(The H4-Index of Geophysics is 37. 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 2020-01-01 to 2024-01-01.)
Deep denoising autoencoder for seismic random noise attenuation173
Building realistic structure models to train convolutional neural networks for seismic structural interpretation120
A theory-guided deep-learning formulation and optimization of seismic waveform inversion106
Extrapolated full-waveform inversion with deep learning88
Automatic velocity analysis using convolutional neural network and transfer learning76
Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks75
Deep learning reservoir porosity prediction based on multilayer long short-term memory network69
Seismic trace interpolation for irregularly spatial sampled data using convolutional autoencoder68
Can learning from natural image denoising be used for seismic data interpolation?67
Physics-guided deep learning for seismic inversion with hybrid training and uncertainty analysis65
Seismic velocity estimation: A deep recurrent neural-network approach61
A gradient boosting decision tree algorithm combining synthetic minority oversampling technique for lithology identification60
Detection of road cavities in urban cities by 3D ground-penetrating radar56
Extracting horizon surfaces from 3D seismic data using deep learning55
Petrophysical properties prediction from prestack seismic data using convolutional neural networks54
A convolutional neural network approach to deblending seismic data54
Seismic stratigraphy interpretation by deep convolutional neural networks: A semisupervised workflow53
Deep-learning seismic full-waveform inversion for realistic structural models52
Mapping full seismic waveforms to vertical velocity profiles by deep learning51
An unsupervised deep-learning method for porosity estimation based on poststack seismic data50
A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data50
Iterative deblending for simultaneous source data using the deep neural network50
Seismic data interpolation based on U-net with texture loss48
Application of machine learning to microseismic event detection in distributed acoustic sensing data47
Missing well log prediction using convolutional long short-term memory network47
Ground-roll attenuation using generative adversarial networks45
Improving the resolution of migrated images by approximating the inverse Hessian using deep learning45
Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks43
Deep learning for relative geologic time and seismic horizons42
Data-driven low-frequency signal recovery using deep-learning predictions in full-waveform inversion41
High-resolution reservoir characterization using deep learning-aided elastic full-waveform inversion: The North Sea field data example41
Uncertainty quantification in fault detection using convolutional neural networks40
Waveform embedding: Automatic horizon picking with unsupervised deep learning40
Velocity model building in a crosswell acquisition geometry with image-trained artificial neural networks39
Modeling the seismic response of individual hydraulic fracturing stages observed in a time-lapse distributed acoustic sensing vertical seismic profiling survey39
Seismic attribute selection for machine-learning-based facies analysis38
Deep learning for multidimensional seismic impedance inversion38