Skip to main content
Log in

Modeling of Fluvial Reservoirs with Object Models

  • Published:
Mathematical Geology Aims and scope Submit manuscript

Abstract

An object model for fluvial reservoirs that has been developed from 1985 to present is described. It uses a formal mathematical object model (marked point process) describing the distributions of four facies: channel, crevasse, barrier, and background. Realisations from the model are generated using the Metropolis-Hastings simulation algorithm with simulated annealing conditioning on the volume ratios and well observations. The main challenge has been to find a suitable parameterization of the geology of fluvial reservoirs, and to find and implement the generating function of the channels in the simulation algorithm. The model and simulation algorithm can be conditioned on arbitrary well paths including horizontal wells and paths with partly missing observations, well test data, well contacts, seismic data, and general geological knowledge.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  • Allen, J. R. L., 1978, Studies in fluviatile sedimentation: an exploratory quantitative model for the architecture of avulsion-controlled alluvial suites: Sedimentary Geology, v. 21, p. 129–147.

    Google Scholar 

  • Allen, J. R. L., 1979, Studies in fluviatile sedimentation: an elementary model for the connectedness of avulsion-related channel sand bodies: Sedimentary Geology, v. 24, p. 253–267.

    Google Scholar 

  • Bridge, J., 1993, Description and interpretation of fluvial deposits: a critical perspective: Sedimentology, v. 40, p. 801–810.

    Google Scholar 

  • Bridge, J., and Leeder, M. R., 1979, A simulation model of alluvial stratigraphy: Sedimentology, v. 26, p. 617–644.

    Google Scholar 

  • Clemetsen, R., Hurst, A. R., Knarud, R., and Omre, H., 1989, A computer program for evaluation of fluvial reservoirs, in Buller, A. T., Berg, E., Hjelmeland, O., Kleppe, J., Torsæter, O., and Aasen, J. O., eds., North Sea Oil and Gas Reservoirs—II, proceedings from 2nd North Sea Oil and Gas Reservoirs Conference: Graham & Trotman, Trondheim, Norway, p. 373–385.

    Google Scholar 

  • Damsleth, E., Tjølsen, C. B., Omre, H., and Haldorsen, H. H., 1990, A two-stage stochastic model applied to a north sea reservoir, in 65th Annual Technical Conference and Exhibition, Soc. of Petroleum Engineers, New Orleans.

  • Deutsch, C. V., and Cockerham, P., 1994, Practical considerations in the application of simulated annealing to stochastic simulation: Math. Geology, v. 26,no. 1, p. 67–82.

    Google Scholar 

  • Deutsch, C. V., and Wang, L., 1996, Quantifying object-based stochastic modeling of fluvial reservoirs: Math. Geology, v. 28,no. 7, p. 857–880.

    Google Scholar 

  • Dubrule, O., 1993, Introducing more geology in stochastic reservoir modeling, in Soares, A., ed., Geostatistics Tróia '92, proc. 4th Inter. Geostat. Congr., Tróia Portugal, 1992: Kluwer Academic Publ., Dordrecht, p. 351–370.

    Google Scholar 

  • Egeland, T., Georgsen, F., Knarud, R., and Omre, H., 1993, Multi facies modeling of fluvial reservoirs, in proc. of 68th Annual Technical Conference and Exhibition, Soc. of Petroleum Engineers, Houston, Texas, p. 863–872.

  • Fält, L. M., Henriquez, A., Holden, L., and Tjelmeland, H., 1991, Moheres, a program system for simulation of reservoir architecture and properties, in Proc. from the Sixth European Symposium on Improved Oil Recovery: Stavanger, Norway, p. 27–39.

  • Geman, S., and Geman, D., 1984, Stochastic relaxation, Gibbs distribution, and Bayesian restoration of images: IEEE Trans. Pattern Analysis and Machine Intelligence, v. 6, p. 721–741.

    Google Scholar 

  • Georgsen, F., and Omre, H., 1993, Combining fiber processes and Gaussian random functions for modeling fluvial reservoirs, in Soares, A., ed., Geostatistics Tróia '92, proc. 4th Inter. Geostat. Congr., Tróia Portugal, 1992: Kluwer Academic Publ., Dordrecht, p. 425–440.

    Google Scholar 

  • Georgsen, F., Egeland, T., Knarud, R., and Omre, H., 1994, Conditional simulation of facies architecture in fluvial reservoirs, in Armstrong, M., and Dowd, P., eds., Geostatistical Simulations, Vol. 7 of Quantitative Geology and Geostatistics, Proc. of the Geostatistical Simulation Workshop, Fontainebleau, France, 1993: Kluwer Academic Publ., Dordrecht, p. 235–250.

