1887

Abstract

Summary

A Reservoir Data Warehouse has been successfully created where key subsurface information used for geophysical reservoir monitoring has been transformed, integrated, and stored into a geospatially registered relational database. Quantitative 4D analysis has been performed on the data, utilising the power of the massively parallel processing architecture of the high-performance analytical database, and combining traditional 4D analysis and business analytics tools. The 4D analysis successfully demonstrated quantitative relationships between the different data in the database. If desired, the integrated data model can be extended with other types of data like top side data. At its simplest the Reservoir Data Warehouse will enable a more sustainable and easily accessible solution for data integration and co-visualization, and simplification in the data management realm. At its most powerful the Reservoir Data Warehouse will enable the creation of new subsurface workflows where data from disparate origins can be analyzed jointly and presented in existing software solutions, or in newly developed cross-disciplinary software solutions.

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/content/papers/10.3997/2214-4609.20141147
2014-06-16
2022-06-29
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References

  1. Berg, E., Svenning, B., and Martin, J.
    , 1994, SUMIC – A new strategic tool for exploration and reservoir mapping: 56th EAGE Meeting, Expanded Abstracts, 477–480.
    [Google Scholar]
  2. Chopra, S. and Marfut, K.J.
    , 2012, Evolution of seismic interpretation during the last three decades, The Leading Edge, 6.
    [Google Scholar]
  3. Fayemendy, C., Espedal, P.I., Andersen. M., and Lygren. M.
    , 2012, Time-laspe seismic surveying: a multi-disciplinary tool for reservoir management on Snorre: First Break, 30, 10, 49–55
    [Google Scholar]
  4. Ferguson, S.E. and VollebregtE.J.E.
    , 2005, Accelerating technology acceptance: Blurring the lines, SPE Annual Technical Conference and Exhibition, 9–12 October 2005, Dallas, Texas.
    [Google Scholar]
  5. Inmon, W.H.
    , 1992, Building the data warehouse: Publisher, John Wiley & Sons, 1992. ISBN, 0471569607, 9780471569602.
    [Google Scholar]
  6. LaneyD.
    , 2001, 3D Data Management. Controlling Data Volume, Velocity, and Variety, Applications Delivery Strategies, File 949.
    [Google Scholar]
  7. Rognø, H., Kristensen, A., and Amundsen, L.
    , 1999, The Statfjord 3-D, 4-C OBC survey: The Leading Edge, 18, 1301–1305.
    [Google Scholar]
  8. Sandø, I., Munkvold, O.N. and Elde, R.M.
    , 2009, Two decades of 4D geophysical developments - experiences, value creation and future trends. World Oil, 230(10).
    [Google Scholar]
  9. Thompson, M. and Amundsen, L.
    , 2009, Past and future trends. Two decades of Ocean Bottom Seismic experience in light of Moore’s law: 79th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, 3395–3398.
    [Google Scholar]
  10. Watts, G.F.T.
    , 2013, Key note speech – Evolution in the PRM market place: Second EAGE Workshop on Permanent Reservoir Monitoring 2013 – Current and Future trends.
    [Google Scholar]
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