Visual Investigations on the Oil Recovery and Sequestration Potential of CO2 in Naturally Fractured Oil Reservoirs
Notice bibliographique
Résumé
Abstract CO2 sequestration into geologic formations such as oil reservoirs, coal beds and aquifers is a possible way to reduce the emissions of this anthropogenic gas into the atmosphere. Among these, sequestration into oil reservoirs while enhancing oil recovery is one of the most feasible ways as the additional oil recovery would offset the cost of CO2 sequestration operation. We postulate that the matrix, the main source of oil, could be a good CO2 storage medium. Hence, we focus on the matrix-fracture interaction during CO2 injection into naturally fracture oil reservoirs (the Weyburn and Midale fields are good examples for this case) in this paper. Proper design of this process is essential to maximize both the amount of CO2 sequestered and oil recovered. In this cooptimization process, miscibility, oil viscosity, matrix properties (permeability, porosity, pore characteristics, wettability, etc.), fracture properties (permeability, orientation, connectivity), injection rate, gravity, and the physical state of CO2 play a critical role. Clear understanding of the contributions of these properties on the dynamics of matrixfracture interaction is essential in designing EOR and CO2 sequestration application. In this paper, the dynamics of CO2 injection was studied experimentally. 2-D glass-bead models with a fracture in the middle were prepared and pentane was used as solvent to displace the kerosene or mineral oil to mimic miscible CO2 displacement. The focus was on the displacement patterns and solvent breakthrough controlled by matrix fracture interaction and pore scale behaviour of solvent-oil interaction for different matrix (wettability), fracture and injection conditions (rate, vertical vs. horizontal injection) as well as oil viscosity. Besides the visual investigation, the produced fluid was analyzed to calculate the solvent cut and oil recovery. It is believed that the visual understanding of the process will provide substantial information for further modelling studies. Introduction Miscible Displacement Mechanisms controlling the miscible displacement and factors effective on the efficiency have been focus of many studies over the last four decades. Huang and Tracht (1) studied oil recovery mechanisms during CO2 injection and reported that the dominant controlling mechanisms are CO2 swelling and the CO2 extraction of oil. Bahralolom and Orr(2) supported that through their micro model visualization study. They also suggested that the extraction is more effective than solubility. In general, the most common mechanisms controlling the oil recovery by CO2 injection are (1) oil displacement by the generation of miscibility, (2) oil swelling and (3) reduction in oil viscosity(3). Presence of water can decrease the efficiency of miscible CO2 displacements in water wet systems as the higher saturation of wetting phase decreases the flow fraction of nonwetting phase and consequently decreases the recovery of oil in water wet systems(4). Interaction of phase behaviour with heterogeneities leads to residual oil saturations due to preferential flow paths(5). In case of naturally fractured reservoirs, other parameters such as matrix and fracture properties critically influence the efficiency of displacement. Thompson and Mungan's(6) study eveals the effect of displacement velocity on recovery efficiency. Later, Firoozabadi and Markeset(7) showed that matrix-fracture configurations and fracture ap
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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 | 0,000 | 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 ».