The present study deals with the evaluation of petrophysics for reservoir and source rock throughout constructing structure depth maps for the picked horizons of the Jurassic section and identifying the elements of the petroleum system. The petrophysical results exhibited that the Jurassic reservoirs show the presence of sandstone with some calcareous cement in all studied wells. Results of well log analysis of the Upper Safa reservoir showed that the thickness of the net effective pay in the studied area ranges between 28 and 70 ft., with an average effective porosity of 9%, an average hydrocarbon saturation of 78%, and an average permeability of 33 mD. However, the Lower Safa reservoirs in the study area have a net effective pay range in thickness between 29 and 60 ft., an effective porosity of 8.9%, and a hydrocarbon saturation of 75%. The geochemical characteristics of the source rocks were evaluated to identify the organic richness, types of organic matter, depositional environment, and maturity of the Jurassic source rocks based on the Rock Eval-6 pyrolysis analysis (TOC, S1, S2, Tmax, HΙ, and OΙ) for seventy (70) ditch samples penetrated by five wells in the study area. Results show that the Upper Safa source rocks are located in the late to overly mature stages and lie in the gas generation stage, while the Lower Safa source rocks are located in the early to overly mature stages and lie in the gas and oil generation stages. The main identified reservoirs in the area are toped and sealed by the intra-formational shale intervals within the reservoirs themselves, and the main traps are developed and controlled by the area structure. The current study used the above-mentioned techniques of integrating geochemical and geophysical methods to identify the main petroleum systems of the Jurassic sediments in the study area. The detailed analysis of the Upper and Lower Safa reservoirs provides a comprehensive understanding of the petrophysical properties, which are crucial for assessing the reservoir quality and potential. The calibration with measured samples ensures the reliability and accuracy of the well-logged interpretations.