CPG

Location: Bldg76, Rm. 2138

Dr. Abdulrahman Al-Fakih

Researcher, CIPR

Dr. Abdulrahman joined CIPR at KFUPM as a Researcher in 2026. His research in Generative AI, Computer Vision, and Computational Geoscience, specializing in AI-driven subsurface reservoir characterization, formation evaluation, and geothermal energy, with over 8 years of experience. Expert in GANs, Diffusion Models, and Transformers, with advanced proficiency in TensorFlow and PyTorch. Brings 2 years of field engineering experience and 7 years as a teaching assistant.

Educational Qualification

  • Ph.D., Geophysics, KFUPM, Saudi Arabia, 2025
  • M.S., Oil and Gas Fields Development Engineering, China University of Geosciences (Beijing), China, 2020
  • B.S.,Petroleum Engineering, Hadhramout University, Yemen, 2012

Research Interests

  • Generative AI for reservoir characterization.
  • AI-driven reservoir geomodeling.
  • Well-log synthesis and anomaly detection.
  • Machine learning for formation evaluation.
  • AI applications in geothermal energy.

Selected Publications

Articles

  1. Al-Fakih, A., Koeshidayatullah, A., Saraih, N. A., Mukerji, T., Kanfar, R., Alali, A., & Kaka, S. I. (2026). Pix2Geomodel: A next-generation reservoir geomodeling with property-to-property translation. Geoenergy Science and Engineering, 258, 214342. https://doi.org/10.1016/j.geoen.2025.214342.
  2. Al-Fakih, A., Koeshidayatullah, A., Mukerji, T., & Kaka, S. I. (2026). Enhanced anomaly detection in well log data through the application of ensemble GANs. Applied Computing and Geosciences, 29, 100316. https://doi.org/10.1016/j.acags.2025.100316.
  3. Koeshidayatullah, A., Al-Fakih, A., & Kaka, S. I. (2026). Toward basin-agnostic well log imputation and anomaly detection via a pre-trained time-series foundation model. Energy Geoscience, 7(2), 100536. https://doi.org/10.1016/j.engeos.2026.100536.
  4. Al-Fakih, A., Koeshidayatullah, A., Mukerji, Kaka. Well log data generation and imputation using sequence-based generative adversarial networks. Sci Rep 15, 11000 (2025). https://doi.org/10.1038/s41598-025-95709-0
  1. Al-Fakih, A., Al-khudafi, A., Koeshidayatullah, Kaka. Forecasting geothermal temperature in western Yemen with Bayesian-optimized machine learning regression models. Geotherm Energy 13, 4 (2025). https://doi.org/10.1186/s40517-024-00324-3
  2. Al-Fakih, A., Koeshidayatullah, A., & Kaka, Abdulraheem. (2024). Application of machine learning and deep learning in geothermal resource development: Trends and perspectives. Deep Underground Science and Engineering. https://doi.org/10.1002/dug2.12098.
  3. