Abstarct: Welbore instability is one of the most significant problems in drilling practice. This instability is usually related to mechanical properties of formation as well as distribution of stress around the wellbore wall. Thus, if exact estimation of geomechanical parameters and stress distribution around the wellbore wall is done precisely, those problems causing the wellbore to be instabled, will be reduced. In this regard, the aim of this paper is to determine the geomechanical parameters of reservoir rocks using well logs data in order to evaluate the effect of these parameters on the wellbore stability through drilling process. To do this, conventional well logs data and drilling reports of sevral wells located in Darquain oil field were used. In the first step, elastic parameters of reservoir rocks were estimated and calibrated using the data obtained from conducting uniaxial compressive strength (UCS) on the core samples. Uniaxial compressive strength of reservoir rocks was also estimated by empirical correlation and calibrated via the data obtained from UCS test. To determine the in-situ stresses, elastic parameters as well as pore pressure data are required. Thus, through utilizing of Eaton equation and fitting curves on the sonic log, pore pressure log was determined continuously. The model of pore pressure was then calibrated against moduar dynamic formation tester (MDT) data. In this stage, much more studies on the data resulted in proposing a new empirical correlation for determination of pore pressure in fields including carbonate reservoirs. Having geoemchnical parameters and pore pressure available, magnitude of in-situ stresses were calculated and calibrated using the mud loss data as well as Zoback’s polygon method. Direction of in-situ stress was identified using formation micro scanner (FMS) and caliper log data. Tangantial, radial and axial stresses have then been determined using Kirsch equations. Using these stresses and three rock failure criteria, including Mohr-Columb, Hoek-Brown and Mogi-Columb, optimum safe mud window was recommended. The result indicates that the Mogi-Coulomb criterion is able to provide much better results in comparison with other two criteria used for this study.