Enhancing CO₂ huff-n-puff recovery in tight sandstone via hybrid nanofluid wettability alteration and fracturing

Tight sandstone reservoirs are constrained by low permeability and oil-wet surfaces, limiting the efficiency of enhanced oil recovery (EOR) by CO₂ huff-n-puff. This study investigates a hybrid nanofluid composed of silica nanoparticles, Triton X-100, and Rhamnolipid to improve wettability and recovery. Physicochemical characterization in terms of turbidity, dynamic light scattering analysis (DLS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) confirmed stable dispersion and favorable interfacial properties. Core huff-n-puff experiments using 38° API crude oil resulted in a recovery factor of 26.91%, which represents a 3.03% increase over the base case value of 23.88%. The accidental fracture underscored fracture-assisted flow behavior, thereby motivating the implementation of coupled simulation analysis. A CMG general equation of state model (GEM) compositional simulation, calibrated with a tuned Peng-Robinson equation of state (PR EOS), reproduced experimental data and extended the study to well configurations and fracture treatments. Opposite-well configuration (one well on both ends of the core) simulations predicted a recovery factor of 51.30%, whereas single-well setup (one well on only one end of the core for injection and production) aligned with realistic field outcomes. When wettability alteration was combined with hydraulic fracturing at the core scale, the recovery factor increased to 39.18%. Considering one well, the Field-scale extrapolation showed a cumulative oil production increasing from 8740.50 bbl of the base case to 10985.15 bbl of the treated case and 13288.48 bbl of the treated + fractured case. This study demonstrates that whereas hybrid nanofluids alone provide moderate recovery enhancement, their coupling with fracturing significantly enhances the CO₂ huff-n-puff performance in tight formations. Core-scale experimental results were critical for validating the numerical model, which was subsequently upscaled to field-scale conditions, confirming the broader applicability of the proposed approach.