Model pipeline that aligns with the 3D ground truth in the voxel grid. The last layer of convolution neural network within 3D decoder is a sigmoid activation function S (x) = 1 1+e -x to bound the output between 0 and 1, 27 turning each voxel grid into a classifier. For a two-phase sample (e.g., ceramic proppants), the numerical prediction in each voxel within the 3D feature map represents the probability prob of finding the solid phase in that spatial location. If prob > 0.5, the grid has a higher chance to be occupied by a solid material (e.g., ceramic), otherwise it is unoccupied (e.g., air).