1887

Abstract

Summary

In this paper, we first subsample numerous datasets from digital rock model, and then the subvolumes were used to simulate the elastic properties with FEM solver. We verified the FEM results through ultrasonic measurements, and presented the cross-plot of acoustic velocity versus porosity. Regardless of the pore shape, Vp-φ crosspiot showed chaotic and scatter. Based on 3D porous structure of each subvolume, we classified such data points into several groups by different pore type. We found that for a certain porosity, pore type greatly affects the acoustic velocities of carbonate rocks. For an instance, we can observe that the acoustic velocities of carbonate rocks with moldic pores are much higher than the ones of carbonate rocks with dissolved intercrystalline pores. Carbonate rocks with compliant pores, let’s say fracture or microcrack, exhibit the lowest acoustic velocity compared with the ones with stiffer pores like moldic pores. Through the classification approach in terms of pore type, one can obtain better correlations between acoustic velocity and porosity concerning with different pore-type carbonate. This probably enables us to gain profound insights into carbonate reservoir prediction based on reservoir inversion with digital rock physics knowledge.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201800673
2018-06-11
2024-03-29
Loading full text...

Full text loading...

References

  1. ArnsC H, KnackstedtM A, PinczewskiW V, et al
    . Computation of linear elastic properties from microtomographic images: Methodology and agreement between theory and experiment[J]. Geophysics, 2002, 67(5): 1396–1405.
    [Google Scholar]
  2. DvorkinJ, NurA
    . Scale of experiment and rock physics trends [J]. Leading Edge, 2009, 28(1): 110–115.
    [Google Scholar]
  3. Eberhart-Phillips, D., Han, D. & Zoback, M.
    , 1989. Empirical relationships among seismic velocity, effective pressure, porosity, and clay content in sandstone, Geophysics, 54(1), 82–89.
    [Google Scholar]
  4. Garboczi, E.J., Day, A.R.
    , 1995. An algorithm for computing the effective linear elastic properties of heterogeneous materials: three-dimensional results for composites with equal phase poisson ratios. J. Mech. Phys. Solids43, 1349–1362.
    [Google Scholar]
  5. Jouini, M.S., Vega, S., Al-Ratrout, A.
    , 2015. Numerical estimation of carbonate rock properties using multiscale images. Geophys. Prospect. 63, 405–421.
    [Google Scholar]
  6. Makarynska, D., Gurevich, B., Ciz, R., Arns, C.H., Knackstedt, M.A.
    , 2008. Finite element modelling of the effective elastic properties of partially saturated rocks. Comput.Geosci.34, 647–657.
    [Google Scholar]
  7. Mavko, G., Mukerji, T., Dvorkin, J.
    , 2009. The Rock Physics Handbook: Tools for Seismic Analysis of Porous Media. Cambridge University Press.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201800673
Loading
/content/papers/10.3997/2214-4609.201800673
Loading

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