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Multivariate geostatistics

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Geostatistics and petroleum geology
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Abstract

There are several situations where one may want to study and exploit the covariance between two or more regionalized variables.

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References

  • Bashore, W.M., Araktingi, U.G., Levy, M. and Schweller, W.J. (1994) Importance of a geological framework and seismic data integration for reservoir modeling and subsequent fluid-flow predictions, in J.M. Yarus and R.L. Chambers (eds), Stochastic Modeling and Geostatistics. American Association of Petroleum Geologists, Tulsa, OK, pp. 159–175.

    Google Scholar 

  • Chambers, R.L., Zinger, M.A. and Kelly, M.C. (1994) Constraining geostatistical reservoir descriptions with 3-D seismic data to reduce uncertainty, in J.M. Yarus and R.L. Chambers (eds), Stochastic Modeling and Geostatistics. American Association of Petroleum Geologists, Tulsa, OK, pp. 143–157.

    Google Scholar 

  • Chu, J., Xu, W. and Journel, A.G. (1994) 3-D implementation of geostatistical analyses — the Amoco case study, in J.M. Yarus, and R.L. Chambers (eds), Stochastic Modeling and Geostatistics, American Association of Petroleum Geologists, Tulsa, OK, pp. 201–216.

    Google Scholar 

  • Clark, I., Basinger, K.L. and Harper, W.V. (1989) MUCK — a novel approach to cokriging, in B.E. Buxton, (ed.), Proceedings of the Conference on Geostatistical, Sensitivity, and Uncertainty Methods for Ground-Water Flow and Radionuclide Transport Modeling, Battelle Press, Columbus, OH, pp. 473–493.

    Google Scholar 

  • Columbia Gas System Service Corporation (1985) Southwest West Virginia Data Book, Issue 2, April 1985, for Gas Research Institute Contract No. 5083–213–0856.

    Google Scholar 

  • Davis, B.M., and Greenes, K.A. (1983) Estimation using spatially distributed multi variate data: an example with coal quality. Math. Geol. 15, 287–300.

    Article  Google Scholar 

  • Deutsch, C.V. and Journel, A.G. (1998) GSLIB: Geostatistical Software Library and User’s Guide. Oxford University Press, New York, 369 pp.

    Google Scholar 

  • Galli, A. and Meunier, G. (1987) Study of a gas reservoir using the external drift method, in G. Matheron and M. Armstrong (eds), Geostatistical Case Studies. D. Reidel, Dordrecht, pp. 105–119.

    Chapter  Google Scholar 

  • Myers, D.E. (1982) Matrix formulation of co-kriging. Math. Geol., 14, 249–257.

    Article  Google Scholar 

  • Myers, D.E. (1983) Estimation of linear combinations and co-kriging. Math. Geol., 15, 633–637.

    Article  Google Scholar 

  • Myers, D.E. (1991) Pseudo-cross variograms, positive-definiteness, and cokriging. Math. Geol. 23, 805–816.

    Article  MathSciNet  MATH  Google Scholar 

  • Papritz, A., Künsch, H.R. and Webster, R. (1993) On the pseudo cross variogram. Math. Geol., 25, 1015–1026.

    Article  MathSciNet  MATH  Google Scholar 

  • Wackernagel, H. (1995) Multivariate Geostatistics: An Introduction with Applications. Springer-Verlag, New York, 256 pp.

    MATH  Google Scholar 

  • Xu, W., Tran, T., Srivastava, R.M. and Journel, A.G. (1992) Integrating Seismic Data in Reservoir Modeling: the Collocated Cokriging Alternative. Proceedings of Society of Petroleum Engineers Technical Conference, pp. 833–842.

    Google Scholar 

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© 1999 Springer Science+Business Media Dordrecht

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Hohn, M.E. (1999). Multivariate geostatistics. In: Geostatistics and petroleum geology. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4425-4_4

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  • DOI: https://doi.org/10.1007/978-94-011-4425-4_4

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-5901-5

  • Online ISBN: 978-94-011-4425-4

  • eBook Packages: Springer Book Archive

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