The choice of appropriate and affordable procedures to boost oil recovery is usually recognized as one of the main challenges in reservoir development due to the huge demand for crude oil. Reservoir flow simulators are valuable tools for understanding and forecasting fluid flow in complex systems. The goal of this study is to run a mathematical model to evaluate the performance of various oil recovery methods, as well as to validate the model's accuracy with simulated field data. Thereby, the results of this developed model indicate that the model is approximately matched with the simulated field data. Enhanced oil recovery typically refers to chemical, miscible, thermal, and microbial processes. A system of nonlinear partial differential equations composed of Darcy's and mass conservation equations governs the model. The system is then numerically solved using the IMPEC (Implicit Pressure and Explicit Concentration) scheme by a finite difference method. We chose this approach because the experimental approaches are not only time consuming, but also costly. As a result, mathematical models could aid in the understanding of a reservoir and how such processes can be optimized to maximize oil recovery while lowering production costs. This paper provides a brief overview of mathematical modelling of various enhanced oil recovery methods, focusing on developing a generalized framework and describing some of the key challenges and opportunities.