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pro vyhledávání: '"Ali, Alsadig"'
We are concerned with a novel Bayesian statistical framework for the characterization of natural subsurface formations, a very challenging task. Because of the large dimension of the stochastic space of the prior distribution in the framework, typica
Externí odkaz:
http://arxiv.org/abs/2302.11149
In this work we are interested in the (ill-posed) inverse problem for absolute permeability characterization that arises in predictive modeling of porous media flows. We consider a Bayesian statistical framework with a preconditioned Markov Chain Mon
Externí odkaz:
http://arxiv.org/abs/2107.08494
Publikováno v:
In Journal of Computational Physics 15 January 2024 497
Publikováno v:
In Applied Mathematics and Computation 15 December 2020 387
Publikováno v:
SSRN Electronic Journal.
We are concerned with a novel Bayesian statistical framework for the characterization of natural subsurface formations, a very challenging task. Because of the large dimension of the stochastic space of the prior distribution in the framework, typica
Publikováno v:
Computational Science – ICCS 2020
Accurate predictions in subsurface flows require the forecasting of quantities of interest by applying models of subsurface fluid flow with very little available data. In general a Bayesian statistical approach along with a Markov Chain Monte Carlo (