A new method of reconstructing 3D tight sandstone digital rock with deep learning is proposed, and 3D convolution is used in the generator and the discriminator of deep convolutional generative adversative network (DCGAN), which can reconstruct 3D digital rock from one dimensional noise data
Gravity prospecting is an important geophysical method for mineral resource exploration and investig...
The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning ...
Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelmi...
Digital rock technology is becoming essential in reservoir engineering and petrophysics. Three-dimen...
This is the dataset for our paper "Multiscale fusion of digital rock images based on deep generative...
Generative Adversarial Networks (GANs), as most popular artificial intelligence models in the curre...
We image two altered rock samples consisting of a meta-igneous and a serpentinite showing an isolate...
To train our deep convolutional neural network for Relative Geologic Time (RGT) estimation and fault...
Digital Rock Analysis involves (1) 3D X-ray CT imaging and processing, (2) identifying and segmentin...
Digital Rock Physics (DRP) provides a fast way to compute rock properties and carry out a related se...
As deep learning (DL) gains popularity for its ability to make accurate predictions in various field...
This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm...
Hammering rocks of different strengths can make different sounds. Geological engineers often use thi...
Accurate identification of the distribution of coal seam is a prerequisite for realizing intelligent...
To make efficient use of image-based rock physics workflow, it is necessary to optimize different cr...
Gravity prospecting is an important geophysical method for mineral resource exploration and investig...
The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning ...
Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelmi...
Digital rock technology is becoming essential in reservoir engineering and petrophysics. Three-dimen...
This is the dataset for our paper "Multiscale fusion of digital rock images based on deep generative...
Generative Adversarial Networks (GANs), as most popular artificial intelligence models in the curre...
We image two altered rock samples consisting of a meta-igneous and a serpentinite showing an isolate...
To train our deep convolutional neural network for Relative Geologic Time (RGT) estimation and fault...
Digital Rock Analysis involves (1) 3D X-ray CT imaging and processing, (2) identifying and segmentin...
Digital Rock Physics (DRP) provides a fast way to compute rock properties and carry out a related se...
As deep learning (DL) gains popularity for its ability to make accurate predictions in various field...
This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm...
Hammering rocks of different strengths can make different sounds. Geological engineers often use thi...
Accurate identification of the distribution of coal seam is a prerequisite for realizing intelligent...
To make efficient use of image-based rock physics workflow, it is necessary to optimize different cr...
Gravity prospecting is an important geophysical method for mineral resource exploration and investig...
The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning ...
Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelmi...
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