Name
Title | ||
|---|---|---|
Preconditioning Markov Chain Monte Carlo Method for Geomechanical Subsidence using multiscale method and machine learning technique |
Abstract | ||
|---|---|---|
In this paper, we consider the numerical solution of the poroelasticity problem with stochastic properties. We present a Two-stage Markov Chain Monte Carlo method for geomechanical subsidence. In this work, we study two techniques of preconditioning: (MS) multiscale method for model order reduction and (ML) machine learning technique. The purpose of preconditioning is the fast sampling, where a new proposal is first tested by a cheap multiscale solver or using fast prediction of the neural network and the full fine grid computations will be conducted only if the proposal passes the first step. To construct a reduced order model, we use the Generalized Multiscale Finite Element Method and present construction of the multiscale basis functions for pressure and displacements in stochastic fields. In order to construct a machine learning based preconditioning, we generate a dataset using a multiscale solver and use it to train neural networks. The Karhunen–Loéve expansion is used to represent the realization of the stochastic field. Numerical results are presented for two- and three-dimensional model examples. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.cam.2021.113420 | Journal of Computational and Applied Mathematics |
Keywords | DocType | Volume |
Poroelastic model,Heterogeneous media,Two Stage Markov Chain Monte Carlo method,Multiscale method,Machine learning,GMsFEM | Journal | 392 |
ISSN | Citations | PageRank |
0377-0427 | 0 | 0.34 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Vasilyeva | 1 | 0 | 0.34 |
| Aleksei Tyrylgin | 2 | 0 | 0.34 |
| Donald L. Brown | 3 | 22 | 3.63 |
| Anirban Mondal | 4 | 0 | 0.34 |