Continuous Methane Monitoring: Equivalency Evaluation of Regulator-Approved Alternative Leak Detection and Repair Program in Alberta, Canada
Notice bibliographique
Résumé
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%.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».