Fines Migration Control in Sandstone Reservoirs: DLVO Modeling for Critical Salt Concentration and Critical Flow Rate Prediction

Critical salt concentration (CSC) is the minimum salt concentration of injected water, below which fines migration occurs in sandstone reservoirs. Sand grains and fine particles experience Van der Waals attraction, electric double-layer repulsion, and hydrodynamic forces. Injection brine salinity and flow rate affect repulsion and hydrodynamic forces. Accurate CSC and critical flow rate prediction are crucial to prevent formation damage. This research presents a novel DLVO modeling approach for predicting and controlling fines migration in sandstone reservoirs. DLVO models are developed to predict fines migration initiation and CSCs for monovalent and divalent brines at different reservoir salinities. The models incorporate 0.1wt% silica nanofluid, resulting in reduced CSC. Zeta potentials are measured for sand-fine-brine (SFB) systems with and without silica nanofluid. Surface forces between fines and sand are calculated at varying salinities to predict CSC. A fines detachment model is also developed using zeta potentials and electrostatic, gravitational, and hydrodynamic forces to predict critical flow rate under changing salinity. Models are validated through core flood experiments conducted on Berea Upper Gray sandstone cores. The zeta potentials of SFB systems are measured at room temperature using a zeta-sizer. In pre-nanofluid application, zeta potentials range from -35 mV to -27 mV, while post-application, they range from -28.6 mV to -27 mV. Zeta potentials and corresponding ionic strengths are used in the DLVO model to calculate the total interaction potential (P_T). The DLVO model predicts a CSC of around 0.11 M for NaCl brine, where total DLVO interactions shift from negative to positive. Incorporating silica nanofluid reduces CSC further to 0.075 M, showcasing the effectiveness of nanoparticles. CSCs of 0.0001 M are predicted for MgCl₂ and CaCl₂ brines. The novel fines detachment model, using zeta potentials, electrostatic, gravitational, and hydrodynamic forces, predicts critical flow rates of 0.9 cc/min, 2.9 cc/min, and 3.8 cc/min for NaCl concentrations of 0.15 M, 0.2 M, and 0.25 M, respectively. Core flood experiments validate the models, closely matching predictions: CSCs of 0.11 M and 0.075 M before and after nanofluid treatment, and critical flow rates of 1 cc/min, 3 cc/min, and 4 cc/min for NaCl concentrations of 0.15 M, 0.2 M, and 0.25 M. This validation confirms the reliability and applicability of the models in fines migration control and reservoir management. Estimating CSC and critical flow rate is essential to prevent formation damage during oil recovery processes, such as waterflooding and alkaline flooding. The proposed DLVO models serve as valuable tools for predicting CSC and critical flow rates for different salinities, minimizing the need for extensive experimentation. Incorporating nanotechnology and its experimental validation offers new insights for controlling fines migration within the practical limits of fluid salinity and injection rates.