a novel combinatorial approach to discrete fracture network modeling in heterogeneous media

fractured reservoirs contain about 85 and 90 percent of oil and gas resources respectively in iran. acomprehensive study and investigation of fractures as the main factor affecting fluid flow or perhapsbarrier seems necessary for reservoir development studies. high degrees of heterogeneity andsparseness of data have incapacitated conventional deterministic methods in fracture networkmodeling. recently, simulated annealing (sa) has been applied to generate stochastic realizations ofspatially correlated fracture networks by assuming that the elastic energy of fractures followsboltzmann distribution. although sa honors local variability, the objective function of geometricalfracture modeling is defined for homogeneous conditions. in this study, after the introduction of saand the derivation of the energy function, a novel technique is presented to adjust the model withhighly heterogeneous data for a fractured field from the southwest of iran. to this end, the regularobject-based model is combined with a grid-based technique to cover the heterogeneity of reservoirproperties. the original sa algorithm is also modified by being constrained in different directionsand weighting the energy function to make it appropriate for heterogeneous conditions. thesimulation results of the presented approach are in good agreement with the observed field data.