Modelling the Miscible Displacement in CO-ECBM Using the Convection-Dispersion with Adsorption Model
Notice bibliographique
Résumé
Abstract The convection-dispersion model with adsorption has been used successfully to evaluate adsorption of foam-forming surfactants from core flooding experiments in enhanced oil recovery applications. Mechanisms that determine the transport of CO2 gas through coal in CO2-ECBM include convection, dispersion and adsorption. This work attempts to model the CO2-ECBM process utilizing the convection-dispersion model with adsorption. A laboratory experiment was conducted to simulate the CH4 miscible displacement by CO2 gas using a coal core sample from Alberta Mannville Formation. The effluent gas compositions were monitored by gas chromatography. The transport equation for dispersion and adsorption of CO2 in coal, considering Langmuir equilibrium adsorption was solved numerically. The results show that the transport of CO2 in coal resulting from dispersion and adsorption can be modeled successfully. The effects of various properties and process parameters such as porosity, Peclet number, injection gas pressure, and Langmuir parameters on gas adsorption and CO2 breakthrough were also investigated and discussed. Introduction Adsorption during flow through porous media is of interest in a number of disciplines, such as adsorptive separation processes, chromatography, soil science, and improved oil recovery. A large number of references on the subject exist(1). Miscible displacement and dispersion coupled with adsorption phenomena therefore occur in many important fields of technology, including petroleum reservoir engineering. Mechanisms that determine the transport of the displacing fluid through a porous medium include convection, dispersion and adsorption. The convection-dispersion model with adsorption has been used successfully to evaluate adsorption of a number of foam-forming surfactants from core flooding experiments in enhanced oil recovery applications(2, 3, 4). The adsorption of polymer and surfactant solutions on porous rocks is complicated by the physiochemical properties of the solutions and rocks andby the nature of the pore structure of the rock matrix. In CBM industry, reservoir modeling and simulation is essential to predict the gas recovery. The transport of CO2 gas through coalbed in CO2-ECBM process is a typical miscible displacement. In commercial CBM simulators, this process is commonly modeled by multi-component adsorption/diffusion in coal matrix with multi-phase Darcy flow in cleat system (i.e. GEM by Computer Modeling Group). This work attempts to utilize the convection-dispersion model with adsorption to model the behavior of CO2 gas flow in CO2-ECBM process and at the same time to investigate the effects of the various properties and process parameters numerically. CO2-ECBM Experiment Sample Preparation The laboratory CO2-ECBM process has been conducted by a core-flood experiment. The coal sample is a Deal Bruce core plug mined from the Manville formation in Alberta. Table 1 lists the major important characteristics of the coal sample. Prior to starting the experiments; the coal core sample was kept in a moisture chamber (25 °C, 30 mmHg) over saturated K2SO4, to simulate reservoir conditions. Proximate analysis was carried out on crushed coal sub-samples to determine moisture (ASTM D3173), ash (ASTM D3174), and volatile matter (ASTM D3175) contents(5). According to the coal rank characterization, the rank of this piece of coal is sub-bituminous B indicated byits 0.47% vitrinite reflectan
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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) | 0,000 | 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 ».