Continuous Methane Monitoring: Equivalency Evaluation of Regulator-Approved Alternative Leak Detection and Repair Program in Alberta, Canada
Bibliographic record
Abstract
Summary Diverse methods have emerged for methane leak detection and repair (LDAR), alongside a growing interest in continuous monitoring (CM). Novel LDAR programs must demonstrate equivalent (or better) emissions reductions compared to conventional handheld methods to be approved by regulators and trusted by industry. We apply and test a widely accepted equivalency framework and report on a regulatory approved alternative LDAR pilot program to evaluate the performance of CM relative to conventional LDAR. The framework, which has not been formally tested to date, relies on a combination of controlled release testing, simulation modeling, and field piloting. First, controlled release testing at known emission rates is used to establish probability of detection functions and other performance metrics for the CM device. Performance metrics are then used to build a CM module in LDAR Simulator (LDAR-Sim), an open-access modeling framework. Finally, CM devices are deployed as part of a field pilot. Controlled release testing results and dispersion modeling suggest that the CM devices can reliably detect (i.e., 90% detection probability or greater) a rate of 1 kg/h (~54 scf/hr) from distances of 75–100 m with no false positive detections. A set of work practices were established using the LDAR-Sim framework. The CM program requires close-range follow-up for any detection event and is estimated by LDAR-Sim to reduce aggregate annual fugitive methane emissions by 91.8% relative to the baseline, doubling the reductions anticipated from a conventional regulatory program. For the pilot, 52 devices are deployed across 16 facilities with Enhance Energy. All devices are positioned within 100 m of monitored assets. Each time devices record a detection event, which is defined as a sustained anomaly three standard deviations above a moving average background concentration for 24 hours, 7 days, or 60 days, the operator performs a close-range follow-up inspection. Preliminary results show that the CM devices can detect leaks and that follow-up protocols are effective at immediately finding leaks and avoiding false positives. Confirmed detections include fugitive emissions such as a tank thief hatch leak and vented emissions including high-bleed pneumatics. Both types of emissions were confirmed as repaired or improved by CM. These results indicate that repairing leaks more expeditiously through faster detection can reduce emissions by up to 90%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".