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    Application of Multiscale methods for Modeling Spatial Heterogeneity in Complex Reservoirs

    , M.Sc. Thesis Sharif University of Technology Hajizadeh Mobaraki, Alireza (Author) ; Farhadpour, Farhad A (Supervisor) ; Sayf Kordi, Ali Akbar (Supervisor)
    Abstract
    Underground reservoirs are highly complicated due to the presence of spatial heterogeneities at length scales that span from micrometer in pore structure of the rocks to kilometer in the reservoir models. While large-scale flow units need to be characterized using seismic and well data, detailed displacements of fluids in pore space need to be modeled using thin section analysis and pore network modeling. It is therefore necessary to adopt a multi-scale approach to reservoir description to make best use of all the available data that vary over several orders of magnitude, from micro-scale in pore structure to field scale in reservoir flow models. In this thesis, an integrated framework for... 

    Geometrical Fracture Modeling Within Multiple-Point Statistics Framework

    , M.Sc. Thesis Sharif University of Technology Ahmadi, Rouhollah (Author) ; Masihi, Mohsen (Supervisor) ; Rasaei, Mohammad Reza (Supervisor) ; Eskandaridalvand, Kiomars (Supervisor) ; Shahalipour, Reza (Co-Advisor)
    Abstract
    Majority of the oil and gas reservoirs, in the main hydrocarbon production regions around the world, are naturally fractured reservoirs. Fractures play an important role in reservoir fluid flow either in the form of high permeable complex conduits or strong permeability anisotropies. Realistic characterization of naturally fractured reservoirs requires an exhaustive understanding of fracture connectivity and fracture pattern geometry. These subsequently demand description of many fracture parameters such as density (intensity), spacing, orientation, size and aperture. Therefore, a first step in fractured reservoirs characterization is the static geometric modeling of the subsurface fracture... 

    A multiple-point statistics algorithm for 3D pore space reconstruction from 2D images

    , Article Advances in Water Resources ; Volume 34, Issue 10 , October , 2011 , Pages 1256-1267 ; 03091708 (ISSN) Hajizadeh, A ; Safekordi, A ; Farhadpour, F. A ; Sharif University of Technology
    2011
    Abstract
    Fluid flow behavior in a porous medium is a function of the geometry and topology of its pore space. The construction of a three dimensional pore space model of a porous medium is therefore an important first step in characterizing the medium and predicting its flow properties. A stochastic technique for reconstruction of the 3D pore structure of unstructured random porous media from a 2D thin section training image is presented. The proposed technique relies on successive 2D multiple point statistics simulations coupled to a multi-scale conditioning data extraction procedure. The Single Normal Equation Simulation Algorithm (SNESIM), originally developed as a tool for reproduction of...