Advertisement

Mathematical Geology

, Volume 28, Issue 7, pp 843–856 | Cite as

Quantifying uncertainty in reservoir performance using streamtubes

  • Marco R. Thiele
  • Srinivas E. Rao
  • Martin J. Blunt
Article

Abstract

We present the use of a streamtube approach to study the uncertainty in reservoir performance resulting from a stochastic description of the flow domain. The streamtube technique is an efficient numerical method which is particularly effective for modeling convective displacements that are dominated by large-scale heterogeneities. Stable, numerical-diffusion-free solutions can be obtained in a fraction of the time taken by conventional finite difference simulators, thereby allowing a statistical approach to reservoir simulation and forecasting.

Key words

reservoir simulation production forecasting streamtubes streamlines stochastic generation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aziz, K., 1993, Reservoir simulation grids: opportunities and problem: Journal of Petroleum Technology, v. 45, no. 7, p. 658–663.Google Scholar
  2. Ballin, P. R., Journel, A. G., and Aziz, K., 1992, Prediction of uncertainty in reservoir performance forecast: Jour. Can. Petrol. Tech., v. 31, no. 4, p. 52–62.Google Scholar
  3. Ballin, P. R., Aziz, K., Journel, A. G., and Zuccolo, L., 1993, Quantifying the impact of geological uncertainty on reservoir performance forecasts: SPE Paper Number 25238, presented at the 12th SPE Symposium on Reservoir Simulation Symposium (New Orleans, LA), p. 47–67.Google Scholar
  4. Blunt, M. J., Barker, J. W., Rubin, B., Mansfield, M., Culverwell, L. D., and Christie, M. A., 1994, Predictive theory for viscous fingering in compositional displacement: SPEC Reservoir Engineering, v. 9, no. 1, p. 73–80.Google Scholar
  5. Chang, Y.-B., Lim, M. T., Pope, G. A., and Sepehrnoori, K., 1994, CO2 flow patterns under multiphase flow: heterogeneous field scale conditions: SPE Reservoir Engineering, v. 9, no. 3, p. 208–216.Google Scholar
  6. Christie, M., 1989, High resolution of unstable flows in porous media: SPE Reservoir Engineering, v. 4, no. 3, p. 297–303.Google Scholar
  7. Davis, J. C., 1986, Statistics and data analysis in geology (2nd ed.): John Wiley & Sons, New York, 646 p.Google Scholar
  8. Deutsch, C. V., and Journel, A. G., GSLIB Geostatistical Software Library and user's guide: Oxford Univ. Press, New York, 340 p.Google Scholar
  9. Dongarra, J. J., Doff, I. S., Sorensen, D. C., and van der Vorst, H. A., 1991, Solving linear systems on vector and shared memory computers: SIAM, 3600 University City Science Center, Philadelphia, PA 19104-2688, unpaginatedGoogle Scholar
  10. Emanuel, A. S., Alameda, G. K., Bchrens, R. A., and Hewett, T. A., 1989, Reservoir performance prediction methods based on fractal geostatistics: SPE Reservoir Engineering, v. 4, no. 3, p. 311–318.Google Scholar
  11. Hewett, T., and Behrens, R., 1991, Scaling laws in reservoir simulation and their use in a hybrid finite difference/streamtube approach to simulation the effects of permeability heterogeneity,in Lake, L., and Carroll, H. B., eds., Reservoir Characterization II: Academic Press, London, p. 402–441.Google Scholar
  12. Higgins, R. V., and Leighton, A. J., 1962, A computer method to calculate two-phase flow in any irregularly bounded porous medium: Jour. Petroleum Technology, v. 14, no. 6, p. 679–683.Google Scholar
  13. Intera Information Technologies Limited, 1994, Eclipse 100 Reference Manual—95A Release: Intera Information Technologies Limited, Henly-on-Thames, Oxfordshire RG9 4PS, England, unpaginated.Google Scholar
  14. Lake, L. W., Johnston, J. R., and Stegemeier, G. L., 1981, Simulation and performance prediction of a large-scale surfactant/polymer project: Soc. Petroleum Engineers Jour., v. 21, no. 12, p. 731–739.Google Scholar
  15. Tchelepi, H., and Orr, F., Jr., 1994, Interaction of viscous fingering, permeability heterogeneity, and gravity segregation in three dimensions, SPE Reservoir Engineering, v. 9, no. 4, p. 266–271.Google Scholar
  16. Thiele, M. R., Blunt, M. J., and Orr, F. M., 1995a, Modeling flow in heterogeneous media using streamtubes—I. Miscible and immiscible displacements: In Situ, v. 19, no. 3, p. 299–339.Google Scholar
  17. Thiele, M. R., Blunt, M. J., and Orr, F. M., 1995b, Modeling flow in heterogeneous media using streamtubes—II. Compositional displacements: In Situ, v. 19, no. 4, p. 367–391.Google Scholar
  18. Thiele, M. R., Batycky, R. P., Blunt, M. J., and Orr, F. M., 1996, Simulating flow in heterogeneous media using streamtubes and streamlines: SPE Reservoir Engineering, v. 10, no. 1, p. 5–12.Google Scholar

Copyright information

© International Association for Mathematical Geology 1996

Authors and Affiliations

  • Marco R. Thiele
    • 1
  • Srinivas E. Rao
    • 1
  • Martin J. Blunt
    • 1
  1. 1.Department of Petroleum EngineeringStanford UniversityStanford

Personalised recommendations