1887

Abstract

Summary

Reservoir models can be improved through the incorporation of process-based models as training images for simulation with MPS. Process-based models in this study are reported to be excellent sources of training images. When combined with knowledge of depositional stratigraphic information, delta complex architectural trends can be accurately reproduced. This approach is applicable to systems that are well constrained by knowledge of depositional processes that can be efficiently synthetized to generate an appropriate process model-derived training image.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201800772
2018-06-11
2024-04-26
Loading full text...

Full text loading...

References

  1. Chidsey, T. Adams, R.D. and Morris, T.H.
    [2004] Regional to Wellbore Analog for Fluvial-Deltaic Reservoir Modelling: The Ferron Sandstone of Utah.
    [Google Scholar]
  2. Chugunova, L.T, and Hu. L.Y.
    [2008] Multiple-point Simulations Constrained by Continuous Auxiliary Data, Mathematical Geosciences, 40, p. 133–146.
    [Google Scholar]
  3. Mariethoz, G. and Caers, J.
    [2014] Multiple-point Geostatistics: Stochastic Modelling with Training Images.
    [Google Scholar]
  4. Michael, H. Li, H. Boucher, A. Sun, T. Caers, J. and Gorelick, S.M.
    [2010] Combining Geological-process Models and Geostatistics for Conditional Simulation of 3D Subsurface Heterogeneity, Water Resources Research, 46.
    [Google Scholar]
  5. Miller, J. Sun, T. Li, H. Stewart, J. Centry, C. Li, D. and Lyttle, C.
    [2008] Direct Modelling of Reservoirs through Forward Process-based Models: Can we get there?International Petroleum Technology Conference, 3–5th December 2008, Kuala Lumpur, Malaysia.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201800772
Loading
/content/papers/10.3997/2214-4609.201800772
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