On Estimating the Water Content of CO2 in Equilibrium with Formation Brine
Notice bibliographique
Résumé
Abstract Water content of carbon dioxide (CO2) is an important parameter in engineering applications, such as CO2 storage in deep saline aquifers and enhanced oil recovery processes. Large numbers of experimental data have been reported on the solubility of CO2 in brine. However, experimental data on the water content of CO2 in equilibrium with formation brine are not reported in the literature. Water content of natural gas is traditionally calculated by general water content charts; however, these charts are not available for CO2 in equilibrium with formation brine. In this work, using an accurate fugacity and activity model available in the literature, an efficient and simple procedure is developed to estimate the water content of CO2 in equilibrium with formation brine. To validate the developed procedure, the predicted CO2 rich phase water content is compared with the reported experimental data in the literature and other predictive models for CO2-water systems. A CO2 water content chart is presented that can be used simply to predict the water content of CO2 in equilibrium with formation brine. The procedure presented may be used for generating necessary input data for flow simulation of CO2 storage in deep saline aquifers. Introduction As concern about the adverse consequences of anthropogenic climate change has grown, so has research into methods to reduce the emissions of greenhouse gases that drive future climatic change. Carbon dioxide (CO2) emissions arising from use of fossil fuels are likely to be the dominant drivers of climate change over the coming century. The use of carbon dioxide and geologic storage (or sequestration) offers the possibility of maintaining access to fossil energy while reducing emissions of carbon dioxide to the atmosphere. Many attempts have been made to mitigate this problem, and several potential methods have been proposed. Among them, the sequestration of CO2 into deep saline aquifers, depleted oil and gas reservoirs, unmineable coal seams and deep oceans are promising options (1). CO2 storage in saline aquifers is proposed for disposition atdepths greater than 800 meters, where the injected CO2 is in a supercritical state (2). The in-situ dissolution of CO2 under such conditions depends on the pressure, temperature and salinity of the resident formation brines. The precise PVT (pressure, volume, temperature) and composition properties of CO2 and brine are essential for accurate evaluation and predicting the long-term behavior of the injected fluid. Thermodynamic modeling of these properties have been attempted by many researchers, including Spycher et al.(3), Spycher and Pruess (4), Portier and Rochelle (5), Duan and Sun (6), Duan et al.(7), and Hassanzadeh et al.(8). Accurate modeling of the disposition of CO2 injected into subsurface formations requires an accurate thermodynamic model. However, using sophisticated thermodynamic models are computationally expensive and are not well suitable for CO2 storage. It is, therefore, important to use a simple but accurate thermodynamic model for a very specific case of geological CO2 sequestration (8).
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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) | 0,003 | 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 ».