Geochemical modeling along with chemical reactions is one of the challenges in modeling of low salinity water injection. The most important issue in the geochemical model is to determine the correct electrical charge distribution model and its tuning parameters. The composition of the rock as well as the candidate water used is effective in determining the type of model and its parameters, so that the tuning parameters are determined based on the history of zeta potential experiments. In this study, in order to determine the correct model of electrical charge distribution and its tuning parameters in carbonate rock samples, first, equilibrium samples of Candidate water with crushed rock are subjected to static zeta potential tests. Then, the diffuse electrical double layer model is used to determine the electrical charge of the rock/water and water/oil surfaces and to predict the zeta potential. In the following, by adjusting the tuning parameters of the model to match the prediction results of the model with the history of the laboratory data, the density of the carbonate rock surface, the equilibrium constants and the kinetics of the governing reactions are determined. The obtained results show that the range of error in zeta potential prediction by the model compared to the laboratory data is from 2 to 20%, which is within the acceptable range of the performance of electrical charge distribution models. Moreover, it could be observed that the error of prediction using DLM model is significantly less than the conventional models (CD-MUSIC and BSM) for different candidate water. Finally, the effect of calculated zeta potential changes is used to calculate the contact angle changes of low salinity water injection based on the coupling of DLVO theory and geochemical model. The results of the study prove that the prediction error is less than 5% compared to the results of the static wettability tests. Based on this, according to the good match between the model and the laboratory results, it is possible to determine the properties of surface sites in surface complexation models of carbonate samples using the proposed approach and the subsequent tuning data of the geochemical model.