An Integrated Approach to Zero Emissions Valve Actuation
Notice bibliographique
Résumé
Abstract Valves are critical components in the oil and gas industry from up-stream to down-stream supply chains that control operation, while protecting lives and assets. Valve actuation at and/or near the wellsite is commonly powered through pneumatic or hydraulic systems, process line pressure and/or manual operation. This involves field transportation and site equipment utilization and/or process gas venting leading to increased greenhouse gas (GHG) emissions. Enabling zero emissions valve actuation is achieved through the development of a self-contained low power electro-hydraulic unit with an intelligent valve controller. This smart valve actuation and monitoring system reduces GHG emissions through four major elements: low power electro-hydraulics, intelligent operation, analytics, and remote operation. System implementation was conducted on actuated wellhead gate valves, where these four major elements were integrated. Both low power electro-hydraulics and intelligent operation contribute to an improved power utilization, while the analytics and remote operation lead to a normally unattended facility through condition-based maintenance and improved operational efficiency, paving the way towards a reduced emissions system. The self-contained low power electro-hydraulic system has been lab tested and field implemented by major energy producers to minimize personnel field presence and allow remote operation, thus leading to a reduction in emissions. Many of the mechanical and electrical components have been validated through continuous operation over more than 2 years on Canadian wellheads with an ambient temperature less than -40C in some instances. In addition, the system was successful in protecting lives during the 2023 wildfires season in Alberta. The analytics conducted by the intelligent valve control system were successful in monitoring the valve, and hydraulic circuit and actuation health through key performance indicators (KPIs). Processing of full and partial stroke data coupled with physics-based models led to an evaluation of a new hydraulic pressure intensity (HPI) factor that can predict potential valve failure to open or close. In addition, evaluation of sensors’ time-based data was found useful to identify the malfunctioning of specific components in the hydraulic circuit. Moreover, early detection of hydraulic leakage and identifying its location in the hydraulic circuit was possible through evaluation of hydraulic pressure signatures. These results indicate the advantage of a smart valve actuation and monitoring system on improving operational efficiency and safety, while reducing emissions. The developed smart system offers a new integrated approach that combines several control, monitoring, and communication elements to achieve zero emissions valve actuation compared to the manual operation that contributes to the baseline carbon footprint. This approach also improves overall system compatibility and efficiency, compared to current independent multi-contractor system integration that leads to inefficient installation, commissioning, and operation.
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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 ».