A Comprehensive Approach to Modeling Air Injection-Based Enhanced Oil Recovery Processes
Notice bibliographique
Résumé
Summary Modeling of air-injection-based processes for enhanced oil recovery (EOR) 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 modeling of high-pressure ramped temperature oxidation (HPRTO) experiments, and combustion tube (CT) tests, performed on two different oil systems: a volatile oil that is near critical at reservoir conditions (44 °API), and a bitumen sample (10 °API). The HPRTO test is a kinetic experiment that intends to mimic the flow conditions within the reservoir and allows the determination of kinetic parameters of the different reactions. On the other hand, the CT test is meant to provide quantitative information on the combustion performance that can be expected in the field. Therefore, a kinetic model was derived for each of the cases based on the history match of an HPRTO experiment. The resulting model was validated by history matching a CT test for each of the oils. An important feature of these experiments is that they were performed at representative reservoir pressure conditions. The modeling 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 high-pressure air injection process as it occurs in light oil reservoirs, which are typically encountered at higher pressure conditions. For example, Belgrave’s model is based on the deposition and combustion of semisolid 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 composition of the oil in terms of maltenes and asphaltenes. The main difference lies in the presence and importance of oxygen-induced cracking reactions, as well as the combustion of a liquid-vapor flammable hydrocarbon mixture that is generated by cracking and oxidation reactions, which take 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 produced gas composition, they also capture changes in the physical properties of the produced oil, such as viscosity and density, as well as the amount of the residual phases in the post-test core. This enhancement to Belgrave’s reactions allows modeling the air injection process in cases where coke is not the main source of fuel, such as in high-pressure light oil reservoirs. This work changes a paradigm deeply rooted in the original in-situ combustion (ISC) theory, by deriving a general chemical reaction framework that is used to develop a kinetic model for two crude oils, which are at opposite ends of the density spectrum. This allows the consolidation of a new and comprehensive general theory for the description of the ISC process as applied to oil reservoirs. Moreover, as the pseudocomponents 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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».