1887

Abstract

Summary

We present an integrated fracture study in the Ekofisk chalk reservoir of the Kraka Field, offshore Denmark, based on core, borehole images and seismic data. The core contains numerous fractures ranging from short (cm-scale) fractures, mostly associated with chert or stylolites, to large (m-scale) open, slickensided fractures likely related to halokinesis. On borehole images, especially larger fractures are identified, coinciding in dip and dip-azimuth. Seismic data at an approximate resolution of 40m would not resolve these local features around the well-bore. We show that chromatic analysis combined with an ant-tracking algorithm extracts several lineaments (> m-scale) from the seismic data. These correlate closely in orientation and distribution with the fractures logged in the well data. It is likely that these represent fracture corridors, small faults or damage zones in the chalk. The seismic data therefore provides a valuable method for mapping the size, orientation and connectivity of fracture zones away from the well. This gives insights into the scalability of local stress fields, and fracture distributions.

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/content/papers/10.3997/2214-4609.201701283
2017-06-12
2022-05-24
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References

  1. Abramovitz, T., Andersen, C., Jakobsen, F., Kristensen, L. and Sheldon, E.
    [2010] 3D seismic mapping and porosity variation of intra-chalk units in the southern Danish North Sea. In: Geological Society, London, Petroleum Geology Conference series, 7. Geological Society of London, 537–548.
    [Google Scholar]
  2. Jorgensen, L., Andersen, P. et al
    . [1991] Integrated study of the Kraka Field. In: Offshore Europe. Society of Petroleum Engineers.
    [Google Scholar]
  3. Klinkby, L., Kristensen, L., Nielsen, E.B., Zinck-Jørgensen, K. and Stemmerik, L.
    [2005] Mapping and characterization of thin chalk reservoirs using data integration: the Kraka Field, Danish North Sea. Petroleum Geoscience, 11(2), 113–124.
    [Google Scholar]
  4. Laake, A.
    [2015] Structural interpretation in color - A new RGB processing application for seismic data. Interpretation, 3(1), SC1–SC8.
    [Google Scholar]
  5. Pedersen, S.I., Randen, T., Sonneland, L. and Steen, O.
    [2005] Automatic fault extraction using artificial ants. 512–515.
    [Google Scholar]
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