A Comprehensive Approach to Modelling Air Injection Based Enhanced Oil Recovery Processes
Notice bibliographique
Résumé
Abstract Modelling of air-injection-based processes for enhanced oil recovery is a challenging task, mostly due to the complexity of the chemical reactions taking place. Also, the applicability of currently available kinetic models is limited to the reservoir systems they were originally developed for. The objective of this study is to derive a general chemical reaction framework that could be used to develop a kinetic model for a variety of crude oils (i.e., light or heavy oils). The work is based on the modelling of high-pressure ramped temperature oxidation (HPRTO) experiments, and combustion tube (CT) tests, performed on three different oil systems: a volatile oil which is near critical at reservoir conditions (44°API), a low-shrinkage light oil (35°API), and a bitumen sample (10°API). A kinetic model was derived for each of the cases based on the history match of a HPRTO experiment. The resulting model was validated by history matching a CT test for each of the oils. An important feature of all these experiments is that they were performed at representative reservoir pressure conditions. The modelling approach chosen is an extension of the methodology originally proposed by Belgrave et al. in 1993, which is arguably the most comprehensive kinetic model available in the air injection literature. However, their model was developed from experiments performed on Athabasca bitumen, and it fails to represent the air injection process as it occurs in light oil reservoirs encountered at high pressure. For example, Belgrave's model is based on the deposition and combustion of semi-solid residue commonly known as "coke", which is rarely present during the combustion of light oils at high pressure. As in Belgrave's model, this study also describes the original oil in terms of maltenes and asphaltenes. The main difference lies on the presence and importance of oxygen-induced cracking reactions, as well as the combustion of a flammable mixture, which takes place in the gas phase. Also, a unique feature of these simulations is that, apart from history matching traditional variables such as thermocouple temperatures, fluid recovery and gas composition, they also capture changes in the physical properties of the produced oil, such as viscosity and density, which enhances the robustness of the approach and represents an important step towards the development of predictive simulation models. This work is unique as it is the first time a single kinetic modelling approach is capable of modelling the in situ combustion of different oil types, which allows the consolidation of a general theory for air injection processes. Moreover, since the pseudo-components representing the fuel are not present in the original oil, the method is not limited to a fluid characterization in terms of maltenes and asphaltenes, but could potentially be applied along with any type of characterization of the original oil.
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Comment cette classification a été obtenuedéplier
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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 ».