activity
20242026
collaborators

6 papers

cs.CV2026

Reservoir property image slices from the Groningen gas field for image translation and segmentation

Abdulrahman Al-Fakih, Nabil Sariah, Ardiansyah Koeshidayatullah +1

Reservoir characterization workflows increasingly rely on image-based and machine-learning/deep learning or even generative AI approaches, but openly available geological image dat…

physics.geo-ph2026

Robustness and Transferability of Pix2Geomodel for Bidirectional Facies Property Translation in a Complex Reservoir

Abdulrahman Al-Fakih, Nabil Sariah, Ardiansyah Koeshidayatullah +2

Reservoir geomodeling is central to subsurface characterization, but it remains challenging because conditioning data are sparse, geological heterogeneity is strong, and convention…

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-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…