Steam Flooding of Naturally Fractured Reservoirs: Basic Concepts, Recovery Mechanisms, Process Improvements, Mechanism and Optimization of In Situ CO2 Generation
Notice bibliographique
Résumé
Abstract As a deep study, some of the main aspects of steam injection in naturally fractured reservoirs are reviewed and discussed in this paper. The thermo-chemical alteration (cracking, dehydrogenation and condensation) of reservoir crude oil and rock are reviewed. After that the effects of temperature on physical properties of crude oils and rocks are reviewed. The temperature of injected fluids can be as high as 350 °C, therefore the physical properties such as viscosity, interfacial tension, wettability, capillary pressure, permeability and etc. may be greatly affected. The recovery mechanisms for steam injection in naturally fractured reservoirs and the characteristic time for these mechanisms are reviewed. The most important recovery mechanism in matrix blocks is differential thermal expansion between oil and the matrix pore volume and the strongest recovery mechanism in fracture network is reduction of viscosity ratio (?o/?w). This will be show that the matrix oil recovery mechanisms are relatively independent of oil gravity, making steam an equally attractive recovery process in fractured light and heavy oil reservoirs. Some of the most common operations (such as fracturing, use of horizontal wells, pressure cycling and etc.) to improve the steam injection process sweep efficiency are discussed. Finally the mechanism and optimization of CO2 generation and liberation during steam injection in carbonate reservoirs were discussed. It will be discussed that the rate of CO2 generation is controlled by the rate of heat conduction from fracture into the matrix. For a specified reservoir there are optimum injection rate and temperature which can optimize oil recovery. If these criteria are not achieved, the liberated CO2 not only can not enhance the oil recovery but also may lower the oil production rate due to bypassing the oil in the fracture network. Introduction Heavy oil occurring in carbonate reservoirs, mostly fractured, is an important resource which accounts for one-third of total heavy oil worldwide. Many fractured reservoirs in the Middle East, former Soviet Union, and Canada are candidates for thermal heavy oil recovery. Processes like steam injection, or other thermal recovery methods, which have been used extensively to recover heavy oil from non-fractured reservoirs were not applied to fractured reservoirs until the decade or so ago. This was primarily based on the belief that the injected steam would bypass the oil through the fractures, and not recover most of the oil. However, the results of experimental, theoretical and pilot tests which have been appeared in the literature since early 1980's, show the feasibility of heavy oil recovery from fractured reservoirs using steam injection. Fractured carbonate reservoirs represent a unique target for application of enhanced oil recovery technology. High divalent ion concentrations in reservoir waters and extensive fracture networks appear to preclude use of chemical processes and gas injection techniques with the possible exception of miscible CO2. Although Schulte and Vries did an experiment to show the feasibility of in-situ combustion in densely fractured reservoirs such as those that occur in Middle East in Iran and Oman, in-situ combustion, because of channeling of injected air, probably cannot be sustained[16].
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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 | 0,001 | 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 ».