Reservoir Simulation Assessment of the Oil Recovery Mechanisms in High-Pressure Air Injection (HPAI)
Notice bibliographique
Résumé
Abstract It has been speculated that oil recovery by High-Pressure Air Injection (HPAI) is mainly attributable to in situ generated flue gas displacement. Several published field scale simulations have been based on this assumption, focusing on the compositional modeling of flue gas/oil interaction. Experimental observations lead to the conclusion that the combustion front leaves behind a zero oil saturation zone (100% microscopic efficiency). Additionally, the self-correcting nature of the combustion zone redirects the air flow, promoting a high macroscopic (volumetric) efficiency. This work is aimed to quantify the contribution of flue gas displacement to oil recovery under HPAI by combining valuable experimental information and numerical reservoir simulation. Compositional (GEM) and thermal (STARS) simulators from CMG are used in this study to match slim-tube and, core flood flue gas displacements for two light crude oils and a combustion tube test. PVT data is matched and resulting parameters are incorporated into the compositional simulation. By using interfacial tension dependent relative permeability curves, it is demonstrated that the mere displacement capability of flue gas cannot account for the oil recovery in the combustion tube test. Introduction Tingas, Greaves and Young1 developed a HPAI simulation model based on typical North Sea oil reservoir conditions. A detailed analysis of phase behavior, chemical reactions and numerical stability is presented. They recommended at least two hydrocarbon liquid components should be defined for a proper description of oil-flue gas phase behavior. Kuhlman2 compared the performance of black oil, EOS-based and thermal simulators in predicting the production behavior of HPAI using data from Coral Creek (viscous-dominated) and Hackberry (gravitystable) reservoirs. The author points out that a minimum of six hydrocarbon components are needed in a thermal model in order to properly describe the incremental oil due to flue gas drive. A number of HPAI field simulation studies have been reported, providing enough details on the methodology employed3–5. None of the studies have properly incorporated the minimal compositional detail to simultaneously account for phase behavior and combustion reactions. As a result, the real contribution of flue gas drive to HPAI oil recovery is still a matter of speculation. Additionally, the existence of three-phase flow and re-saturation phenomena is a characteristic that needs attention in order to appropriately describe the HPAI process and to assess the contribution of each mechanism to the final oil recovery. The wide variation in pressure, temperature and phase composition in HPAI affects not only the phase behavior and chemical reactions involved, but also influences the relative permeability, and thus the mobility of each phase. Oil-gas interfacial tension (IFT) variation with pressure, temperature and composition is used in this work to establish a relationship between flue gas/light oil relative permeability and IFT, making use of Shokoya et al. 6,7 experimental work. This correlation is applied to the simulation of a combustion tube test (CT), carefully considering three-phase flow, to assess the oil recovery potential of flue gas drive in a HPAI process. Methodology Two light oils were used in this work: Oil 1 and Oil 2 are Oil A and Oil B correspondingly from Shokoya7.
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 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 | 0,000 | 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) | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».