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Enregistrement W2026309888 · doi:10.2118/2009-204

Heat Transfer Fundamentals for Electro-thermal Heating of Oil Reservoirs

2009· article· en· W2026309888 sur OpenAlexaboutno aff
Bruce C. W. McGee, R.D. Donaldson

Notice bibliographique

RevueCanadian International Petroleum Conference · 2009
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHeat transferPetroleum engineeringThermalHeat transfer fluidMaterials scienceEnvironmental scienceMechanicsThermodynamicsGeologyPhysics

Résumé

récupéré en direct d'OpenAlex

Abstract Electro-thermal methods are being used for extraction of bitumen from the oil sands. Several processes have been tested or are being proposed. Shell has proposed the use of electro-thermal methods in the carbonates and have tested a process at their Shell Peace River operation. E-T Energy is using an electro-thermal process in the Athabasca Oil Sands. Other institutions and companies, for example, the Alberta Research Council has also developed electro-thermal approaches for bitumen recovery. The heat transfer mechanisms, either from horizontal or vertical wells, associated with the electro-thermal approach distinguishes the various methods. In some of the approaches, heat transfer by conduction is the dominant method of transferring heat to the reservoir. In other methods, heat is generated within the reservoir electrically and transferred conductively, and in other processes convection is a key heat transfer mechanism in combination with the others. The purpose of this paper is to present a model for radial heat transfer that can be used to compare different electro-thermal heating methods. The model compares the resulting temperature distribution, time to achieve a heated volume at some distance away from the wellbore, and the power density in the reservoir between the different electro-thermal methods. Also, insight into design issues, such as well spacing and input power requirements, as well as practical matters related to efficiency, near wellbore heating, and water vaporization are presented. Introduction Oil reservoirs are a mixture of sand, bitumen and water. In Alberta, most of the oil is heavy or bitumen (from the oil sands) and cannot be produced easily from the reservoir. Electro-thermal methods are presently being considered for mobilizing bitumen from the oil sands. Bitumen is defined as oil that is less than 10 API and will not flow to a well in its naturally occurring state. Steam assisted gravity drainage (SAGD) is a promising in-situ thermal recovery method, having the advantages of lower energy requirements and higher recovery factors over other steam injection methods. However, about two thirds of the total deposit is too deep for surface mining and too shallow for steam injection [4] as depicted in Figure 1. These shallow resources may be well suited for electro-thermal processes. Also, electro-thermal methods have the potential to produce bitumen from oil sands that are at the mineable depths [2]. All in-situ thermal recovery methods as applied in oil sand deposits have the common objective of accelerating the hydrocarbon recovery process. Raising the temperature of the host formation reduces the bitumen viscosity allowing the near solid material at original temperature to flow as a liquid. These effects assist in sweeping the bitumen to be recovered from the formation when driving agents are externally injected or when autogenous processes, such as gravity drainage come into play. Conduction Methods that use electro-thermal energy to increase the temperature of the wellbore without current flow in the reservoir have been also been developed. This is the first configuration shown in Figure 2. Electric heater elements are placed within the wellbore and are operated at very high temperatures.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,241
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,255
Écart entre enseignants0,237 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2009
Routes d'admission1
Résumé présentoui

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