Sharif Digital Repository

Fluid flow modeling in porous media has many applications in waste treatment, hydrology and petroleum engineering. In any geological model, flow behavior is controlled by multiple properties. These properties must be known in advance of common flow simulations. When uncertainties are present, deterministic modeling often produces poor results. Percolation and Random Walk (RW) methods have recently been used in flow modeling. Their stochastic basis is useful in dealing with uncertainty problems. They are also useful in finding the relationship between porous media descriptions and flow behavior. This paper employs a simple methodology based on random walk and percolation techniques. The... 

In force gas/oil gravity drainage process in fractured porous media, gas is flowing in both matrix and fractures leading to produce a finite gas pressure gradient. Consequently, viscous force plays an important role for displacing matrix oil toward fractures in addition to gravity force that is required to be modeled appropriately. A new analytical model for estimation of steady state oil saturation distribution with assumption of fixed gas pressure gradient throughout the matrix is presented. Moreover, based on some results of this analytical model a different numerical formulation is developed to predict the performance of oil production process. Comparison of the results obtained from... 

The prediction of flow behavior in porous media can provide useful insights into the mechanisms involved in CO2 sequestration, petroleum engineering and hydrology. The multi-phase flow is usually simulated by solving the governing equations over an efficient model. The geostatistical (or fine grid) models are rarely used for simulation purposes because they have too many cells. A common approach is to coarsen a fine gird realization by an upscaling method. Although upscaling can speed up the flow simulation, it neglects the fine scale heterogeneity. The heterogeneity loss reduces the accuracy of simulation results. In this paper, the relation between heterogeneity loss during upscaling and... 

An upscaling method such as renormalization converts a detailed geological model to a coarse one. Although flow equations can be solved faster on a coarse model, its results have more errors. Numerical dispersion, heterogeneity loss, and connectivity misrepresentation are the factors responsible for errors. Connectivity has a great effect on the fluid distribution and leakage pathways in EOR processes or CO2 storage. This paper deals with the description and quantification of connectivity misrepresentation in the upscaling process. For detection of high-flow regions, the flow equations are solved under simplified single-phase conditions. These regions are recognized as the cells whose fluxes... 

The connectivity between two points in porous media is important for evaluating hydrocarbon recovery in underground reservoirs or toxic migration in waste disposal. For example, the connectivity between a producer and an injector in a hydrocarbon reservoir impact the fluid dispersion throughout the system. The conventional approach, flow simulation, is computationally very expensive and time consuming. Alternative method employs percolation theory. Classical percolation approach investigates the connectivity between two lines (representing the wells) in 2D cross sectional models whereas we look for the connectivity between two points (representing the wells) in 2D aerial models. In this...