Machine learning-based generalized multiscale finite element method and its application in reservoir simulation

：陈洁（西交利物浦大学）
：2022-04-20 10:00
：腾讯会议ID：680829103（无密码）

报告人：陈洁（西交利物浦大学）

时  间：4月20日上午10:00

地  点：腾讯会议ID：680829103（无密码）

内容摘要:

In multiscale modeling of subsurface fluid flow in heterogeneous porous media, standard polynomial basis functions are replaced by multiscale basis functions to acquire multiscale properties. To produce such functions, a number of Partial Differential Equations (PDEs) must be solved, so it makes sense to replace PDEs solvers with data-driven methods, given their great capabilities and general acceptance in recent decades. A mixed Generalized Multiscale Finite Element Method (mixed GMsFEM) has been recently proposed for subsurface flow problems, which approximates the pressure and velocity in the multiscale and fine grid space, respectively. The main purpose of this talk is to develop four distinct Convolutional Neural Network (CNN) models to predict four different multiscale basis functions for the mixed GMsFEM. These models have been applied to the 249,375 samples generated by the MatLab software, with the permeability field as the only input. The statistical results indicate that the four developed models yield satisfactory outputs with a coefficient of determination (R2) of 0.8328 - 0.9049 and Mean Squared Error (MSE) of 0.0109 - 0.0261. Graphically, all models follow the observed trend in each coarse block. Looking at this work as an image (matrix)-to-image (matrix) regression problem, the constructed deep learning-based models may have applications beyond reservoir engineering, such as hydrogeology and rock mechanics. 

个人简介：

陈洁副教授，博士生导师，分别于2004年和2007年在南京大学数学系获得学士和硕士学位，2011年在南洋理工大学获得博士学位；于2011/08-2012/10在香港科技大学做博士后研究，于2012/11-2013/03在沙特国王大学做博士后研究；2013/04进入西安交通大学数学与统计学院工作，2019/08进入西交利物浦大学工作。研究方向包括有限元方法，计算流体力学，油藏模拟。在Mathematics of Computation, Journal of computational physics, International Journal for Numerical Methods in Engineering等国际权威期刊上发表论文二十余篇，主持和参与面上项目、青年基金、博士后特等资助、CMG基金等十余项科研项目。担任包括Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering, Water Resources Research, International Journal for Numerical Methods in Engineering在内20多个国际期刊的审稿人。担任教育部学位论文评审专家。2019年，陈洁参加第8届华人数学家大会并做45分钟邀请报告。

 

联系人：陈黄鑫