Oil Pipeline Standoff Leak Detection: A Novel Approach for Airborne Remote Detection of Small Leaks
Notice bibliographique
Résumé
While natural gas pipelines already benefit from airborne, remote detection of leaks [1, 2], oil pipeline leak detection has been for a long time reliant on SCADA systems limited in their capability to detect very small leaks, and/or visual inspection of the right of way (line flyers, pipeline employees or members of the public). This paper presents a novel and complementary way of detecting small leaks (i.e. sensitivity of 0.1 L/minute, 1 barrel/day) of oil (crude or refined products) using an optical detection system mounted on an airborne platform (UAV, plane or helicopter). The scope of this paper is based on the requirements provided by TransCanada, namely sensitivity (herein referred as LOD — Limit of Detection) and accuracy (herein referred as spatial resolution) as similar to their description in API 1130, while the topic of reliability is addressed in our noted concerns on the false alarms that may be generated in Infrared-DiAL based systems due to soil reflectivity. Robustness, as described in API 1130, was out of scope. Keeping in mind the requirement of airborne operation, three different approaches for the detection of leaks along long pipeline ROWs were studied. Infrared Differential Absorption lidar (IR-DiAL), UltraViolet Raman lidar (UV-Raman lidar) and UltraViolet Laser-Induced Fluorescence lidar (UV-LIF lidar) have been tested in realistic conditions. In the first round of tests, laboratory spectral measurements of vapors in a closed cell were performed. In the second round of tests, the breadboards were placed in a mobile laboratory and the light beams aimed at a large open at 40 to 50 meters and reflected off a sand target. Finally, the mobile laboratory with the breadboards was installed at ∼40 meters from a leak simulator. The leak simulator was made by using a large sand container in which petroleum products were leaked. Intermediate scale leak simulator tests showed that it is clearly a challenge to correlate a measured concentration to an actual leak size. Tests have also shown that there is a strong concentration gradient in the air above a leak. This indicates that a better overall detection performance should be obtained with a measurement using the air next to the ground, and that it is feasible to detect a leak of less than 1 barrel/day. UV-Raman tests performed in the outdoors suggested a Limit Of Detection (LOD) of the system below 1 500 ppm-m when detecting all hydrocarbons. Because of the hardware that would be needed to lower this detection limit, results suggest abandoning the Raman technique for remote leak detection from an airborne platform. IR-DiAL showed the best sensitivity for the detection of hydrocarbons (< 1 ppm-m of LOD). However the effective LOD will be reduced because of the soil spectral reflectance variations that may lead to a high false alarm rate for concentrations of hydrocarbons lower than 235 ppm-m. The UV-absorption approach was also briefly tested, suggesting a LOD for benzene of between 1.5 and 2.5 ppm-m. The UV absorption of benzene is not affected by ground spectral reflectance variations. This is an approach that will be investigated further.
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 ».