In order to properly meet up with the ever-increasing demand for petroleum products worldwide, it has become increasingly necessary to produce oil and gas fields more economically and efficiently. Waterflooding is currently the most widely used secondary recovery method to improve oil recovery after primary depletion. A crucial component required to conduct an efficient waterflooding operation is an optimal production setting, most especially with respect to the amount of water involved. This research work has been carried out to develop a model that can be used to maximize oil recovery and minimize water production with the least amount and number of waterflood variables in order to minimize the secondary recovery investment cost. The gradient-based approach to optimize the production and net present value (NPV) from a waterflood reservoir using the flow rates or bottom hole pressures of the production wells as the controlling factors with the use of smart well technology was applied. In this approach, a variant of the optimal switching time technique was used in the optimization process to equalize the arrival times of the waterfront at multiple producers, thereby increasing the cumulative oil production. The optimization procedure involved maximizing the objective function (NPV) by adjusting a set of manipulated variables (flow rates). The optimal pressure profile of the waterflood scenario that gave the maximum NPV was obtained as the solution to the waterflood problem. The proposed optimization methodology was applied to a waterflood process carried out on a reservoir field developed by a five-spot recovery design in the Niger Delta area of Nigeria, which was used as a case study. The forward run was carried out with a commercial reservoir oil simulator. The results of the waterflood optimization revealed that an increase in the net present value of up to 9.7% and an increase in cumulative production of up to 30% from the base case could be achieved.