The Application of Water Cut Sensors in Optimizing Hydrocarbon Production
Notice bibliographique
Résumé
Abstract Oil production in Canada is typically associated with water. The term used to identify this is Watercut. In recent developments of electronic instrumentation that directly and instantaneously measure dynamic WaterCut of a producing well, has created new methods of optimizing oil production; determining well and reservoir characteristics; preventing formation and interface damage; and extending the production lifetime of a well or reservoir. This is best applied on 2 phase productions, oil and water, or wells that use a gas separator and allow a 2 phase measurement to be made. A well in production is either free flowing or pumped. A variety of pumps can be used. Each pump type will cause the well to develop particular production characteristics based on the reservoir, formation and pump rate. Data about the WaterCut composition, fluid volumes and production variations provide information regarding the optimization of hydrocarbon volumes, determining long-term production and enhancing selection of producing and injection wells in a reservoir. It is particularly useful in determining short and longterm WaterCut for royalty and revenue estimates and projections. Every well producing water and oil has a particular "signature" that is identifiable in its delivery of fluids. To capture data a small, custom, portable service unit that connects in about 10 minutes of well downtime is used until the signature of a well is determined. The well's signature can be determined in the order of minutes, hours and slow pump wells-like Pumpjacks, may require days-ie one well had a 4 day repeat cycle. The data is analyzed and additional information that may be determined is sand production, condition of the pumping equipment, degradation of the interface and hydrocarbon reduction of the reservoir (increasing WaterCut). The equipment used is efficient in connection; the data may be collected locally or transmitted to a central office or location. The installation method simplifies the collection of data without running downhole equipment or halting production for extended periods of time. Data is immediately available and tests may be dynamically configured, extended or concluded according to the results. Production can be dynamically optimized and the production methods verified prior to concluding data collection or de-installing equipment. Introduction Recent development of comparatively low cost technology for the determination of water and oil percentages in production fluids, WaterCut. This technology made possible the monitoring of WaterCut in low producing and marginal wells. The data acquired has additionally provided new insights into reservoir characteristics and alternatives for enhancing production. The equipment used, coupled with ancillary instrumentation and power drivers, provides an array of features previously not available by one instrument set. Theory Recently developed instrument technology has the capability of measuring the proportionate volumes of water and oil in production fluids in either single phase or emulsion. The equipment and Sensors are connected to the Wellhead or production manifold, power changed over and the test started. The data is acquired over a period of time as the production fluid flows through the device. The values are integrated through the acquisition cycle and are accurate for the measurement period.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| 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 source (Gemma direct ou Codex distillé), 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 ».