Over the past decades, directional drilling has continuously advanced to increase hydrocarbon recovery by effectively targeting high-productivity reservoirs. However, many existing approaches primarily focus on heuristic optimization algorithms. Moreover, existing models often neglect the incorporation of petrophysical attributes that can significantly impact the selection of production targets, such as the reservoir quality indicator. This article introduces a novel application of mixed-integer programming to define directional drilling paths, considering practical aspects of interest. The paths are subject to drift angle constraints and reference coordinates that align with the optimal reservoir targets. Such targets are identified using the authors’ proposed technique of maximum closeness centrality and the geologic model of hydraulic flow units. In order to evaluate the effectiveness of this approach, a realistic model of the Campos Basin in Brazil is studied. The results reveal that the highest recovery factors obtained with the proposed methodology (17%) exceed the historical average recovery factor of the studied reservoir (15.66%). We believe this study can contribute to the ongoing efforts to enhance directional drilling and maximize the production potential of offshore oil and gas reservoirs.