Case Study: Dynamic Visualization of Miscibility for EOR Design and Implications for Field Planning
Notice bibliographique
Résumé
Abstract CO2 flooding is a well-known enhanced oil recovery method which is made attractive both by the opportunity to recover significant additional oil and the opportunity to sequester CO2 at abandonment. However, as the acquisition and compression of CO2 is costly, the flood must be carefully designed to maximize recovery from the injected volumes. Typically, design is done with a plan to maintain reservoir pressure above the minimum miscibility pressure (MMP), but this study investigates if a far more detailed analysis of miscibility is warranted. A pilot CO2 flood in Western Canada and its existing development plan are investigated. Instead of a relying on the single MMP from slim tube tests, miscibility is calculated on cell-by-cell basis with a tuned equation of state (EOS) and history matched reservoir model. A ‘distance’ to miscibility is calculated, in pressure terms, by comparing the saturation pressure to the cell pressure throughout the flood. The result is then visualized to illuminate possible improvements. Because it takes in account changes in pressure, composition and temperature in both space and time, this method may model important reservoir phenomena that are not considered with the slim tube method - including channeling, buoyancy, heterogeneity, multiple gradients with depth, and cross-flow diffusion. The calculation was applied to the field development plan to evaluate the effectiveness of the current strategy. Even though the MMP conditions were nominally met, the new parameter highlights areas where miscibility was not occurring and oil was being by-passed. The measure also shows areas where the CO2 concentrations were excessive, and so the injectant was underutilized in sweeping oil towards producers. Based on these results, changes to the field development plan were proposed. Well plans and operating constraints were altered to improve downhole mixing and miscibility, leading to improvement in predicted oil recovery and economic measures such as capital expenditure, operating expenditure and net present value. These results demonstrate that MMP can be overly simplistic in the design of miscible flooding strategy. The case-study presented adds to the database of past experience when designing EOR floods, while providing a simple visualization parameter to aid engineers in understanding and optimizing miscible recovery design. It is particularly useful for multiple contact floods, for fields with limited CO2 availability, and where in-situ heterogeneity, gradients with depth, and diffusion phenomena complicate recovery.
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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 ».