A novel workflow to optimize well placement using geomechanical constraints is introduced to maximize production performance, reduce excessive simulation runs, and minimize drilling constraints by considering the local stress field and the petrophysical properties in a given reservoir. A case study is presented for optimization of horizontal well placement in the Monterey Formation of Miocene Age in California. First, a three-dimensional reservoir model of formation pressure, in situ stresses, petrophysical and rock properties were built from available petrophysical and well log data. Second, numerical modeling using material point method (MPM) was applied to generate the differential stress field, taking into consideration a three-dimensional natural fracture network in the reservoir model. Third, an optimization algorithm which incorporates petrophysical properties, natural fracture distribution, differential stresses, and mechanical stability was used to identify the best candidate locations for well placement. Finally, flow simulations were conducted to segregate each candidate location where both natural and hydraulic fractures were considered. Statistical methods identify optimal well positions in areas with low differential stress, high porosity, and high permeability. Several candidate locations for well placement were selected and flow simulations were conducted. A comparison of the production performance between the best candidates and other randomly selected well configurations indicates that the workflow can effectively recognize scenarios of optimum well placement. The proposed workflow provides practical insight on well placement optimization by reducing the number of required reservoir simulation runs and maximizing the hydrocarbon recovery.