SmartWater Effects on Wettability, Adhesion and Oil Liberation in Carbonates
Notice bibliographique
Résumé
Abstract The chemistry of injection water affects oil recovery from carbonate reservoirs by SmartWater flooding. It is widely believed that the ions present in the SmartWater alter the wettability of carbonate rocks, depending on their type and the amounts present. Although some effort has been made to understand the effects of salinity and water ion compositions on wettability in carbonates, the prior research studies were mostly limited to contact angle, spontaneous imbibition and coreflooding. In the current study, adhesion forces between a carbonate substrate and a crude oil droplet in the brines of varying ionic compositions were measured directly by using a custom-designed integrated thin film drainage apparatus (ITFDA) equipped with a bimorph force sensor. In addition, the liberation kinetics of crude oil from carbonate rocks was determined using an optical microscope-based liberation cell at both ambient and elevated temperatures. These measurements were complemented with thermogravimetric analysis (TGA) and standard macroscopic data such as water contact angles and zeta potentials. The effect of individual cations (Ca2+, Mg2+) and anions (SO42-) on wettability, adhesion and oil liberation in carbonates was studied by using reservoir rock surfaces, reservoir crude oil and different brines composed of a single type of salts at a fixed low salinity. Both deionized (DI) water and low salinity brine composed of sufficient amounts of three key ions (Ca2+, Mg2+ and SO42-) were used as the baseline for selected experiments. The results showed a significant increase in water wettability (or decrease in contact angles) with low salinity brines when compared to deionized water, depending on the type of ions present in these brines. The presence of SO42- increased the water wettability the most, followed by Ca2+ and Mg2+ ions. The zeta potential data of carbonate rock minerals in DI water/brines showed similar trends on surface charges to correlate well with contact angles. Increasing the water wettability of brines on carbonate surfaces decreased the adhesion force between oil and the rock in the corresponding brines. Such favorable changes in adhesion forces in turn led to more efficient crude oil liberation from carbonates at microscopic scale when exposed to different low salinity brines than in DI water. The dynamic oil liberation data from carbonates at the elevated temperature demonstrated significant advantage of low salinity brine containing SO42- ions when compared to DI water, but showed only its slight effectiveness over the low salinity brine composed of three key ions. The thermogravimetric analysis further confirmed the efficiency of both the low salinity brines, composed of SO42- and the three key ions, to liberate more crude oil from carbonates. The findings from different microscopic to macroscopic scale measurements reported in this work clearly indicate the importance of both lower salinity and major role of certain ions in the SmartWater to effectively release crude oil from carbonates. It can also be concluded that low salinity water containing sufficient amount of three key ions can become a practical SmartWater for waterflooding operations, considering the adverse impact of SO42- ions on the interactions at crude oil/water interface as well as the reservoir damage resulting from scaling and souring issues.
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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 | 0,000 | 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) | 0,001 | 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 ».