Automation and Surveillance Improve Progressing Cavity Pump Performance
Notice bibliographique
Résumé
This article is based on paper SPE 136690 by the same author, which was presented at the 2010 SPE Progressing Cavity Pumps Conference, Edmonton, Canada, 12-14 September. To extend the run life of the pump while producing all available fluid is the goal of all progressing cavity pump (PCP) operators. The primary challenge is to do so without starving the pump and causing damage to the stator. The petroleum industry has been searching for years for a reliable way to control PCPs for pump-off. Several methods have been used, from monitoring torque to manual fluid levels. To date, none have been commercially successful. A method for controlling these wells has been developed combining wedge meter flow technology and microprocessor control of both electric motors through the use of variable frequency drives (VFDs) and hydraulic motors using proportional control valves. This method has proved accurate and reliable, extending run life while producing all available fluids. Combining this automated technology at the well with a web-based system that feeds back real-time data to a dedicated supervisory control and data acquisition (SCADA) host allows PCP technical experts to diagnose problems, and operators to respond quickly to changing well conditions. This article discusses the advances in automation and optimization of PCPs. The acceptance of PCPs in the oil and gas industry has grown worldwide. A major concern is potential damage to the stator if the well is pumped off. The most common prevention is to ensure that there is a substantial amount of fluid level above the pump. Operators taking manual fluid level shots and adjusting pump speed has been the most widely used method to maintain a safe fluid level. With advancements in fluid flow measurement and proven algorithms, the PCP controller has eliminated this concern, while producing all the available fluid from the wellbore without damaging the pump. With this automated technology and a web-based SCADA system, it became possible to monitor several data trends and discover additional control algorithms. Further development of these algorithms is ongoing. Pump-Off Control for PCPs Two main objectives were defined when the theory of the PCP controller was introduced. The first objective was to reduce premature pump failure. The most common failure is stator damage due to pump-off. Pump-off is defined as a lack of fluid entry into the pump. This causes a lack of lubrication to the stator, resulting in extremely high temperatures being generated. The high temperature ultimately burns the elastomer in the pump. The stator’s rubber surface becomes hard, brittle, and cracked. In severe circumstances, the stator contour is torn up, producing rubber at surface. This may be caused by one or a combination of the following problems: plugged pump intake, poor inflow, or production rates exceeding inflow.
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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 ».