China University of Petroleum

Dongyan Fan

Kai Zhang

Jun Yao

Yongfei Yang

Lei Zhang

Hai Sun

Xia Yan

Lei Liu

Qian Sang

Fei Luo

Yuda Kan

Liang Zhou

Disclosed a method for predicting permeability of a multi-mineral phase digital core based on deep learning. In the present disclosure, a three-dimensional digital core is constructed and a pore structure is randomly generated; after a plurality of multi-mineral digital core images is acquired by performing image segmentation on the three-dimensional digital core, permeability corresponding to each of the multi-mineral digital core images is acquired by simulation using multi-physics field simulation software and a multi-mineral digital core data set is constructed based on the plurality of multi-mineral digital core images and the permeability corresponding to each of the multi-mineral digital core images; an SE-ResNet18 convolutional neural network is constructed and trained with the multi-mineral digital core data set; and an image of a multi-mineral core to be predicted is input into the trained SE-ResNet18 convolutional neural network to determine the permeability of the multi-mineral core.

Method for predicting permeability of multi-mineral phase digital core based on deep learning

Growing community of inventors

Qingdao, China

Dongyan Fan