Process optimization of reservoir fines trapping by mesoporous silica nanoparticles using Box-Behnken design

Abstract

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 < 1 and n values of 5–11 shows sufficient site for adsorption. Predicted reservoir fines adsorption with R2 of kaolinite (98.77%) and illite (99.32%) close to unity indicates that the model is highly consistent with the experimental results with high precision and reliability. Experimental and statistical analysis proved that MSNP can fixate reservoir fines and has adequate capacity to be rejuvenated and reused.