Rock Physics Modeling Assisted Reservoir Properties Prediction: Case Study in Malay Basin

  • Authors

    • Amir Abbas Babasafari
    • Deva Ghosh
    • Ahmed M. A. Salim
    • S Y. Moussavi Alashloo
    2018-08-26
    https://doi.org/10.14419/ijet.v7i3.32.18385
  • Litho-facies, reservoir modeling, reservoir properties prediction, rock physics modeling, petrophysical properties
  • Shear velocity log is not measured at all wells in oil and gas fields, thus rock physics modeling plays an important role to predict this type of log. Therefore, seismic pre stack inversion is performed and elastic properties are estimated more accurately. Subsequently, a robust Petro-Elastic relationship arising from rock physics model leads to far more precise prediction of petrophysical properties. The more accurate rock physics modeling results in less uncertainty of reservoir modeling. Therefore, a valid rock physics model is intended to be built. For a better understanding of reservoir properties prediction, first of all rock physics modeling for each identified litho-facies classes should be performed separately through well log analysis.

     

     

  • References

    1. [1] Ghosh D., Halim MFA, Brewer M and Viratno B (2010), “Geophysical issues and challenges in Malay and adjacent basins from an E & P perspective,†Leading Edge, vol. 29, pp. 436–449.

      [2] Ghosh D., Babasafari A., Ratnam T., and Sambo C. (2018), "New Workflow in Reservoir Modelling - Incorporating High Resolution Seismic and Rock Physics", Offshore Technology Conference. doi:10.4043/28388-MS.

      [3] Ghosh D., Sajid M and Ibrahim NA (2014), “Seismic attributes add a new dimension to prospect evaluation and geomorphology offshore Malaysia,†Leading Edge, vol. 33, pp. 536–545.

      [4] Avseth P, Mukerji T, Mavko G (2010), “Quantitative seismic interpretation: Applying rock physics tools to reduce interpretation risk†Cambridge University Press.

      [5] Johansen, A., Jensen, E., Mavko, G., and Dvorkin, J. (2013), “Inverse rock physics modeling for reservoir quality prediction†Geophysics, vol. 78, No. 2, P. M1–M18.

      [6] Jensen, E., Johansen, A., Avseth, P. and Bredesen, K. (August 2016), “Quantitative interpretation using inverse rock-physics modeling on AVO dataâ€, The Leading Edge.

      [7] Bredesen, K., Jensen, E., Johansen, T. and Avseth, P. (2015), “Quantitative seismic interpretation using inverse rock physics modellingâ€, Petroleum Geoscience.

      [8] Russell B. (2014), “Rock Physics Templatesâ€.

      [9] Russell B. and Smith T. (2007), “The relationship between dry rock bulk modulus and porosity–an empirical study,†CREWES Res. Rep., vol. 19, pp. 1–14.

      [10] Russell B. (2013), “A Gassmann-consistent rock physics template,†in CSEG Recorder, pp. 22–30.

      [11] Mavko, G., Mukerji, T., and Dvorkin, J. (2009), “The Rock Physics Handbook: Tools for Seismic Analysis of Porous Media†Cambridge University Press.

      [12] Avseth, P., Jørstad, A.,van Wijngaarden, A. J., and Mavko, G. (2009), “Rock physics estimation of cement volume, sorting, and net-to-gross in North Sea sandstones†The Leading Edge, 28, 98–108.

      [13] Dvorkin, J., Gutierrez, M. A., and Grana, D. (2014), “Seismic reflections of rock properties†Cambridge University Press.

  • Downloads

  • How to Cite

    Abbas Babasafari, A., Ghosh, D., M. A. Salim, A., & Y. Moussavi Alashloo, S. (2018). Rock Physics Modeling Assisted Reservoir Properties Prediction: Case Study in Malay Basin. International Journal of Engineering & Technology, 7(3.32), 24-28. https://doi.org/10.14419/ijet.v7i3.32.18385