Static Adsorption Evaluation for Anionic-Nonionic Surfactant Mixture on Sandstone in the Presence of Crude Oil at High Reservoir Temperature Condition
Notice bibliographique
Résumé
Summary The application of surfactants in enhanced oil recovery (EOR) has revealed over the years various challenges that impose limitations on the successful implementation of surfactant flooding. Surfactant adsorption is one of the most important aspects that strongly dictates the feasibility of surfactant-based EOR. The effect of the presence of crude oil on surfactant adsorption and the influence of surfactant partitioning on the adsorption quantification are presented in this paper. Static adsorption experiments were conducted in this study for a surfactant mixture [alkyl ether carboxylate (AEC):alkylpolyglucoside (APG)] on sandstone rock samples in the absence and presence of crude oil. Partitioning experiments were carried out to evaluate the surfactant partitioning between the aqueous surfactant solution and the crude oil to determine the partitioning influence on the adsorption results in the presence of crude oil. The mixture’s adsorption and partitioning behaviors were studied at a fixed salinity of 32 k ppm and temperatures of 80 and 106°C. High-performance liquid chromatography (HPLC) was used in measuring the surfactant concentration throughout adsorption and partitioning tests. Rock characterization was also performed in this study using X-ray diffraction (XRD) as well as X-ray photoelectron spectroscopy (XPS) before and after adsorption with and without crude oil being present. Static adsorption outcomes displayed the adsorption of APG, AEC, and the overall mixture with and without crude oil being present, because all are having a similar increasing trend when concentration increases. However, the adsorption values were much higher when crude oil was present as compared with the adsorption values when crude oil was absent; this is because of not considering the impact of surfactant partitioning. The adsorption values (i.e., at 0.2 wt%) for both temperatures were below 2.5 mg/g in the absence of crude oil and rose to around 3.5 mg/g in the presence of crude oil. A significant amount of what was adsorbed belongs to AEC because of its increased chain-chain interactions with APG, which was evidenced experimentally in our previous work; hence, AEC is the greatest contributor to the overall surfactant mixture’s adsorption. Also, temperature had an impact on the adsorption capacity of the AEC:APG mixture, showing that APG has a greater sensitivity to temperature in comparison to AEC. The adsorption behavior of APG was found to be the opposite of AEC, where the adsorption capacity at 106°C was lower for AEC than its adsorption capacity at 80°C and vice versa for APG. The surfactant partitioning results were used to validate the surfactant adsorption outcomes in the presence of crude oil. After eliminating the partitioning effect, the surfactant adsorption isotherms in both cases of the presence and the absence of crude oil were almost identical. The results highlighted the importance of measuring surfactant partitioning, and the impact that partitioning has on the total surfactant losses during the surfactant flooding process. XRD and XPS results indicated that the change of the rock structure after adsorption when crude oil was present was attributed to the rock dissolution phenomena. It was concluded that adsorption and partitioning take place in the water/oil/rock system simultaneously and taking that into account allows for the improved and proper designing of the surfactant flooding.
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| 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 ».