1887
PDF

Abstract

Summary

Natural fractures in shale formations can provide a pathway for higher permeability; therefore, they need to be characterized. The characterization of small-scale features is a challenge when dealing with conventional seismic methods. Seismic resolution has limitations for understanding sub-seismic scale structural patterns, stratigraphic variations and reservoir heterogeneities.

Minor fault trends, stratigraphic edges and fractures represent scattering sources for seismic wave propagation. The wavefield generated by those source points is identified as diffraction energy. This energy is always registered during seismic acquisition, but suppressed by standard processing sequences and imaging algorithms. The method explained in this paper is based on an imaging algorithm that maps the recorded surface information into the local angle domain (LAD). The differentiator of this method is its ability to preserve the wavefield through decomposition into reflection and diffraction energy. This paper shows the benefits of LAD technology when applied to the Eagle Ford play in South Texas, where seismic data can be of moderate quality, leading to accurate, high-resolution, and high-certainty seismic interpretation for risk management in field development.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201702535
2017-11-23
2024-04-25
Loading full text...

Full text loading...

/deliver/fulltext/2214-4609/2017/UR13.html?itemId=/content/papers/10.3997/2214-4609.201702535&mimeType=html&fmt=ahah

References

  1. BerkovitchA., BelferI., HassinY. and LandaE.
    [2009] Diffraction imaging by multifocusing. Geophysics, 74, no. 6.
    [Google Scholar]
  2. GrasmueckM. MoserT. and PelissierM.
    [2012] Stop Treating Diffractions as Noise. Use Them for Imaging of Fractures and Karst. AAPG Hedberg Conference, Fundamental Controls on Flow in Carbonates, Saint-Cyr Sur Mer, France.
    [Google Scholar]
  3. KorenZ. and RavveI.
    [2011] Full azimuth subsurface angle domain wavefield decomposition and imaging Part 1 and 2. Geophysics76, no 1, S1–s13.
    [Google Scholar]
  4. MoserT. J. and HowardC. B.
    [2008] Diffraction Imaging in Depth. Geophysical Prospecting, 56, 627–641.
    [Google Scholar]
  5. Roberts, A.
    , [2001], Curvature attributes and their application to 3-D interpreted horizons: First Break, v. 19/2, p. 85–100.
    [Google Scholar]
  6. Koren, Z., I.Ravve, and R.Levy
    , [2010], Specular-diffraction imaging from directional angle decomposition: 72nd Conference and Exhibition, EAGE, Extended Abstracts, G045.
    [Google Scholar]
  7. G.Yelin, B.de Ribet, Y.Serfaty and D.Chase
    , [2016], Multi-dimensional Seismic Data Decomposition for Improved Diffraction Imaging and High Resolution Interpretation: 78th European Association of Geoscientists and Engineers (EAGE), Extended Abstracts.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201702535
Loading
/content/papers/10.3997/2214-4609.201702535
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