Reservoir Characterization to Inexpensively Evaluate the Exploitation Potential of a Small Morrow Incised Valley-fill Field

Kansas Geological Survey
Open-file Report 2002-9

Reservoir Simulation


  1. The auto-correlation technique used pattern matching of wireline log signatures between adjacent wells to automatically delineate reservoir sand bodies. It also effectively identified the producible porosity within these sand bodies. The 3D-reservoir model developed by application of this technique closely resembled that obtained from traditional geologic analysis.
  2. Correlations exist between Swi and K for both clean and argillaceous sands. Capillary pressure curves were modeled using equations that use absolute permeability as the independent variable and utilize variables representing threshold entry pressure, capillary pressure curve shape, and irreducible water saturation response to pore-throat size distribution.
  3. Synthetic relative permeability curves were constructed using Corey-type equations, and these were anchored on measured Swi and Sorw data. The curve shapes were defined by the limited existing relative permeability data available for Morrow sands.
  4. A spreadsheet-based pattern recognition technique, Super-Pickett analysis, was used to analyze wireline logs. The Super-Pickett provided an effective template to integrate log data with core data.
  5. Identification and distribution of sand bodies, synthetic capillary pressure curves and relative permeability data were incorporated to create a 3D-reservoir model that served as the basis for a PC-based simulation study of the Minneola field.
  6. Successful match of primary and secondary production and flowing pressure (Pwf) history was obtained for a majority of the wells in a based reservoir simulation study.
  7. After history matching, Swi and K data from sand #2 (major producing layer) was overlaid on corresponding core data. It revealed that the effective lithology of the reservoir rock was a combination of both clean and argillaceous sands. This substantiated that reservoir permeability was refined within geologic reason during history matching.
  8. This field study, therefore, demonstrates the applicability of cost-effective tools, such as, auto-correlation, Super-Pickett analysis, and modeling of capillary pressure and relative permeability data in reservoir characterization studies. The capillary pressure and relative permeability modeling techniques are critical for fields where laboratory measured data are not available.



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Last updated March 2002