Artículo de publicación ISISin acceso a texto completoDeterministic modeling of the geological domains is often restricted to the uncertainty assessment. Using stochastic modeling can be considered as an effective solution in order to overcome this restriction. It can also be effectively used for evaluation of ore bodies. Sequential indicator simulation as a stochastic modeling method is a widely used technique to characterize the categorical variables such as facies, rock types, alterations, and mineralized zones. Inverting the categorical variables to indicators proposes the global and local variability of the variable under study by descriptive and spatial statistics. In this study, this approach has been applied to a set of experimental data acquired from Daralu ore deposit located in southern part of the Urumieh-Dokhtar magmatic arc, south of Kerman province, SE Iran. Kerman province hosts several porphyry copper deposits in which calculation of probabilistic description of four normally presented mineralized zones (hypogene, supergene, oxide, and leached zones) for evaluation of relevant ore bodies would be advisable.National Iranian Copper Industries Co. (NICICO

The formation of gas condensate near the wellbore affects the gas liquid two-phase flow between the pores. It may occur in the path between two pores depending on the thermodynamic conditions of the single-phase gas flow, two-phase gas liquid annular flow or the closed path of condensate in the throat. To model the behavior of gas condensate in a network of pores, relative permeability and naturally pressure drop should be calculated. This study obtained the flow characteristics (pressure drop) between the pores at different physical and geometric conditions using computational fluid dynamics (CFD). CFD is time-consuming, so its results were transferred to an artificial neural network (ANN) model and the ANN model was trained. The CFD was replaced with the ANN model for calculating the pressure drop. In addition, instead of utilizing empirical correlations to compute the accurate value of condensate formed in throats' corners at every time step, the flash calculation using Esmaeilzadeh–Roshanfekr equation of state was performed, and closed throats were specified. This accurately estimates gas and condensate distribution in the pore network. Furthermore, the value of condensate that transferred to the adjacent throats was computed using Poiseuille's law. The results showed that the proposed ANN-based proxy model could promote the calculation speed in gas condensate simulation, considering the dynamic change of relative permeability curves as a function of gas condensate saturation. Also, it was found that the relative permeability obtained by the proposed model is in good agreement with the experimental data. By entering the fractures pattern in the network model and predicting the relative permeability of gas and condensate by the proposed method, the role of fractures in gas condensate production in such reservoirs could be predicted. Dynamic changes due to the relative permeability of gas and condensate as a function of saturation can be entered into the reservoir simulation to optimize inertia and positive coupling phenomena to maximized condensate production in gas condensate reservoir.