Experimental study and geochemical modeling of the effect of asphaltene during smart water flooding in carbonate reservoirs

Understanding the role of crude oil properties, especially the asphaltene content of crude oil is crucial for enhancing the efficiency of smart water flooding, as it significantly impacts wettability and recovery factors. This study evaluates the predictive capabilities of a developed geochemical model for predicting wettability alteration during smart water flooding in carbonate reservoirs. Three types of oil samples with varying asphaltene content were employed: crude oil (8.5% asphaltene), deasphalted oil (1.8% asphaltene), and asphaltene-enriched toluene (98% asphaltene). Core flooding experiments were conducted using five types of brines: seawater, twice the sulfate concentration (2SO₄), four times the sulfate concentration (4SO₄), four times the calcium concentration (4Ca), and four times the magnesium concentration (4Mg). The model integrates DLVO (Derjaguin, Landau, Verwey, and Overbeek) theory and calculates zeta potential and disjoining pressure based on the crude oil/brine/rock (COBR) system properties such as ionic composition and oil properties. Recovery factor measurements and contact angle analyses confirmed the model's accuracy, with seawater injection in asphaltene-rich oil resulting in the most negative electrical double layer (EDL) pressure (- 350 MPa) and a recovery factor of 10%. Conversely, 4Mg brine demonstrated superior performance in promoting water-wet conditions for both crude oil (21.34% recovery factor) and deasphalted oil (18.41% recovery factor). This study underscores the critical role of brine composition and crude oil properties in optimizing smart water flooding strategies and validates the geochemical model as a robust tool for tailoring brine compositions to enhance oil recovery in carbonate reservoirs.