The dataset consists of two primary components: the data itself and the implementation code for constructing the multi-fidelity model. The data component comprises two types of sources: low-fidelity data derived from chart-based knowledge, and high-fidelity engineering data collected from actual shield tunneling projects. Both types of data include shield tunneling parameters along with the corresponding geological parameters.

Database and code to the paper: A multiscale CNN-based intrinsic permeability prediction in deformable porous media. Including: (1) a dataset of CT images from Bentheim sandstone at different volumetric strain levels; (2) pore-scale permeability simulation data of single-phase flow using the lattice Boltzmann method (LBM); (3) the CNN model with the processed CT images as inputs and permeability tensors as outputs; and (4) data augmentation and alternative CNN architectures.