Abstarct: The oil and gas industry, as the primary source of global energy supply, has always faced numerous technical challenges in the fields of extraction and production. Among these, drilling operations—being the frontline method for accessing hydrocarbon reservoirs—are characterized by a high level of complexity and sensitivity. The success of these operations largely depends on the proper performance of the drilling fluid, commonly known as drilling mud. This research was designed and conducted with the aim of simulating, analyzing, and optimizing drilling fluid parameters in order to simultaneously reduce two major drilling challenges: bit wear and formation damage. The study was carried out using operational data from Well F 5 in the Valo oil field. Due to the geomechanical and hydraulic complexities encountered during drilling operations, the use of a hybrid analytical–intelligent approach was required. Therefore, after modeling the baxseline conditions using governing equations (a combination of the Adnoy force transfer model, the Archard wear relationship, and the Hawkins formation damage equation), the Particle Swarm Optimization (PSO) algorithm was developed to determine the optimal equilibrium point. The most significant quantitative and qualitative achievement of this research was establishing a balance between two phenomena with physically conflicting requirements—bit wear and formation damage. Simulation results showed that the algorithm successfully reduced the skin factor by a remarkable 84.08% compared to the actual field operation, while simultaneously improving the bit wear index by 2.23%. This balance indicates that the algorithm prevented excessive increases in viscosity (which reduces wear but damages the formation) and proposed the most optimal condition for safe field application