Process optimization of reservoir fines trapping by mesoporous silica nanoparticles using Box-Behnken design
Mesoporous silica nanoparticles (MSNP) were used to trap reservoir fines and adsorption capacity of MSNP was optimized. Box-Behnken design was used to model effect of concentration, time, salinity and pH on adsorption capacity of reservoir fines. Multiple response surface method was applied to optim...
Gespeichert in:
Veröffentlicht in: | Alexandria engineering journal 2022-11, Vol.61 (11), p.8809-8821 |
---|---|
Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Mesoporous silica nanoparticles (MSNP) were used to trap reservoir fines and adsorption capacity of MSNP was optimized. Box-Behnken design was used to model effect of concentration, time, salinity and pH on adsorption capacity of reservoir fines. Multiple response surface method was applied to optimize any combination of variables at which the maximum adsorption of the reservoir fines occurred. Microstructural analysis shows a mesoporous structure ranging from 2.88 to 44.8 nm with high specific surface area of 332 m2/g and purity of 94%. Pseudo-second order with regression coefficient (R2) of 0.99 shows that the model best defines reservoir fines adsorption. Langmuir isotherm model with R2 of 0.985 best fitted the equilibrium adsorption of kaolinite whereas high R2 of 0.98 and lower sum of squared errors of illite for Freundlich model indicates it is better than Langmuir model. Heterogeneity factor value of 1/n |
---|---|
ISSN: | 1110-0168 |
DOI: | 10.1016/j.aej.2022.02.016 |