A Practical Methodology To Estimate The Fracture Spacing In A Dual-porosity Model From Discrete Fracture Networks

The dual-porosity model and discrete fracture network (DFN) model are two common approaches used to simulate field scale multiphase flow in naturally fractured reservoirs. While the DFN approach has several advantages, for example, it can explicitly take into account the geometry, conductivity and connectivity of fracture networks, it is seldom used in field scale multiphase flow simulation due to the difficulties in describing the flow exchange between the matrix and fractures and also due to the requirements of an excessive number of elements in spatial discretization. As an alternative, many researchers have sought to use the DFN model to upscale geological information into the dual porosity model to simulate multiphase flow (Bourbiaux et.al., 1999 and 2005; Dershowitz et.al., 2000). Fracture spacing is widely used to estimate input parameters (for example, shape factor) in a dual-porosity multiphase flow model. Based on the assumption that the conditions in rock matrix are controlled primarily by the distance from the fractures, a function called the "proximity function" can be defined in a certain volume of subdomain as the total fraction of matrix volume within a distance from fracture faces (Pruss, 1985). A practical way is proposed to compute the proximity function for a 3D subdomain characterized by a DFN with the help of Monte Carlo simulation. For a subdomain described by an ideal dual porosity model, the proximity function is a function of unknown fracture spacing which can be written analytically. Based on the computed proximity function of DFN subdomain, an optimization problem to minimize the difference between two proximity functions is set up. Solving this optimization problem, unknown fracture spacing that is appropriate for the dual porosity model can be estimated.