Application of DLVO Modeling to Predict Critical pH for Fines Migration Pre- and Post-SiO2 and MgO Nanofluid Treatments in Sandstones

Abstract

Injection water pH affects the release of fines in sandstones. The force equilibrium between fines and sand governs the attachment or release of fines in the system. At a pH higher than a critical value, fines are released and block the pores, causing formation damage. The fines release can be avoided by adjusting the pH and using nanofluids. This paper introduces the concept of DLVO modeling to estimate the critical pH before and after the application of nanofluids without extensive experimentation. Scanning electron microscopy determines the average size of in-situ fines collected from the sandstone core. Injection brine of 11700 ppm and 0.1 wt% SiO2 nanofluid are prepared, the zeta potentials of dispersed sand are measured with varying pH from 2 to 12, and the resulting attractive and repulsive surface forces between fines and sand grains are quantified. The DLVO models are developed to predict the mobilization of fines and a critical pH before and after the application of silica nanofluid. The zeta potentials are measured by a Zetasizer and are in the range of -5 mV (less repulsion) to - 31 mV (more repulsion). Furthermore, the application of nanofluids increases the zeta potential to a range of -3 mV to - 24.9 mV, indicating a compression in electric double layers. Measured zeta potentials, ionic strength, and fine size are used as inputs to compute surface forces, and DLVO models are developed. The critical pH, at which total DLVO interactions shift from negative to positive, as predicted by the model, is about 8. A separate DLVO model predicted an improved critical pH of 11 following the use of SiO2 nanofluid, demonstrating a reduction in repulsion forces. Furthermore, the DLVO model estimated a critical pH of 12 after using 0.0075 wt% MgO nanofluid, demonstrating the greater efficiency of MgO nanoparticles even at low concentrations. DLVO modeling approach gives a new insight into predicting critical pH before and after applying nanofluids, and nanotechnology validates the ability of nanoparticles to control fines migration and improve critical pH for waterflooding and alkaline flooding operations.