Simulating Cold Heavy-Oil Production With Sand by Reservoir-Wormhole Model
Notice bibliographique
Résumé
Abstract Continuous sand production and foamy oil behavior are both believed to be key factors for the enhanced nonthermal fluid production in unconsolidated heavy oil reservoirs in Canada (Alberta and Saskatchewan). The same mechanisms are likely to be active in similar heavy oil strata in Venezuela (Faja del Orinoco), Oman, China (Bohai Bay), and elsewhere. Field experience indicates that fundamental understanding of sand production mechanisms, reservoir fabric alteration, foamy oil behavior, pressure gradient changes, and stress changes are key to successful operations involving massive continuous sanding. Inter-relating these factors requires coupling of geomechanics and fluid flow processes. An integrated approach incorporating a three-phase, three-dimensional black-oil model coupled with a simplified slurry transport 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. An elastoplasticmodel is imposed near the wormhole tip 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 tip pressure gradient is reached. A material balance equation is established between solids enter into each wormhole and those correspond to the enlarged wormhole. Field data from Frog Lake, Alberta are used to validate the model, and it appears that the simulation can match the field data remarkably well. Introduction An operational strategy of producing heavy oil with sand has been widely used for a decade in Alberta and Saskatchewan1–7 and the productivity can be significantly improved as a high mobility near a wellbore or inside the reservoir formation may be achieved after sand production. However, 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. Improving these aspects, particularly the understanding of this enhanced production mechanisms, can be vital to 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 to 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 the enhanced oil production have also been calculated by a coupled geomechanics model8–10. No wormhole network is postulated in these models, sand production and the enhanced oil production are contributed by the development of a continuous sanding zone adjacent to the wellbore. Attempting to simulate the cold heavy-oil reservoir production (CP) in Northwestern Canada, where some evidences indicated that large-scale wormholes or high-permeability channels exist inside the reservoir formations4, a wormhole model is proposed. The proposed model is developed based on the hypothesis that the reservoir formation is poorly consolidated thus wormholes development under a critical flow velocity or pressure gradient is possible.
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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.
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