Bayesian inversion for steady flow in fractured porous media with contact on fractures and hydro mechanical coupling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68145535%3A_____%2F20%3A00533163" target="_blank" >RIV/68145535:_____/20:00533163 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/20:10244847
Result on the web
<a href="https://link.springer.com/article/10.1007/s10596-020-09935-8" target="_blank" >https://link.springer.com/article/10.1007/s10596-020-09935-8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10596-020-09935-8" target="_blank" >10.1007/s10596-020-09935-8</a>
Alternative languages
Result language
angličtina
Original language name
Bayesian inversion for steady flow in fractured porous media with contact on fractures and hydro mechanical coupling
Original language description
The paper is motivated by a strong interest in numerical analysis of flow in fractured porous media, e.g., rocks in geo-engineering applications. It follows the conception of porous media as a continuum with fractures which are represented as lower dimensional objects. In the paper, the finite element discretization of the flow in coupled continuum and fractures is used. Fluid pressures serve as the basic unknowns. In many applications, the flow is connected with deformations of the porous matrix, therefore, the hydro-mechanical coupling is also considered. The fluid pressure is transferred to the mechanical load in both pores and fractures and the considered mechanical model involves elastic deformations of the porous matrix and opening/closing of the fractures with the non-penetration constraint. The mechanical model with this constraint is implemented via the technique of the Lagrange multipliers, duality formulation, and combination with a suitable domain decomposition method. There is usually lack of information about problem parameters and they undergo many uncertainties coming e.g. from the heterogeneity of rock formations and complicated realization of experiments for parameter identification. These experiments rarely provide some of the asked parameters directly but require solving inverse problems. The stochastic (Bayesian) inversion is natural due to the mentioned uncertainties. In this paper, the implementation of the Bayesian inversion is realized via Metropolis-Hastings Markov chain Monte Carlo approach. For the reduction of computational demands, the sampling procedure uses the delayed acceptance of samples based on a surrogate model which is constructed during a preliminary sampling process. The developed hydro-mechanical model and the implemented Bayesian inversion are tested on two types of model inverse problems.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational Geosciences
ISSN
1420-0597
e-ISSN
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Volume of the periodical
24
Issue of the periodical within the volume
February 2020
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
22
Pages from-to
1911-1932
UT code for WoS article
000517019300001
EID of the result in the Scopus database
2-s2.0-85081326146