2015
DOI: 10.1007/s11004-015-9614-x
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Change-of-Support Models on Irregular Grids for Geostatistical Simulation

Abstract: International audienceIn many domains, numerical models are initialized with inputs defined on irregular grids. In petroleum reservoir engineering, they consist of a great variety of grid cells of different size and shape to enable fine-scale modeling in the vicinity of the wells and coarse modeling in less important regions. Geostatistical simulation algorithms, which are used to populate the cells of unstructured grids, often have to address the problem of transition from the small-scale statistical data ste… Show more

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Cited by 11 publications
(8 citation statements)
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“…The use of point-based parameterizations is also much studied in computational physics under the term "meshless methods", see for instance Liu and Gu (2005). In the practice of geostatistical methods, the values m k are generally modeled on a Cartesian grid, but recent papers also discuss about the application of geostatistics on unstructured grids (Gross and Boucher 2015;Manchuk et al 2005;Zaytsev et al 2016), or directly on points (Zagayevskiy and Deutsch 2016). A major interest of these methods is to estimate or simulate values directly on the physical modeling support, and also to use adaptive resolution depending on the local information density and on the sensitivity between the model parameters and the physical process.…”
Section: Parameterizations For Physical Modelsmentioning
confidence: 99%
“…The use of point-based parameterizations is also much studied in computational physics under the term "meshless methods", see for instance Liu and Gu (2005). In the practice of geostatistical methods, the values m k are generally modeled on a Cartesian grid, but recent papers also discuss about the application of geostatistics on unstructured grids (Gross and Boucher 2015;Manchuk et al 2005;Zaytsev et al 2016), or directly on points (Zagayevskiy and Deutsch 2016). A major interest of these methods is to estimate or simulate values directly on the physical modeling support, and also to use adaptive resolution depending on the local information density and on the sensitivity between the model parameters and the physical process.…”
Section: Parameterizations For Physical Modelsmentioning
confidence: 99%
“…The Discrete Gaussian Model extended to unstructured grids (Zaytsev et al, 2015) respects both point-support statistics and the Central Limit Theorem. It avoids the use of a potentially costly fine grid, but the calculation of block covariances through a sextuple integral is computationally difficult.…”
Section: Limits Of the Existing Methodsmentioning
confidence: 99%
“…The simplest approach to account for the support effect, referred to as "fine-scale simulation approach" by Zaytsev et al (2015), is to use a fine scale Cartesian grid overlaid by a coarse, irregular or unstructured grid (Fig. 2.5a).…”
Section: Use Of a Fine Gridmentioning
confidence: 99%
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