The quest for efficient well location optimization in resource extraction industries has led to the integration of advanced techniques to maximize resource recovery while minimizing operational costs and environmental impact.This work explores the application of Bayesian optimization as a powerful strategy for achieving these objectives in well placement decisions. The foundation of Bayesian optimization lies in its ability to effectively handle uncertainty and balance exploration and exploitation. This approach proves particularly advantageous in the context of well location optimization, where geological complexities, subsurface heterogeneity, and inherent uncertainties pose challenges to traditional optimization methods. In this talk, we will try to share our learnings from integrating Bayesian Optimizer with Well Location Optimizer in simple scenario. We will also cover operational performance challenges we received and our approach to overcome those challenges.