74 citations · 146 across the 13 of their papers we have counts for
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SeisCoDE: 3D Seismic Interpretation Foundation Model with Contrastive Self-Distillation Learning
Goodluck Archibong, Ardiansyah Koeshidayatullah, Umair Waheed +3
Seismic interpretation is vital for understanding subsurface structures but remains labor-intensive, subjective, and computationally demanding. While deep learning (DL) offers prom…
Joint Learning for Spatial Context-based Seismic Inversion of Multiple Datasets for Improved Generalizability and Robustness
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion plays a very useful role in detailed stratigraphic interpretation of seismic data. Seismic inversion enables estimation of rock properties over the complete seism…
Semi-supervised Sequence Modeling for Elastic Impedance Inversion
Motaz Alfarraj, Ghassan AlRegib
Recent applications of machine learning algorithms in the seismic domain have shown great potential in different areas such as seismic inversion and interpretation. However, such a…
3D Curvature Analysis of Seismic Waveforms and its Interpretational Implications
Haibin Di, Motaz Alfarraj, Ghassan AlRegib
The idea of curvature analysis has been widely used in subsurface structure interpretation from three-dimensional (3D) seismic data (e.g., fault/fracture detection and geomorpholog…
Petrophysical Property Estimation from Seismic Data Using Recurrent Neural Networks
Motaz Alfarraj, Ghassan AlRegib
Reservoir characterization involves the estimation petrophysical properties from well-log data and seismic data. Estimating such properties is a challenging task due to the non-lin…