Multi-Scale and Multi-Physics Methods for Numerical Modeling of Fluid Flow in Fractured Formations

Abstract

Abstract Natural fractures reside in various subsurface formations and are at various length scales with different intensities. Fluid flow in fractures, in matrix and between matrix and fractures are following different flow physics. It is thus a great challenge for efficiently modeling and simulation of fluid flow in fractured media due to the multi-scale and multi-physics nature of the flow processes. Traditional dual porosity and permeability approach represents factures and matrix as different continuum. The transfer functions or shape factors are derived to couple the fluid flow in matrix and fractures. The dual porosity and permeability model can be viewed as a multi-scale method and the transfer functions are used to propagate fine-scale information to the coarse-scale reservoir simulation. In this paper, we perform a detailed study to better understand the optimal way to propagate the fracture information to the coarse-scale model based on the detailed fracture characterization at fine-scale. We use two different upscaling procedures. One is the multiple sub-region method (SPE 102491) that is based on the dual porosity and permeability approach. The other is using Stokes-Binkman equation (SPE 105377) to solve the fine-scale flow problem and then deriving the upscaling information from the fine-scale solution. The Discrete Fracture Modeling (DFM) approach is used to represent each fracture individually and explicitly. Then, both the multiple sub-region method and Stokes-Brinkman equations are used to solve for fine-scale flow information based on the DFM. The fine-scale information captured by these two approaches are used in coarse-scale reservoir simulations respectively. The two approaches are compared in terms of how well they preserve key fine-scale flow dynamics in the coarse simulations. We then propose an efficient and accurate upscaling workflow for numerical modeling of fractured media, which will extends predicting capability in efficient development of fractured reservoirs.