Electrical resistivity measurements for nondestructive evaluation of chloride-induced deterioration of reinforced concrete—a review

KPV Robles, JJ Yee, SH Kee - Materials, 2022 - mdpi.com
The objective of this study is to review, evaluate, and compare the existing research and
practices on electrical resistivity as a nondestructive technique in evaluating chloride …

Wavefield reconstruction inversion via physics-informed neural networks

C Song, TA Alkhalifah - IEEE Transactions on Geoscience and …, 2021 - ieeexplore.ieee.org
Wavefield reconstruction inversion (WRI) formulates a PDE-constrained optimization
problem to reduce cycle skip** in full-waveform inversion (FWI). WRI is often implemented …

Unsupervised 3-D random noise attenuation using deep skip autoencoder

L Yang, S Wang, X Chen, OM Saad… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
Effective random noise attenuation is critical for subsequent processing of seismic data,
such as velocity analysis, migration, and inversion. Thus, the removal of seismic random …

GPRInvNet: Deep learning-based ground-penetrating radar data inversion for tunnel linings

B Liu, Y Ren, H Liu, H Xu, Z Wang… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
A DNN architecture referred to as GPRInvNet was proposed to tackle the challenges of
map** the ground-penetrating radar (GPR) B-Scan data to complex permittivity maps of …

Deep-learning seismic full-waveform inversion for realistic structural models

B Liu, S Yang, Y Ren, X Xu, P Jiang, Y Chen - Geophysics, 2021 - library.seg.org
Velocity model inversion is one of the most important tasks in seismic exploration. Full-
waveform inversion (FWI) can obtain the highest resolution in traditional velocity inversion …

Deep learning for 3-D magnetic inversion

Z Jia, Y Li, Y Wang, Y Li, S **, Y Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The difficulty of 3-D magnetic inversion is to use 2-D magnetic anomaly data to obtain 3-D
magnetic susceptibility structure. The contribution of the underground medium to the …

Denoising of distributed acoustic sensing data using supervised deep learning

L Yang, S Fomel, S Wang, X Chen, W Chen, OM Saad… - Geophysics, 2023 - library.seg.org
Distributed acoustic sensing (DAS) is an emerging technology for acquiring seismic data
due to its high-density and low-cost advantages. Because of the harsh acquisition …

Recovering 3D basement relief using gravity data through convolutional neural networks

S He, H Cai, S Liu, J **e, X Hu - Journal of Geophysical …, 2021 - Wiley Online Library
Gravity surveys in regional geophysical research can be used to estimate the depth of the
sediment‐basement interface. In this study, we investigate a novel method using the …

[HTML][HTML] TBM penetration rate prediction based on the long short-term memory neural network

B Gao, RR Wang, C Lin, X Guo, B Liu, W Zhang - Underground Space, 2021 - Elsevier
Tunnel boring machines (TBMs) are widely used in tunnel engineering because of their
safety and efficiency. The TBM penetration rate (PR) is crucial, as its real-time prediction can …

Deep learning for 3-D inversion of gravity data

L Zhang, G Zhang, Y Liu, Z Fan - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Three-dimensional (3-D) gravity inversion obtains the density distribution of subsurface
geological bodies through observed gravity anomalies. Recently, data-driven methods …