help define where image-based gas quantification performs well, where limitations exist, and how results should be interpreted in real-world operating conditions.

Learn more about validation studies and interpretations that support informed use of QOGI across leak detection and repair (LDAR), Measurement-Reporting-Verification (MRV), and emissions management workflows.

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Independent Field & Controlled‑Release Studies

Independent, peer-reviewed studies have confirmed QOGI’s reliability and accuracy. Best results are achieved with proper setup, environmental awareness, and operator training.

Read the article to learn how QOGI is evaluated and how its performance compares to other measurement approaches. You can also click below to explore specific topics.

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An Evaluation of an Optical Gas Imaging System for the Quantification of Fugitive Hydrocarbon Emissions

A controlled-release study showing QOGI’s superior quantification accuracy and reliability compared to Method 21.

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Blind Testing Comparing QL320 to Other Quantitative Technologies

Blind outdoor testing demonstrated QOGI’s robustness and the importance of operator technique for reliable quantification.

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Alberta Methane Field Challenge

Large-scale field trials in Alberta confirmed QOGI’s value for rapid, facility-level emission screening and MRV workflows.

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METEC QOGI Study

Single-blind experiments at METEC validated QOGI’s practical accuracy under realistic field conditions.

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Internal Studies

Our Flir research and development team has also participated testing aimed at validating QOGI as a practice and our quantitative technologies. These studies evaluated metered flow readings and included blind testing of extremely small fugitive leaks.

Flir METEC Product Evaluation (Oct 2019)

QOGI evaluated by Colorado State University METEC facility using metered flow readings.

TADI QOGI Blind Testing (April 2025)

Advancement in Methane Emissions Measurement using Quantitative Optical Gas Imaging (QOGI) Technology.

 

What QOGI Studies Reveal About Real-World Performance

Evaluation Category

What Is Examined

Practical Takeaway

Flir Guidance

Leak Rate Sensitivity
Controlled and variable release rates QOGI performs best above defined detection thresholds QOGI is ideal when aligned with common regulatory leak sizes.  For the U.S. EPA, this is often referred to as 60 g/h and up.
Distance & Geometry
Standoff distance and viewing angle Consistent setup improves reliability Basic understanding of QOGI and reviewing lessons learned create positive results.
Environmental Conditions
Wind, turbulence, thermal contrast Like all measurement technologies, certain conditions increase measurement uncertainty Understanding the technology, including how environmental conditions affect results, ensures better results.
Repeatability
Multiple measurements under similar setups Stable workflows matter more than fine tuning Using QOGI in camera simplifies workflow and helps create more efficient LDAQ processes.
Comparison Methods
Cross‑checks with other measurement tools QOGI aligns best when used for comparative or trend analysis While aggregate measurements increase accuracy, FLIR helps on a per reading basis with the new uncertainty metric per measurement.

 

Imaging + Quantification = Faster coverage. Greater efficiency. Smarter decisions.

 

infographic showing advantage of QOGI

By combining optical gas imaging with quantification capability, QOGI enabled workflows support faster coverage and more efficient emissions inspection programs.

 

How QOGI Applies to Real-World Programs

CASE STUDY

LDAR Programs

Leak prioritization and comparative sizing.

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APPLICATION STORY

MRV & Reporting

Supporting emissions estimates alongside other data.

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CASE STUDY

Emissions Management

Trend analysis and program optimization.

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TECH NOTE

Compliance Support

Demonstrating method suitability and limitations.

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APPLICATION STORY

Loss Mitigation

Using QOGI to turn invisible losses into measurable value 

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