1887

Abstract

Summary

Numerical models of the reservoirs usually depend on a set of uncertain parameters. To adjust these parameters and build representative models, the dynamic behavior of many reservoir models needs to be investigated, what can be very time consuming. A way to handle this difficulty consists in building proxy models to approximate the responses of interest from a limited number of simulated values. These models, also called response surfaces, can then replace the calls to the fluid-flow simulator.

In reservoir engineering, many simulation outputs depend on time or space. However, the response surfaces only approximate scalars, what can be a strong limitation to properly study uncertainties: building a proxy model per time or space takes time and neglects possible correlations. An alternative methodology is thus considered here. It consists in building response surfaces for new variables deduced from a reduced-basis approach, what makes it possible to approximate grid outputs from a limited number of response surfaces. A more systematic uncertainty analysis for grid outputs as well as new tools for history matching can then be envisaged.

In this paper, we propose to investigate the potential of the approach for seismic attributes, considering a synthetic Steam Assisted Gravity Drainage (SAGD) produced field.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201413035
2015-06-01
2024-03-28
Loading full text...

Full text loading...

References

  1. Feraille, M., and Marrel, A.
    [2012] Prediction under uncertainty on a mature field. OGST, 67(2), 193–206.
    [Google Scholar]
  2. Marrel, A., Perot, N.
    [2012] Development of a surrogate model and sensitivity analysis for an atmospheric dispersion computer code. Proceedings of PSAM 11 & ESREL 2012 Conference, Helsinki, Finland, June2012.
    [Google Scholar]
  3. Douarche, F., Da Veiga, S., Feraille, M., Enchery, G., Touzani, S. and Barsalou, R.
    [2014] Sensitivity analysis and optimization of surfactant-polymer flooding under uncertainties. OGST, 69(4), 603–617.
    [Google Scholar]
  4. Tillier, E., Le Ravalec, M. and Da Veiga, S.
    [2012] Simultaneous Inversion of Production Data and Seismic Attributes: Application to a Synthetic SAGD Produced Field Case. OGST, 67(2), 289–301.
    [Google Scholar]
  5. Lerat, O., Adjemian, F., Baroni, A., Etienne, G., Renard, G., Bathelier, E., Forgues, E., Aubin, F., Euzen, T.
    [2010] Modelling of 4D Seismic Data for the Monitoring of Steam Chamber Growth During the SAGD Process. J. Can. Pet. Technol., 49(6), 21–30.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201413035
Loading
/content/papers/10.3997/2214-4609.201413035
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