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    Random walk-percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation

    , Article Physica A: Statistical Mechanics and its Applications ; Vol. 406, issue , July , 2014 , p. 214-221 ; ISSN: 03784371 Ganjeh-Ghazvini, M ; Masihi, M ; Ghaedi, M ; Sharif University of Technology
    Abstract
    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... 

    Integration of adaptive neuro-fuzzy inference system, neural networks and geostatistical methods for fracture density modeling

    , Article Oil and Gas Science and Technology ; Vol. 69, issue. 7 , 2014 , pp. 1143-1154 ; ISSN: 12944475 Jafari, A ; Kadkhodaie-Ilkhchi, A ; Sharghi, Y ; Ghaedi, M ; Sharif University of Technology
    Abstract
    Image logs provide useful information for fracture study in naturally fractured reservoir. Fracture dip, azimuth, aperture and fracture density can be obtained from image logs and have great importance in naturally fractured reservoir characterization. Imaging all fractured parts of hydrocarbon reservoirs and interpreting the results is expensive and time consuming. In this study, an improved method to make a quantitative correlation between fracture densities obtained from image logs and conventional well log data by integration of different artificial intelligence systems was proposed. The proposed method combines the results of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural... 

    Water propagation in two-dimensional petroleum reservoirs

    , Article Physica A: Statistical Mechanics and its Applications ; Volume 445 , 2016 , Pages 102-111 ; 03784371 (ISSN) Najafi, M. N ; Ghaedi, M ; Moghimi Araghi, S ; Sharif University of Technology
    Elsevier 
    Abstract
    In the present paper we investigate the problem of water propagation in 2 dimensional (2D) petroleum reservoir in which each site has the probability p of being occupied. We first analyze this propagation pattern described by Darcy equations by focusing on its geometrical features. We find that the domain-walls of this model at p=pc ≃ 0.59 are Schramm-Loewner evolution (SLE) curves with κ=3.05 ∓ 0.1 consistent with the Ising universality class. We also numerically show that the fractal dimension of these domain-walls at p=pc is Df ≃ 1.38 consistent with SLEκ=3. Along with this analysis, we introduce a self-organized critical (SOC) model in which the water movement is modeled by a chain of...