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Enregistrement W2015515352 · doi:10.2118/06-02-01

Laboratory Investigation of Enhanced Light-Oil Recovery By CO/Flue Gas Huff-n-Puff Process

2006· article· en· W2015515352 sur OpenAlexafffundabout
Y.P. Zhang, S.G. Sayegh, Mingzhe Dong

Notice bibliographique

RevueJournal of Canadian Petroleum Technology · 2006
Typearticle
Langueen
DomaineEngineering
ThématiqueEnhanced Oil Recovery Techniques
Établissements canadiensUniversity of ReginaSaskatchewan Research Council (Canada)
Organismes subventionnairesPetroleum Technology Research CentreUniversity of Alberta
Mots-clésFlue gasPetroleum engineeringResidual oilEnhanced oil recoverySaturation (graph theory)Environmental scienceOil fieldFuel oilWaste managementChemistryEngineering

Résumé

récupéré en direct d'OpenAlex

Abstract This paper focuses on phase behaviour measurements with reservoir oil-CO2 mixtures and on coreflooding tests in the huffn- puff mode to characterize the system, determine the influential mechanisms, and supply data for simulation of the field implementation. The results indicate that significant amounts of CO2 could dissolve in the oil, which caused oil swelling and viscosity reduction. During the puff cycle, the oil retained CO2 preferentially to methane; thus, the beneficial swelling and viscosity effects were maintained over an extended portion of this cycle. Corefloods were performed to investigate the effect of waterflood residual oil saturation and injection gas composition (CO2 and enriched flue gas) on oil recovery. Incremental oil recovery was observed to be sensitive to waterflood residual oil saturation and to the process application scheme. Coreflooding results suggest that the huff-n-puff process may be more suitable to oil-wet than water-wet reservoirs. Introduction Various technologies have been applied in tertiary oil recovery processes, such as gas miscible/immiscible injection and chemical flooding. Among these enhanced oil recovery (EOR) methods, the huff-n-puff process has been reported to be economic at an oil price of less than US$20/STB and CO2 costs of US$40/ton(1). For example, it was shown in a flue-gas huff-n-puff project(2)that oil production rates stabilized, and the project proved to be cost effective with small investment requirements and low operating costs. In another case(3), the CO2 huff-n-puff process was not successful in increasing incremental oil recovery. However, there were reduced water-handling and electrical requirements during the injection, soak, and flow phases, which were beneficial to the project. There is increasing interest in CO2/flue-gas huff-n-puff injection into single wells because the process is relatively easy to apply and does not require a large initial capital outlay. The process typically begins with the injection of a slug of gas into a single well. This is followed by a shut-in or soak period to allow the gas to dissolve into the oil, swell its volume, and reduce its viscosity. The same well is then returned to production and the response is monitored. In reservoirs with poor inter-well communication, this single-well approach may be one of the best ways, and sometimes the only way, to accelerate response in underperforming wells. Since miscibility between the reservoir oil and injected gas is not a requirement of the huff-n-puff process, it is well suited for low pressure reservoirs and for gases with high minimum miscibility pressures such as flue gas. The mechanisms involved in the production of oil during gas huff-n-puff are diverse and complex. The following mechanisms have been mentioned in the literature(4–6):oil viscosity reduction;oil swelling;solution gas drive;relative permeability hysteresis due to reduced water saturation, drainage/imbibition, and wettability alternation;repressurization;gas diffusion and mass transfer; and,interfacial tension reduction in the zone near the wellbore. The purpose of this work is to investigate the potential for applying the CO2 huff-n-puff process in a medium-gravity oil reservoir in Saskatchewan.

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 candidatesMéta-épidémiologie (sens strict)
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 enseignants0,024
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0030,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,002
Tête enseignante GPT0,185
Écart entre enseignants0,182 · 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

Citations39
Publié2006
Routes d'admission3
Résumé présentoui

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