    Google Scholar 

  • Gundesø, R., and Egeland, O., 1989, SESIMIRA—a new geological tool for 3-D modeling of heterogeneous reservoirs, in Buller, A. T., Berg, E., Hjelmeland, O., Kleppe, J., Torsaeter, O., and Aasen, J. O., ed., North Sea Oil and Gas Reservoirs—II, proc. from 2nd North Sea Oil and Gas Reservoirs Conference: Graham & Trotman, Trondheim, Norway, p. 363–371.

    Google Scholar 

  • Haldorsen, H. H., and Damsleth, E., 1990. Stochastic modeling: J. Petr. Techn., April, p. 404–412.

  • Hastings, W. K., 1970, Monte Carlo sampling methods using Markov chains and their applications: Biometrika, v. 57,no. 1, p. 97–109.

    Google Scholar 

  • Hegstad, B. K., Omre, H., Tjelmeland, H., and Tyler, K., 1994, Stochastic simulation and conditioning by annealing in reservoir description, in Armstrong, M., and Dowd, P. ed., Geostatistical Simulations, Vol. 7 of Quantitative Geology and Geostatistics, Proceedings of the Geostatistical Simulation Workshop, Fontainebleau, France, 1993: Kluwer Academic Publ., Dordrecht, p. 43–55.

    Google Scholar 

  • Hjort, N. L., and Omre, H., 1994, Topics in spatial statistics: Scand. J. Statist., v. 21,no. 4, p. 289–357.

    Google Scholar 

  • Holden, L., 1996, Geometric convergence of the metropolis-hastings simulation algorithm: Preprint, University of Oslo.

  • Holden, L., Omre, H., Solberg, R., and Taxt, T., 1986, Technical documentation of the sisabosasystem., NR-note SAND/12/86, Norwegian Computing Center, P.O. Box 114 Blindern, N-0314 Oslo, Norway.

    Google Scholar 

  • Journel, A. G., and Alabert, F. G., 1990, New method for reservoir mapping: J. Petr. Techn., v. 42,no. 2, p. 212–218.

    Google Scholar 

  • Lia, O., Omre, H., Tjelmeland, H., Holden, L., and Egeland, T., 1997, Uncertainties in reservoir production forecasts: Am. Assoc. Petroleum Geologists Bulletin, v. 81,no. 5, p. 775–802.

    Google Scholar 

  • Macdonald, A., Falt, L. M., and Hektoen, A., 1997, Stochastic modeling of incised valley geometries: Am. Assoc. Petroleum Geologists Bulletin.

  • Mackey, S. D., and Bridge, J. S., 1995, Three-dimensional model of alluvial stratigraphy: Theory and application: J. of Sedimentary Research, v. 65,no. 1, p. 7–31.

    Google Scholar 

  • Martinius, A., 1996, The sedimentological characterisation of labyrinthine fluvial reservoir analogues: PhD thesis, Tech. rep., Delft University of Technology, Netherland, 300 p.

    Google Scholar 

  • Ripley, B. D., 1981, Spatial Statistics: John Wiley & Sons, New York, 252 p.

    Google Scholar 

  • Skare, Ø., Skorstad, A., Hauge, R., and Holden, L., 1997, Conditioning a fluvial model on seismic data, in Baafi, E. Y., and Schofield, N. A., ed., Geostatistics Wollongong '96, proc. 5th Inter. Geostat. Congr., Wollongong Australia, 1996: Kluwer Academic Publ., Dordrecht, p. 465–476.

    Google Scholar 

  • Skorstad, A., and Holden, L., 1997, Direct conditioning on well test data, in Baafi, E. Y., and Schofield, N. A., eds., Geostatistics Wollongong '96, proc. 5th Inter. Geostat. Congr., Wollongong Australia, 1996: Kluwer Academic Publ., Dordrecht, p. 562–572.

    Google Scholar 

  • Tyler, K. J., Henriquez, A., and Svanes, T., 1994, Modeling heterogeneities in fluvial domains: a review on the influence on production profile, in Yarus, J. M., and Chambers, R. L., eds., Stochastic Modeling and Geostatistics, AAPG Computer Applications in Geology, No. 3: The American Association of Petroleum Geologists, Tulsa, Oklahoma 74101, p. 379.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Holden, L., Hauge, R., Skare, Ø. et al. Modeling of Fluvial Reservoirs with Object Models. Mathematical Geology 30, 473–496 (1998). https://doi.org/10.1023/A:1021769526425

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1021769526425

Navigation