collaborators

5 papers

physics.geo-ph2025

Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation

Abdulrahman Al-Fakih, Ardiansyah Koeshidayatullah, Nabil A. Saraih +4

Accurate geological modeling is critical for reservoir characterization, yet traditional methods struggle with complex subsurface heterogeneity, and they have problems with conditi…

physics.geo-ph2025

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…

physics.geo-ph2024

Leveraging Time-Series Foundation Model for Subsurface Well Logs Prediction and Anomaly Detection

Ardiansyah Koeshidayatullah, Abdulrahman Al-Fakih, SanLinn Ismael Kaka

The rise in energy demand highlights the importance of suitable subsurface storage, requiring detailed and accurate subsurface characterization often reliant on high-quality boreho…

physics.geo-ph2024

Well log data generation and imputation using sequence-based generative adversarial networks

Abdulrahman Al-Fakih, A. Koeshidayatullah, Tapan Mukerji +2

Well log analysis is crucial for hydrocarbon exploration, providing detailed insights into subsurface geological formations. However, gaps and inaccuracies in well log data, often…

physics.geo-ph2024

Enhanced anomaly detection in well log data through the application of ensemble GANs

Abdulrahman Al-Fakih, A. Koeshidayatullah, Tapan Mukerji +1

Although generative adversarial networks (GANs) have shown significant success in modeling data distributions for image datasets, their application to structured or tabular data, s…