Dual energy coarse-resolution computed tomography (CT) scans reveal the density and atomic number volumes in carbonate samples. The atomic number volumes are resolved for the calcite and dolomite mineralogy volumes. These mineralogy and density volumes are converted into the total porosity volumes. To convert these mineralogy and porosity volumes into the effective elastic properties, we require a rock physics model relating the elastic bulk and shear moduli to porosity and mineralogy. Such a model is established by analysing wireline data from a well drilled in the oil field under examination. Two effective-medium models are established for these wireline data: the constant cement model and the differential effective medium model. To match the data, we found the coordination number and shear correction factor in the first model and the inclusion aspect ratio in the second model. In addition, we found the zero-porosity elastic property end points — bulk and shear moduli of pure calcite to match the wireline data. Both rock physics models were applied to the porosity and mineralogy volumes. This methodology offers ways of estimating the velocities in wells where wireline data are not available, e.g., horizontal wells or in legacy wells where rock material has been preserved.


Article metrics loading...

Loading full text...

Full text loading...


  1. Abbad, A., and Dvorkin, J.
    [2016] Estimating Rock Transport Properties of Sandstone and Carbonate Samples Using Coarse-resolution 3D Dual Energy Images. 78th EAGE Conference and Exhibition 2016.
    [Google Scholar]
  2. Arns, C. H., Knackstedt, M. A., Pinczewski, W. V., and Garboczi, E. J.
    [2002] Computation of linear elastic properties from microtomographic images: Methodology and agreement between theory and experiment. Geophysics, 67, 1396–1405.
    [Google Scholar]
  3. Bosl, W. J., Dvorkin, J., and Nur, A.
    [1998] A study of porosity and permeability using a lattice Boltzmann simulation. Geophysical Research Letters, 25, 1475–1478.
    [Google Scholar]
  4. Derzhi, N., Dvorkin, J., Fang, Q., and Suhrer, M.
    [2015] Method for improving the accuracy of rock property values derived from digital images. US Patent 9,047,513 B2.
    [Google Scholar]
  5. Dvorkin, J., and Derzhi, N.
    [2015] Method and system for estimating rock properties from rock samples using digital rock physics imaging. US Patent, 9,046,509 B2.
    [Google Scholar]
  6. Dvorkin, J., Armbruster, M., Baldwin, C., Fang, Q., Derzhi, N., Gomez, C., and Nur, A.
    [2008] The future of rock physics: computational methods vs. lab testing. The First Break, 26, 63–68.
    [Google Scholar]
  7. Dvorkin, J., Derzhi, N., Diaz, E., and Fang, Q.
    [2011] Relevance of computational rock physics, Geophysics, 76, E141-E153.
    [Google Scholar]
  8. Dvorkin, J., Gutierrez, M., and Grana, D.
    [2014] Seismic Reflections of Rock Properties, Cambridge University Press.
    [Google Scholar]
  9. Keehm, Y., Mukerji, T., and Nur, A.
    [2001] Computational rock physics at the pore scale: Transport properties and diagenesis in realistic pore geometries. The Leading Edge, 20, 180–183.
    [Google Scholar]
  10. Knackstedt, M. A., Arns, C. H., and Pinczewski, W. V.
    [2003] Velocity-porosity relationships, 1: Accurate velocity model for clean consolidated sandstones. Geophysics, 68, 1822–1834.
    [Google Scholar]
  11. Mavko, G., Mukerji, T., and Dvorkin, J.
    [2009] The rock physics handbook: Tools for seismic analysis of porous media.Cambridge University Press.

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error