Simulating Cold Heavy Oil Production With Sand by Reservoir-Wormhole Model
Notice bibliographique
Résumé
Abstract Continuous sand production and foamy oil behaviour are both believed to be key factors for the enhanced non-thermal fluid production in unconsolidated heavy oil reservoirs in Canada (Alberta and Saskatchewan). The same mechanisms are plausible to be active in similar heavy oil strata in Venezuela (Faja del Orinoco), Oman, and China. Field experience indicates that a fundamental understanding of sand production mechanisms, foamy oil behaviour, pressure gradient changes, and stress changes are essential to successful operations involving massive continuous sanding. Inter-relating these factors requires the coupling of geomechanics and fluid flow processes. An integrated approach incorporating a three-phase, threedimensional, black-oil model coupled with a geomechanics model is introduced in this article. Piping channels (wormholes) are postulated to develop from perforations when pressure gradients exceed the residual cohesion of the sand formations. An elastoplastic constitutive model is extended to describe the reservoir material before seepage forces liquefy and suspend the sand particles at the advancing tips of wormholes. The hemispherical wormhole tip is postulated to propagate as long as a critical tipressure gradient is exceeded. A slurry transport model is usedo describe the flow inside the wormholes. Field data from Frog ake, Alberta are used to validate the model, and it appears that the simulation and the field data are well-matched. Introduction An operational strategy of producing heavy oil with sand has been widely used for a decade in Alberta and Saskatchewan(1–6). However, a poor understanding of this production process, a recovery rate limited to ˜12 - 20% in appropriately screened reservoirs, and difficulties in well management (i.e., repeated workovers) have been the weak points for this technology(7). Improving these aspects, particularly the understanding of this enhanced production mechanisms, can be vital to achieving direct economic benefits. This article introduces a model to address reservoir fluid mobility changes arising from sanding, and pressure drive changes arising from foamy-oil flow. Simulations are based on a general three-dimensional, four-phase, black-oil production model coupled with a slurry flow model (i.e., solid phase is the fourth phase simulated). The latter model represents the wormholes network (or slurry transport zone), and the material balance for solids transport is established. Alternatively, the volumetric sand production and enhanced oil production have also been calculated by a coupled geomechanics model(7–9), in which fluid flow is simultaneously solved with a solid deformation system. Sand production and enhanced oil production contribute to the development of a continuous sanding zone adjacent to the wellbore. In an attempt to simulate cold heavy-oil reservoir production (CP) in Northwestern Canada, where some evidence indicates that large-scale wormholes or high-permeability channels exist inside the reservoir formations(3), a wormhole model is proposed. The proposed model is developed based on the hypothesis that the reservoir formation is poorly consolidated, thus wormhole development under a critical flow velocity or pressure gradient is possible. A detailed discussion on the wormhole model can also be found elsewhere(10). Background Sand production has long been considered undesirable(11, 12), but it is associated with high drawdown and production rates, which are required for faster and more profitable oil production.
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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 | 0,002 | 0,001 |
| 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 | 0,001 |
| 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 ».