Method for predicting permeability of multi-mineral phase digital core based on deep learning
US11954417B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2023 |
| Grant date | Apr 9, 2024 |
| Priority date | — |
| Expiry date | Nov 8, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2113/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.