Multimodal imaging and machine learning to enhance microscope images of shale

TI Anderson, B Vega, AR Kovscek - Computers & Geosciences, 2020 - Elsevier
A machine learning based image processing workflow is presented to enhance shale
source rock microscopic images obtained using diverse imaging platforms. Images were …

Deep learning in pore scale imaging and modeling

Y Da Wang, MJ Blunt, RT Armstrong… - Earth-Science Reviews, 2021 - Elsevier
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 …

Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

S Kamrava, P Tahmasebi, M Sahimi - Neural Networks, 2019 - Elsevier
Accounting for the morphology of shale formations, which represent highly heterogeneous
porous media, is a difficult problem. Although two-or three-dimensional images of such …

RockFlow: Fast generation of synthetic source rock images using generative flow models

TI Anderson, KM Guan, B Vega, SA Aryana… - Energies, 2020 - mdpi.com
Image-based evaluation methods are a valuable tool for source rock characterization. The
time and resources needed to obtain images has spurred development of machine-learning …

Multi-scale reconstruction of porous media from low-resolution core images using conditional generative adversarial networks

Y Yang, F Liu, J Yao, S Iglauer, M Sajjadi… - Journal of natural gas …, 2022 - Elsevier
Various rocks such as carbonate, coal or shale contain both micro-and macro-pores. To
accurately predict the fluid flow and mechanical properties of these porous media, a multi …

An innovative application of generative adversarial networks for physically accurate rock images with an unprecedented field of view

Y Niu, YD Wang, P Mostaghimi… - Geophysical …, 2020 - Wiley Online Library
High‐resolution X‐ray microcomputed tomography (micro‐CT) data are used for the
accurate determination of rock petrophysical properties. High‐resolution data, however …

Digital rock resolution enhancement and detail recovery with multi attention neural network

Z Xing, J Yao, L Liu, H Sun - Geoenergy Science and Engineering, 2023 - Elsevier
High-quality digital rock images are essential for subsequent high-precision numerical
simulations. But limited by the imaging capability of computed tomography (CT), high …

Enhancing the resolution of micro-CT images of rock samples via unsupervised machine learning based on a diffusion model

Z Ma, S Sun, B Yan, H Kwak, J Gao - SPE Annual Technical …, 2023 - onepetro.org
Objectives/Scope X-ray Micro-Computer Tomography (μ-CT) has been widely adopted in
earth science and petroleum engineering due to its non-destructive characteristic …

Siamese-SR: A siamese super-resolution model for boosting resolution of digital rock images for improved petrophysical property estimation

VR Ahuja, U Gupta, SR Rapole… - … on Image Processing, 2022 - ieeexplore.ieee.org
Digital Rock Physics leverages advances in digital image acquisition and analysis
techniques to create 3D digital images of rock samples, which are used for computational …

Nano-imaging of shale using electron microscopy techniques

L Froute, AR Kovscek - SPE/AAPG/SEG Unconventional Resources …, 2020 - onepetro.org
Modeling of fluid migration in shale nanoscale systems is hampered by knowledge gaps in
rock-fluid affinity, storage and transport processes under confinement, phase behavior …