2002
DOI: 10.1002/fld.267
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Upscaling: a review

Abstract: SUMMARYPorous media have properties with heterogeneities on several length scales. It is possible to build digital models of such properties. However these can be so detailed that a computing machine of the same power as that used to build the property model is not able to solve the uid ow equations using standard discretisation methods-storage is needed for workspace, and the discrete equations have to be solved in a reasonable time. This paper reviews averaging techniques, devised to simulate large scale fea… Show more

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Cited by 321 publications
(180 citation statements)
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“…Upscaling, i.e. methods to make measurements, process descriptions, or model parameters identified at the local scale available for use at larger scales, has received wide attention in the hydrological literature (Becker and Braun 1999;Farmer 2002;Neuman and Di Federico 2003;Renard and de Marsily 1997;Sánchez-Vila et al 1995). The same is true for regionalisation, i.e.…”
Section: Gw-sw Related Processes At Different Scalesmentioning
confidence: 99%
“…Upscaling, i.e. methods to make measurements, process descriptions, or model parameters identified at the local scale available for use at larger scales, has received wide attention in the hydrological literature (Becker and Braun 1999;Farmer 2002;Neuman and Di Federico 2003;Renard and de Marsily 1997;Sánchez-Vila et al 1995). The same is true for regionalisation, i.e.…”
Section: Gw-sw Related Processes At Different Scalesmentioning
confidence: 99%
“…The rapid variations in fine-scale permeability have big influence on the flow and need to be accounted for in the numerical methods. Various upscaling procedures have been developed to increase the efficiency of the flow calculations (see [12]). These techniques serve to construct coarse-scale flow parameters for the global problem on a coarser scale.…”
mentioning
confidence: 99%
“…Bayes' theorem then reveals that the posterior probability density of the states given the observations is proportional to the product of the likelihood and the prior density. 3 Thus, the consequence of Bayes' theorem is that we can find, in principle, We emphasize that the application of Bayes' theorem is not a way of extracting theories or models from data: it is just a procedure for updating probability densities. As we have indicated in the previous section, we need to perform forecast evaluation to quantify the fidelity of models and probability densities.…”
Section: (C) Bayes' Theoremmentioning
confidence: 99%