Data-driven microseismic event localization: An application to the Oklahoma Arkoma basin hydraulic fracturing data

H Wang, T Alkhalifah, U bin Waheed… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The microseismic monitoring technique is widely applied to petroleum reservoirs to
understand the process of hydraulic fracturing. Geophones continuously record the …

Multi-parameter pre-stack seismic inversion based on deep learning with sparse reflection coefficient constraints

D Cao, Y Su, R Cui - Journal of Petroleum Science and Engineering, 2022 - Elsevier
In the field of seismic inversion, Convolutional Neural Network (CNN) has been extensively
applied for their powerful capability of feature extraction and nonlinear fitting. However, the …

Groundwater potential delineation using geodetector based convolutional neural network in the Gunabay watershed of Ethiopia

AM Tegegne, TK Lohani, AA Eshete - Environmental Research, 2024 - Elsevier
Groundwater potential delineation is essential for efficient water resource utilization and
long-term development. The scarcity of potable and irrigation water has become a critical …

Deep-learning-based method for estimating permittivity of ground-penetrating radar targets

H Wang, S Ouyang, Q Liu, K Liao, L Zhou - Remote Sensing, 2022 - mdpi.com
Correctly estimating the relative permittivity of buried targets is crucial for accurately
determining the target type, geometric size, and reconstruction of shallow surface geological …

A self‐supervised learning framework for seismic low‐frequency extrapolation

S Cheng, Y Wang, Q Zhang, R Harsuko… - Journal of …, 2024 - Wiley Online Library
Full waveform inversion (FWI) is capable of generating high‐resolution subsurface
parameter models, but it is susceptible to cycle‐skipping when the data lack low‐frequency …

Magnetotelluric noise suppression via convolutional neural network

J Li, Y Liu, J Tang, F Ma - Geophysics, 2023 - library.seg.org
It is well known that a magnetotelluric (MT) signal with high signal-to-noise ratio is an
important prerequisite for correct interpretation of subsurface structures. However, MT …

Joint Inversion of Seismic and Resistivity Data Powered by Deep-learning

Y Ren, B Liu, B Liu, Z Liu, P Jiang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Incorporating multiple perspectives makes joint inversion of multiple geophysical data is an
effective way for improving the accuracy of imaging complex geological structures. In this …

Self-supervised learning waveform inversion for seismic forward prospecting in tunnels: A case study in Pearl River Delta Water Resources Allocation Project in China

Y Ren, J Wang, Q Wang, S Yang - Geophysics, 2024 - library.seg.org
Tunnel and underground engineering construction often encounter unfavorable geology,
leading to disasters such as water and mud inrushes and landslides. To prevent geologic …

[HTML][HTML] Seismic ahead-prospecting based on deep learning of retrieving seismic wavefield

L Chen, S Yang, L Guo, P Zhang, K Li, W Shao, X Xu… - Underground …, 2023 - Elsevier
Unknown geology ahead of the tunnel boring machine (TBM) brings a large safety risk for
tunnel construction. Seismic ahead-prospecting using TBM drilling noise as a source can …

DAS weak signals recovery under condition of multiple complicated noise using CA-MSRNet

Y Li, Z Zhao, Y Tian, N Wu - Journal of Applied Geophysics, 2022 - Elsevier
Over the years, distributed fiber-optical acoustic sensing (DAS) has been widely used in
seismic exploration benefited from its numerous advantages over traditional geophones …