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Enregistrement W1980428507 · doi:10.2118/05-01-04

SAGD Wind-Down: Lab Test and Simulation

2005· article· en· W1980428507 sur OpenAlex

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Notice bibliographique

RevueJournal of Canadian Petroleum Technology · 2005
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensSocial Sciences and Humanities Research Council
Organismes subventionnairesNational Taiwan University
Mots-clésPetroleum engineeringSteam injectionFossil fuelPilot testEnvironmental scienceComputer simulationEngineeringSteam-assisted gravity drainageProcess engineeringAsphaltWaste managementOil sandsSimulation

Résumé

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Abstract As SAGD moves from pilot test to commercial operation, a number of issues need to be dealt with. These include diagnosing and solving operational problems and improving energy efficiency. One of the methods of improving energy efficiency is to prolong oil production after steam injection stops by using the energy remaining in place. The results of a laboratory experiment and corresponding numerical history matching are reported in this paper. The study showed that the hot chamber continued its expansion after steam injection was stopped and a gas injection was initiated. The continuous expanding period represented the most productive period in the gas injection wind-down process. A total of 12.5% of OOIP was recovered during wind-down. Successful history matching of both the oil production curve and temperature profiles at different times demonstrated that the numerical simulation could handle the gas/steam mixing phenomena. Gas concentration profiles from numerical simulation indicated that gas was concentrated at the region where oil saturation was experiencing big changes. Introduction The successful tests of the SAGD process at UTF(1, 2) and other pilot projects(3, 4) have established SAGD as a viable technology for in situ recovery of the huge heavy oil and bitumen resources in western Canada. A number of commercial SAGD projects in western Canada are in the operation, construction, or planning stages(5). However, the SAGD technology is still in a transition from pilot to commercial operation. Development of the technology is currently focusing on two areas. The first is to diagnose and solve operational problems. In field operations, many projects have encountered difficulties, such as lower than expected oil production rate, higher than expected steam-oil ratio (SOR), or premature production rate decline. In each case, the cause of the problem needs to be identified in order to develop methods to deal with the problem and avoid the problem in the future. The second area of SAGD development is to improve energy efficiency as the costs of fuel and associated water treatment account for a large portion of the oil production cost. These developments include hybrid processes using co-injection of steam and solvent(6 – 10), or steam and non-condensable gas(11). The hybrid processes take advantage of both heating by steam and dilution by solvent. The injection of non-condensable gas is intended to reduce heat loss to the overburden, and therefore, improve SOR. With this idea in mind, efforts have been directed to developing SAGD wind-down methods. At a certain stage of the SAGD operation, as instantaneous SOR increases, there is no economic benefit to continue pure steam injection. At this stage, a wind-down process can be started to utilize energy in place and continue oil production. A numerical simulation and economic evaluation study(12) showed that a co-injection of steam and non-condensable gas gave the best result. Recently, the results of co-injection of steam with flue gas into UTF Phase B as a wind-down process was reported(13). The key to achieve the best economics for a SAGD wind-down process is optimization.

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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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,343
Score d'incertitude au seuil0,443

Scores Codex et Gemma par catégorie

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

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 Opus0,008
Tête enseignante GPT0,231
Écart entre enseignants0,223 · 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