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Application of Multiscale methods for Modeling Spatial Heterogeneity in Complex Reservoirs

Hajizadeh Mobaraki, Alireza | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 42646 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Farhadpour, Farhad A; Sayf Kordi, Ali Akbar
  7. Abstract:
  8. 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 heterogeneity modeling from pore to field scale, using data from various scales is presented. We use advanced statistical and probability concepts of multiple-point statistics and gradual deformation and develop two reconstruction algorithms, each with a particular design, to generate 3D geologically realistic representations of porous media from a single high-resolution 2D thin section image. The proposed reconstruction methods are capable of generating geologically realistic representations of underground porous media and are at least an order of magnitude faster than the recently developed reconstruction algorithms available in the literature. Using these faithful and computationally efficient algorithms, we successfully reconstruct equi-probable 3D pore structures from a single 2D thin section image. The 3D reconstructions are validated using experimental data reported for two unstructured porous solids, namely the Berea sandstone and synthetic Silica. We extract the pore network models from the 3D voxelated images using the maximal-ball algorithm and use them to obtain the single (porosity, absolute permeability) and two-phase (capillary pressure and relative permeability curves) fluid properties. The calculated properties from pore network modeling may be exported to the highresolution geological models to obtain a plausible distribution of the petrophysical properties. At the geological grid scale an improved direct sampling (DS) algorithm is developed. The improved algorithm increases the computational efficiency of the original DS algorithm by applying a search procedure based on partial ranking technique to find the desired number of nearest neighbors on a simulation grid. In addition, a modified definition of the distance function is used to accept or reject a sample and a multiscale informing procedure is adopted to inform the simulation grid patch-wise rather than pixel-wise. The improved DS algorithm reduces the CPU-time of the original DS algorithm up to 10 folds. Finally, a geometrically based upscaling technique is developed that upscales the high-resolution geological grid to flow simulation grid using the image segmentation algorithm of Quadtree decomposition. This algorithm quickly produces upscaled grids based solely on geometrical attributes of the geological grid. Limiting the level of decomposition, results in the desired coarse model, which in turn makes the numerous flow simulations performed in processes like history matching viable
  9. Keywords:
  10. Multiple Point Statistics ; Two Phase Flow ; Upscaling ; Image Segmentation ; Spatial Heterogeneity ; Pore Space Reconstruction ; Pore-to-Field Modeling

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