Pages that link to "Item:Q2184490"
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The following pages link to Surrogate permeability modelling of low-permeable rocks using convolutional neural networks (Q2184490):
Displaying 9 items.
- The use of ANN for the prediction of the modified relative permeability functions in stratified reservoirs (Q1682805) (← links)
- Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow (Q2021999) (← links)
- Automated porosity estimation using CT-scans of extracted core data (Q2147571) (← links)
- Rapid estimation of permeability from digital rock using 3D convolutional neural network (Q2192827) (← links)
- A deep learning perspective on predicting permeability in porous media from network modeling to direct simulation (Q2192831) (← links)
- A novel deep learning-based modelling strategy from image of particles to mechanical properties for granular materials with CNN and BiLSTM (Q2237268) (← links)
- Deep CNNs as universal predictors of elasticity tensors in homogenization (Q2679501) (← links)
- Prediction of permeability of porous media using optimized convolutional neural networks (Q2683510) (← links)
- Estimating permeability of 3D micro-CT images by physics-informed CNNs based on DNS (Q6106108) (← links)
