Phase Behaviour and Physical Properties of Athabasca Bitumen, Propane and CO
Notice bibliographique
Résumé
Abstract The design and optimization of solvent based processes to recover heavy oil are hampered by limited data and modeling capability for mixtures of heavy oils and solvents. Phase boundaries, compositions, and physical properties such as viscosity and density are required. Here, mixtures of propane and CO2 with Athabasca bitumen are considered. Saturation pressures were measured in a PVT cell and the density and viscosity of the saturated liquid phase were determined at temperatures between 0 and 90 °C and pressures up to 5 MPa. Data are reported for CO2-bitumen, propane-bitumen and three propane-CO2-bitumen mixtures. Vapour-liquid and some liquidliquid and vapour-liquid-liquid phase boundaries were determined. Regions where multiple liquid phase formation is likely were identified. A simple analytical methodology for determining the vapour-liquid phase boundary for each mixture was developed. Introduction In Canada, steam based methods are often employed to improve heavy oil recovery. However, the industry is seeking alternatives to these methods because they are energy intensive and are drawing heavily on the available water supply. Solvent based recovery methods are a potential alternative capable of providing high recovery factors without high waterrequirements(1,2). One option is the vapor extraction method(Vapex), which is a solvent-based analogue of the steam assisted gravity drainage (SAGD) process(3–6). Vapex is implemented with a pair of horizontal wells: a production well at the bottom of the reservoir and a solvent injection well located directly above the production well(4). The vaporized solvent is injected through the injector and a chamber of solvent vapour forms around the well. At the walls of the chamber, the solvent diffuses into a surface layer of the heavy oil and dramatically reduces its viscosity. The diluted oil layer is then mobile enough to drain down, under the influence of gravity, into the production well. VAPEX performance depends on the viscosity and density of the liquid phase that forms at the edge of the solvent chamber. In order to design and optimize VAPEX and other solvent based processes, it is critical to be able to: determine the diffusivity of the solvent in the heavy oil; identify the phases that form in the solvent and heavy oil mixtures at various temperatures and pressures; determine the density and viscosity of the liquid phase. Other solvent-based processes (steam and solvent injection for heavy oil recovery and solvent extraction of oil sands) require similar data. Most research on Vapex has focused on physical model experiments with light alkane solvents, particularly mixtures of methane and propane (2). However, mixtures of carbon dioxide and propane may be a more viable option. Currently, carbon dioxide is expensive but costs are expected to decrease if environmental incentives to sequester carbon dioxide are introduced. Carbon dioxide may also be a better Vapex solvent than methane because it is more soluble in heavy oil and reduces the viscosity more (7). However, at typical heavy oil reservoir conditions (pressure of ∼1.2 MPa and temperature of ∼10 ° C), propane and butane have higher solubility and provide greater viscosity reduction than carbon dioxide.
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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 ».