Flow-based characterization of digital rock images using deep learning
X-ray imaging of porous media has revolutionized the interpretation of various microscale
phenomena in subsurface systems. The volumetric images acquired from this technology …
phenomena in subsurface systems. The volumetric images acquired from this technology …
Deep learning convolutional neural networks to predict porous media properties
N Alqahtani, RT Armstrong… - SPE Asia Pacific oil and …, 2018 - onepetro.org
Digital rocks obtained from high-resolution micro-computed tomography (micro-CT) imaging
has quickly emerged as a powerful tool for studying pore-scale transport phenomena in …
has quickly emerged as a powerful tool for studying pore-scale transport phenomena in …
Deep learning–driven permeability estimation from 2D images
Current micro-CT image resolution is limited to 1–2 microns. A recent study has identified
that at least 10 image voxels are needed to resolve pore throats, which limits the …
that at least 10 image voxels are needed to resolve pore throats, which limits the …
Upscaling permeability anisotropy in digital sandstones using convolutional neural networks
Pore-scale modelling and implementation of micro x-ray Computed Tomography (μxCT)
images have become a reliable method to predict the petrophysical properties of rocks …
images have become a reliable method to predict the petrophysical properties of rocks …
[HTML][HTML] Machine and deep learning for estimating the permeability of complex carbonate rock from X-ray micro-computed tomography
M Tembely, AM AlSumaiti, WS Alameri - Energy Reports, 2021 - Elsevier
Accurate estimation of permeability is critical for oil and gas reservoir development and
management, as it controls production rate. After assessing numerical techniques ranging …
management, as it controls production rate. After assessing numerical techniques ranging …
A deep learning perspective on predicting permeability in porous media from network modeling to direct simulation
Predicting the petrophysical properties of rock samples using micro-CT images has gained
significant attention recently. However, an accurate and an efficient numerical tool is still …
significant attention recently. However, an accurate and an efficient numerical tool is still …
Generation of ground truth images to validate micro-CT image-processing pipelines
Digital rock technology and pore-scale physics have become increasingly relevant topics in
a wide range of porous media with important applications in subsurface engineering. This …
a wide range of porous media with important applications in subsurface engineering. This …
PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media
Abstract We present the PoreFlow-Net, a 3D convolutional neural network architecture that
provides fast and accurate fluid flow predictions for 3D digital rock images. We trained our …
provides fast and accurate fluid flow predictions for 3D digital rock images. We trained our …
Deep learning in pore scale imaging and modeling
Pore-scale imaging and modeling has advanced greatly through the integration of Deep
Learning into the workflow, from image processing to simulating physical processes. In …
Learning into the workflow, from image processing to simulating physical processes. In …
[HTML][HTML] Predicting permeability from 3D rock images based on CNN with physical information
Permeability is one of the most important properties in subsurface flow problems, which
measures the ability of rocks to transmit fluid. Normally, permeability is determined through …
measures the ability of rocks to transmit fluid. Normally, permeability is determined through …