Optical imaging via specialized
cameras known as optical gas imaging (OGI) cameras has become standard in
exploring oil & gas facilities for detecting, and to a lesser extent,
quantifying gas leaks. The GMP03 is Konica Minolta’s latest handheld
Quantitative Optical Gas Imaging (QOGI) camera, which provides methane
detection and field quantification. Accurate quantification is one of the
biggest challenges to understanding facility-level methane leaks. The company
refers to the camera as a tool that provides Reliable Quantitative Optical Gas
Imaging (R‑QOGI).
The company’s white paper: Design Philosophy of Reliable - Quantitative
Optical Gas Imaging camera GMP03 for Achieving “Reliable Quantification” in the
Field is summarized and reviewed below. First is the abstract:
ABSTRACT
This white paper presents the design philosophy for
achieving reliable, decision ready quantification using the R‑QOGI camera GMP03 under
real-world field conditions. While OGI cameras have become widely adopted for
rapid leak detection, effective methane-mitigation efforts and regulatory
reporting increasingly require identifying leaks and quantifying emission rates.
Direct-contact methods, such as high-volume sampling, or bagging techniques,
are often impractical in hazardous, hard-to-reach, or structurally complex
facilities, reinforcing the need for a robust non-contact alternative.
However, field-based QOGI faces inherent fundamental
challenges. Outdoor airflow is rarely stable, and wind-driven plume deformation
introduces significant temporal variability. As a result, measurement sequences
often contain transient segments that are unsuitable for quantification,
leading to unstable results and a high dependence on operator interpretation.
To address these challenges, the R-QOGI camera GMP03
reframes quantification as a time-series evaluation problem. It analyzes plume
dynamics and environmental stability over time, automatically selects only data
segments suitable for quantification, and generates a single representative
emission value. In addition, the R-QOGI camera GMP03 provides an
intuitive reliability indicator derived from cumulative imagery and
environmental metrics, enabling users to assess the reliability of each result
on site while reducing reliance on operator judgment.
Finally, this paper outlines how QOGI cameras are evolving
beyond fugitive emissions to address higher-rate events—such as vents,
blowdowns, and episodic releases—that are required to be quantified under
recent regulatory and reporting frameworks. These advancements include
large-scale calibration, enhanced background reconstruction.
OGI cameras utilize infrared
imagery to detect methane leaks. QOGI pixilates that imagery in order to better
quantify leaks. It generates “stable, high contrast, high dynamic range gas
flow imagery through proprietary image processing technologies.”
Wind can have a profound effect on
OGI measurements. A key feature of the QOGI camera is its ability to work
through wind-driven variability, as shown below.
“{The camera}… introduces an
automated capability to evaluate temporal fluctuations in plume shape, motion,
and environmental conditions, extracting only the segments deemed suitable for
quantification and generating a single representative value.”
Several environmental variables
affect the ability of OGI cameras, including the QOGI camera, to accurately
measure emissions rates by influencing gas detection sensitivity.
“Flow rate estimation using QOGI cameras is strongly
influenced by gas detection sensitivity at the time of imaging and by
surrounding environmental noise. When sensitivity is degraded or when noise
levels are high, the algorithm cannot acquire sufficient information, making it
inherently difficult to estimate highly accurate flow rate values.”
Altitude, time of day, relative
position of the sun, and clouds can all affect measurements. With its previous
model, the company introduced a sensitivity map function to help filter out and
work around environmental noise. Since these noise sources, like clouds and
wind, change over time, one can take measurements at different times to
validate results.
“Rather than focusing on “always producing correct
numerical values,” GMP03 places emphasis on “enabling users to judge whether a
result should be adopted.”
Understanding the effects of
environmental noise in differing conditions allows for better estimation of
leak rates.
They note that the incorporation of representative values and reliability indicators gives the product a higher accuracy.
Below, they give some examples where underestimation and overestimation of leak rates are likely.
“In addition to the influence of wind, estimation errors
may occur under these imaging conditions:
- When the temperature of the observed object is close to
the gas temperature, detection sensitivity decreases and the flow rate tends to
be underestimated.
- In environments with significant noise, noise may be
misidentified as gas, leading to overestimation of the flow rate.”
In the R-QOGI approach, the
reliability indicators are based on factors such as imaging sensitivity, noise
level, and wind conditions. Ideal imaging conditions lead to better
quantification. Thus, it could become a strategy to plan OGI measurements with
the predicted weather. Weather prediction has gotten very good and detailed, so
that planning accordingly can yield the best results. Adjusting the shooting
angles based on prevailing wind direction can improve imaging quantification
results. Reliability factors can also determine whether re-shooting an area is
warranted.
“…the R‑QOGI camera GMP03 is designed with the
understanding that plume behavior and imaging conditions vary over time, and it
places strong emphasis on enabling users to assess the validity of the results.”
They stress that giving the
reliability indicators with each reading is essential in getting accurate
estimations.
The graph below shows that the
company’s statistical method of representative values offers somewhat better
accuracy than simple averaging of values. The percentages indicate “the
proportion of estimates falling within a factor‑of‑two range (50%–200%)
relative to the true flow rate.”
The white paper’s section on
future technical directions notes that QOGI tech has, in the past, mainly
focused on small, fugitive, unintentional leaks of less than a few kilograms
per hour. Those are still important, but there is now more focus on vents,
blowdowns, and large episodic events. One reason for more focus on these is
that, as the smaller leaks are repaired, the larger leaks associated with
maintenance events like blowdowns take up a greater share of the overall leaks.
This means that there is now more emphasis on measuring and quantifying leak
rates during these events. For the scientist, this is an opportunity to acquire
more data, improve understanding, and potentially to get better overall
quantification. However, as they note, larger gas plumes behave differently
from small ones.
“Field evaluations at METEC and Stanford have
demonstrated that traditional concentration‑pathlength (ppm-m)
estimation methods—optimized for small leaks—can significantly under‑estimate emissions in the
20–1000 kg/hr range, particularly in situations where gas retention prevents
accurate background determination.”
The company has implemented the
following enhancements to better quantify larger leaks and has plans to release
future products to better measure such releases:
“With planned product releases for vent and blowdown
quantification in 2026 and super-emitter quantification in 2027, QOGI systems
are evolving into comprehensive emission measurement platforms capable of
supporting regulatory reporting, carbon accounting, and operational decision
making. As global methane reduction initiatives accelerate, these innovations
will play a vital role in enabling operators to understand their full emission
profiles and to take informed, data-driven action.”
To summarize, the R-QOGI camera
GMP03 has enabled judgment to be shifted from human operators to an algorithmic
framework specifically designed for field conditions. This allows it to better
account for plume behavior and environmental factors. Essentially, it has the
ability to filter out what should be considered bad data due to poor
conditions. They seem to suggest that prior measurements have relied too much
on human judgement, and replacing that with algorithms coordinated with field
conditions can give more consistent results.
Finally, they note that GMP03 is
not simply a tool, but a platform as well:
“Advances in large-scale correction, background
reconstruction, and total mass estimation further extend the applicability of
OGI based quantification to high-rate and long-range scenarios. Together, these
developments position QOGI as a comprehensive emissions measurement platform
rather than a niche inspection tool.”
References:
Design
Philosophy of Reliable - Quantitative Optical Gas Imaging camera GMP03 for
Achieving Reliable Quantification in the Field. Konica Minolta. KonicaMinolta_design-philosophy-of-reliable-quantative-optical-gas-imaging-camera.pdf
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