Geophysics

Papers
(The H4-Index of Geophysics is 35. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
Deep denoising autoencoder for seismic random noise attenuation177
Extrapolated full-waveform inversion with deep learning91
Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks87
Deep learning reservoir porosity prediction based on multilayer long short-term memory network75
Can learning from natural image denoising be used for seismic data interpolation?72
Physics-guided deep learning for seismic inversion with hybrid training and uncertainty analysis66
A gradient boosting decision tree algorithm combining synthetic minority oversampling technique for lithology identification65
Extracting horizon surfaces from 3D seismic data using deep learning61
Detection of road cavities in urban cities by 3D ground-penetrating radar61
Petrophysical properties prediction from prestack seismic data using convolutional neural networks59
Mapping full seismic waveforms to vertical velocity profiles by deep learning57
Deep-learning seismic full-waveform inversion for realistic structural models56
An unsupervised deep-learning method for porosity estimation based on poststack seismic data56
Seismic stratigraphy interpretation by deep convolutional neural networks: A semisupervised workflow55
Seismic data interpolation based on U-net with texture loss55
Application of machine learning to microseismic event detection in distributed acoustic sensing data52
Missing well log prediction using convolutional long short-term memory network51
Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks50
Improving the resolution of migrated images by approximating the inverse Hessian using deep learning50
Ground-roll attenuation using generative adversarial networks49
Deep learning for relative geologic time and seismic horizons47
Physics-driven deep-learning inversion with application to transient electromagnetics45
Waveform embedding: Automatic horizon picking with unsupervised deep learning45
Data-driven low-frequency signal recovery using deep-learning predictions in full-waveform inversion45
Deep learning for multidimensional seismic impedance inversion45
Uncertainty quantification in fault detection using convolutional neural networks43
Modeling the seismic response of individual hydraulic fracturing stages observed in a time-lapse distributed acoustic sensing vertical seismic profiling survey43
High-resolution reservoir characterization using deep learning-aided elastic full-waveform inversion: The North Sea field data example42
Convolutional neural networks for microseismic waveform classification and arrival picking40
Fast imaging of time-domain airborne EM data using deep learning technology40
Reparameterized full-waveform inversion using deep neural networks37
Automatic seismic facies interpretation using supervised deep learning36
Modeling of fiber-optic strain responses to hydraulic fracturing36
Double-scale supervised inversion with a data-driven forward model for low-frequency impedance recovery36
Evidence-based guidelines for protective actions and earthquake early warning systems36
Integrating deep neural networks with full-waveform inversion: Reparameterization, regularization, and uncertainty quantification35
Automatic waveform-based source-location imaging using deep learning extracted microseismic signals35
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