Preventive Maintenance of Electric Submersible Pumps and its Relationship to Root Cause of Failure Analysis
Notice bibliographique
Résumé
Abstract We live in working environments where it is difficult if not career limiting, to say "no" to job assignments from bosses and colleagues. Pulling before catastrophic failure is normally not done, except in rare instances. Units are rarely pulled until total electrical failure occurs and the unit will not restart. Many times these restart attempts, after the systems have gone to ground, destroys the evidence needed to determine the reason for failure. Proper diagnostics of a unit that shuts down on overload could, in many instances, reduce repair costs for the unit, provided they are pulled prior to restarting. However, this is not the general procedure in the field. Many lease operators do not have the equipment or training to troubleshoot ESP systems after they have gone down and, being pressured for production will automatically attempt a restart as soon as they discover the failure. Producing wells can be monitored, and corrections in operation such as incoming power, wellhead pressure, casing pressure, etc., can reduce the stresses and increase the life of an ESP system. Also, use of proper monitoring techniques can aid in determining needs for replacing equipment and can reduce the repair costs if units are pulled and/or resized prior to catastrophic failure. The operator is the most important determining factor on runlife and is probably the least trained in the operating and design limitations of ESP systems. Further improvement in RCFA in the ESP field is undoubtedly in the hands of the ESP users. More manufacturer-user RCFA teams working together are becoming necessary to extend ESP run times. The objective of this paper is to provide modifications to Root Cause Failures Analysis (RCFA) methods, specific to ESP applications and show how many of the methods can be applied as Preventive Maintenance in the ESP field. It will be supported by case study from the Meekwap field where the "Time between Failures" (TBF) was tripled as a result of close cooperation between field operator and ESP manufacturer. Field Introduction The Meekwap field is located in the Swan Hills area in North-Central Alberta, Canada. It is under an extensive waterflood with 800 - 1600 m3/d of source water from the Debolt formation injected into the Nisku. Field flood pressure ranges from 22 MPa to 15 MPa. The reservoir is mix of dolomite and limestone and belongs to Nisku formation. Dolomite generally utilizes ESP's (11 wells) for production, whereas Limestone area is generally produced with conventional rod pumps, and a total of 20 producers are in five production sections. Emulsion is sour (up to 60,000 ppm) with high chlorides content (3,000 ppm). The oil gravity is 36 degrees API, water gradient is 10.9 kPa/m and Bottom Hole Temperature (BHT) is 86 ° C. ROOT CAUSE FAILURE ANALYSIS - PROPER APPROACH TO FAILURE ANALYSIS RCFA is a disciplined problem solving methodology, used to determine root causes of specific failure events. The following process is necessary to implement a successful RCFA:Determine the failure mode. This is commonly mistaken for the root cause of failure.
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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 | 0,001 | 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) | 0,001 | 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.
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