Discrete Fracture Network (DFN) Modelling of Fractured Reservoir Based on Geomechanical Restoration, a Case Study in the South of Iran (Rudarsko-geološko-naftni zbornik, 2021)
Fractured reservoirs have always been of interest to many researchers because of their complexities and importance in the oil industry. The purpose of the current study is to model the fractured reservoir based on geomechanical restoration. Our target is the Arab Formation reservoir which is composed of seven limestone and dolomite layers, separated by thin anhydrite evaporate rock. First of all, in addition to the intensity, the dip, and the azimuth of the fractures, the magnitude and the direction of the stresses are determined using wireline data e.g. photoelectric absorption factor (PEF), sonic density, neutron porosity, a dipole shear sonic imager (DSI), a formation micro imager (FMI), and a modular formation dynamics tester (MDT). Then, the seismic data are interpreted and the appropriate seismic attributes are selected. One of our extracted attributes was the ant tracking attribute which is used for identifying large-scale fractures. Using this data, fractures and faults can be identified in the areas away from wells in different scales. Subsequently, the initial model of the reservoir is reconstructed. After that, the stress field and the distribution of fractures are obtained using the relationship between the stresses, the strains, and the elastic properties of the existing rocks. The model is finely approved using the azimuth and the intensity of fractures in the test well. Our findings showed that the discrete fracture network (DFN) model using geomechanical restoration was positively correlated with real reservoir conditions. Also, the spatial distribution of fractures was improved in comparison to the deterministic-stochastic DFN.