1993
DOI: 10.1007/978-94-011-1739-5_43
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Including a Regional Trend in Reservoir Modelling Using the Truncated Gaussian Method

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Cited by 30 publications
(13 citation statements)
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“…Truncation thresholds depend on the proportions of facies in each litho-unit and on the relationship between the different lithotypes (contacts and transitions). The Gaussian Random Function is stationary but the proportions (hence the thresholds) can vary in space (Beucher et al, 1993;Galli et al, 1994;Le Loch and Galli, 1996;Doligez et al, 2007). This method was applied to litho-units corresponding to point bar deposits (litho-units 1, 2 and 6), and to chute channels heterogeneously filled by sands and shales (litho-units 5, 8 and 9).…”
Section: Geostatistical Parametersmentioning
confidence: 99%
“…Truncation thresholds depend on the proportions of facies in each litho-unit and on the relationship between the different lithotypes (contacts and transitions). The Gaussian Random Function is stationary but the proportions (hence the thresholds) can vary in space (Beucher et al, 1993;Galli et al, 1994;Le Loch and Galli, 1996;Doligez et al, 2007). This method was applied to litho-units corresponding to point bar deposits (litho-units 1, 2 and 6), and to chute channels heterogeneously filled by sands and shales (litho-units 5, 8 and 9).…”
Section: Geostatistical Parametersmentioning
confidence: 99%
“…Truncation thresholds depend on the proportions of facies in each litho-unit. The Gaussian Random Function is stationary, but the proportions (hence, the thresholds) can vary in space (Beucher et al 1993;Galli et al 1994;Le Loc'h & Galli 1997). The VPC computed from well data (Fig.…”
Section: Litho-unit Simulationmentioning
confidence: 98%
“…This flag shows the allowed and forbidden contacts between domains (in the present example, all the domains are in contact), while the thresholds determine the proportion of space covered by each domain. When the domain proportions are not constant in space, one can consider the use of spatially varying thresholds [3]. The spatial behavior of the domains mainly depends on that of the underlying Gaussian random fields; for instance, the anisotropy of the second Gaussian random field (Y 2 ) in Figure 4 leads to an anisotropic behavior for domains 2 and 3, but not for domain 1 that is defined only on the basis of the first Gaussian random field (Y 1 ).…”
Section: Plurigaussian Simulationmentioning
confidence: 99%