Journal Article10.1016/J.ADVWATRES.2004.10.013
Multiscale data integration using coarse-scale models☆
TL;DR: The approach introduced in the paper is hierarchical and the conditional information from different length scales is incorporated into the posterior distribution using a Bayesian framework.
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About: This article is published in Advances in Water Resources. The article was published on 01 Mar 2005. The article focuses on the topics: Markov chain Monte Carlo & Markov chain.
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Citations
A Bayesian framework for the validation of models for subsurface flows: synthetic experiments
TL;DR: In this article, a new Bayesian framework for the validation of models for subsurface flows is presented, which combines high performance computing, Bayesian inference, and a Markov chain Monte Carlo (McMC) method for characterizing the posterior distribution of the permeability field conditioned on the available dynamic measurements (saturation values at slices).
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Theoretical development of the history matching method for subsurface characterizations based on simulated annealing algorithm
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Infill well placement optimization in two-dimensional heterogeneous reservoirs under waterflooding using upscaling wavelet transform
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Reservoir Multiscale Data Assimilation Using the Ensemble Kalman Filter
TL;DR: In this paper, a coarse-scale EnKF was proposed to integrate data at different spatial scales using the ensemble Kalman filter (EnKF), such that the finest scale data is sequentially estimated, subject to the available data at the coarse scale (s), as an additional constraint.
References
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TL;DR: In this article, the problem of homogenizing a two-dimensional matrix has been studied in the context of Diffusion problems, where the homogenization problem is formulated as a set of problems of diffusion.
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Numerical calculation of equivalent grid block permeability tensors for heterogeneous porous media
TL;DR: In this paper, a numerical procedure for the determination of equivalent grid block permeability tensors for heterogeneous porous media is presented, which entails solution of the fine scale pressure equation subject to periodic boundary conditions.
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Random Field Models in Earth Sciences
George Christakos
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TL;DR: Prolegomena the spatial random field model the intrinsic spatial randomField model the factorable random fieldModel the spatiotemporal random fieldmodel space transformations of random fields random field modelling of natural processes simulation of natural process estimation in space and time sampling design.
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A coupled local-global upscaling approach for simulating flow in highly heterogeneous formations
TL;DR: In this paper, a new technique for generating coarse scale models of highly heterogeneous subsurface formations is developed and applied, which uses generic global coarse scale simulations to determine the boundary conditions for the local calculation of upscaled properties (permeability or transmissibility).
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