Revolutionizing Drilling: Integrating the Internet of Things (IoT) and Cloud Technology into Remotely Operated Managed Pressure Drilling (MPD) and Tripping in Canada, Duvernay Formation
Notice bibliographique
Résumé
Abstract As the IoT continues to transform drilling operations, technologies that were once restricted to local control can now be remotely operated through a collective network that connects local devices with the cloud. This paper presents a case study where IoT integration enabled an operator to leverage the advantages of managed pressure drilling (MPD) operations in the Duvernay formation, all within a carefully planned and remotely controlled environment, leading to cost savings and more effective drilling operations. A hydraulics model was initially set up on an operating panel in the doghouse using MPD software, enabling direct remote access and integration with the rig's electronic drilling recorder. This allowed MPD equipment on-site to be operated locally or remotely. With the operating panel connected to the cloud, remote operators could manipulate MPD parameters before or during operations. Given that IoT and cloud technology were critical to safely operating the MPD equipment remotely, all personnel were briefed on the associated risks. Drillers received additional training to handle situations that prevented remote operators from controlling the equipment. Over the course of nine wells, constant bottomhole pressure (BHP) was remotely automated and applied to the wellbore, targeting anywhere between 1,750 to 1,900 kg/m³ at the landing point or Duvernay Top on connections during drilling. A little over 37,800 meters were drilled with MPD equipment operated remotely from Calgary and Houston. Remote operators also assisted with tripping operations, maintaining a dynamic target pressure at BH to mitigate swab effects while stripping out of the hole. To ensure the hydraulics model accurately reflected current well parameters, constant communication between on-site representatives, drillers, remote operators, engineers, and other vendors (e.g., drilling fluids, directional, and cementers) was recognized as an essential requirement, in which an integrated chat application and communication devices were all utilized. The success of drilling these nine different curves and laterals in the Duvernay, with no incidents, reflects the effectiveness of integrating IoT and cloud technology into traditionally manual operations, despite the challenges which were addressed through considerate pre-planning and execution. The use of IoT and cloud technology for remotely controlling MPD equipment is still uncommon in the drilling industry. This paper provides practical insights into the application of these technologies in actual drilling operations within the Duvernay formation. While it demonstrates the feasibility of IoT and cloud integration in MPD operations, it can also highlight potential future challenges and lessons learned in safely operating and controlling MPD equipment and software remotely
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 ».