Abstract
Sequential simulation is a powerful stochastic simulation technique the theory of which relies on the ability to determine, for a given multivariate model, the conditional probability of a single random variable given any number of conditioning values. Sequential simulation can be used with those multivariate models for which these conditional probabilities can be determined. In practice, it is not enough to know how to determine the conditional probabilities, the procedure must be feasible from an operational point of view. Because it is not so in most cases, some approximations to the conditional probability distribution function are used in the implementation of the technique. These approximations are shown not to have a large impact in the performance of the technique, at least for the case in which the underlying multivariate model is multiGaussian.
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References
Alabert, F. G. (1987). The practice of fast conditional simulations through the lu decomposition of the covariance matrix. Math. Geology, 19(5):369–387.
Anderson, T. W. (1984). Multivariate statistical analysis. Wiley, New York.
Deutsch, C. V. and Journel, A. G. (1992). GSLIB, Geostatistical Software Library and User’s Guide. Oxford University Press, New York.
Górmez-Hernández, J. J. and Journel, A. G. (1993). Joint simulation of multiGauussian random variables. In Soares, A., editor, Geostatistics Tróia ’92, volume 1, pages 85–94. Kluwer.
Gómez-Hernández, J. J. and Srivastava, R. M. (1990). ISIM3D: An ANSI-C three dimensional multiple indicator connditional simulation program. Computer and Geosciences, 16(4):395–440.
Guardiano, F. B. and Srivastava, R. M. (1993). Multivariate geostatistics: Beyond bivariate models. In Soares, A., editor, Geostatistics Tróia ’92, volume 1, pages 133–144. Kluwer.
Isaaks, E. H. and Srivastava, R. M. (1989). An Introduction to Applied Geostatistics. Oxford Press, New York.
Journel, A. G. (1983). Non-parametric estimation of spatial distributions. Math. Geology, 5(3):445–468.
Journel, A. G. (1989). Fundamentals of Geostatistics in Five Lessons, volume 8 of Short Courses in Geology. AGU, Washington D.C.
Journel, A. G. (1993). Geostatistics: Roadblocks and challenges. In Soares, A., editor, Geostatistics T róia ’92, volume 1, pages 213–224. Kluwer.
Journel, A. G. and Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press. London.
Matheron, G. (1976). A simple substitute for conditional expectation: the disjunctive kriging. In Advanced Geostatistics in the Mining Industry, pages 221–236, Rome. NATO ASI.
Omre, H., Sølna, K., and Tjelmeland, H. (1993). Simulation of random functions on large lattices. In Soares, A., editor, Geostatistics Tróia ’92, volume 1, pages 179–199. Kluwer.
Verly, G. W. (1993). Sequential gaussian cosimulation: A simulation method integrating several types of information. In Soares, A., editor, Geostatistics Tróia ’92, volume 1, pages 543–554. Kluwer.
Xiao, H. (1985). A description of the behavior of indicator variograms for a bivariate normal distribution. Master’s thesis, Stanford University.
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© 1994 Springer Science+Business Media Dordrecht
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Gómez-Hernández, J.J., Cassiraga, E.F. (1994). Theory and Practice of Sequential Simulation. In: Armstrong, M., Dowd, P.A. (eds) Geostatistical Simulations. Quantitative Geology and Geostatistics, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8267-4_10
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DOI: https://doi.org/10.1007/978-94-015-8267-4_10
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4372-6
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