Key Takeaways on Bridger Photonics’ Study on Enhanced Reliability and Auditability in Emission Detection Sensitivity

At-a-glance takeaways: 

• A model was developed that simplifies the many complex parameters that affect the detection sensitivity of Gas Mapping LiDAR methane leak detection, such as environmental conditions or flight parameters, into a single, measurable metric.
  • This means that detection sensitivity performance of aerial LiDAR scans can be measured for any flyover pass and at  any spatial scale, e.g. equipment-level or facility-level.
  • This new model provides operators peace of mind by ensuring robust auditability for regulations, emissions inventory accuracy, and gas certification and reporting.
• Across 12 different North American production basins, the average emission rate detection sensitivity for second-generation aerial LiDAR sensors was 1.27 kg/hr at 90% PoD.
  • This emission rate detection sensitivity exceeds industry standards for the production and transmission sectors, and builds on the already best-in-class sensitivity capabilities that Bridger Photonics offers.

Emission rate detection sensitivity is a key factor in assessing the performance of an emission detection technology, but the probability of detection (PoD) for an emission source is affected by a complex mix of environmental and operational parameters. The effects of these parameters on detection tech performance are often nonlinear, which makes characterization difficult.

Historically, minimum detection limit, or MDL, was used to assess the sensitivity of a technology, but this term only represents the lowest possible emission rate detectable, without the element of reliability for that emission rate, or a PoD. Recent modeling methods in scientific research have improved the understanding of PoD, especially as it relates to wind speed, but have not fully addressed the influence of other environmental factors.

Until now there has not been a simple way to model and account for all known parameters that affect a technology’s ability to detect emissions. This new study conducted by the Bridger Photonics team along with leading academic researchers in the methane space, developed a rigorous model that, when combined with wind speed, accounts for all deployment and environmental parameters that affect detection sensitivity for an individual emission source.

Here are the key takeaways from the study: 

Takeaway 1: A model was developed that condenses many complex environmental and operational parameters down into a single metric.

Why It Matters:
The weather is constantly changing, different infrastructure and terrain cover types reflect light differently, and the flight parameters used to scan facilities, such as altitude and speed, might not be the same from one day to the next. With so many variables that can affect detection sensitivity, it can be nearly impossible to measure all of them. This new Gas Concentration Noise (CGN) model, combined with wind speed, accurately predicts the detection sensitivity and PoD for any individual emission location by correctly accounting for how these parameters affect detection sensitivity.

The development of this GCN model is a breakthrough in assessing aerial LiDAR detection sensitivity sensor performance at any equipment-level or facility-level scale.

Takeaway 2: A model was developed that estimates detection sensitivity and probability of detection for any isolated emission source, detected during any flyover pass, and works well in any location, regardless of aircraft or environmental parameters.

Why It Matters:
The new model is important because it gives operators peace of mind. It means robust auditability to meet regulatory requirements in new U.S. and Canadian oil and gas regulations, improving the accuracy of emissions inventories (including the measured and unmeasured emissions) and emissions intensities, and supporting reliable measurements for gas certification and reporting initiatives, like OGMP 2.0.

Takeaway 3: Across 12 different North American production basins, the average emission rate detection sensitivity for GML 2.0 was 1.27 kg/hr at 90% PoD.

Why It Matters:
Although environmental parameters and differing characteristics across oil and gas production basins can mean variable performance for emissions detection technologies, this study showed that second-generation Gas Mapping LiDAR sensors (GML 2.0) had superior performance across the board.

An emission rate detection sensitivity of 1.27 kg/hr with a 90% PoD exceeds industry standards for the production and transmission sectors, and builds on the already best-in-class sensitivity capabilities.

Reliable detection sensitivity performance means operators can have very high confidence in their detection solution when using GML, regardless of the basin they operate in or the environmental conditions present.

Thank you to the authors and co-authors, the study peer-reviewers, and the team at Remote Sensing of Environment.