Bayesian inversion for steady flow in fractured porous media with contact on fractures and hydro mechanical coupling

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/61989100:27240/20:10244847

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Bayesian inversion for steady flow in fractured porous media with contact on fractures and hydro mechanical coupling

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Bayesian inversion for steady flow in fractured porous media with contact on fractures and hydro mechanical coupling

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational Geosciences

ISSN

1420-0597

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

February 2020

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

22

Strana od-do

1911-1932

Kód UT WoS článku

000517019300001

EID výsledku v databázi Scopus

2-s2.0-85081326146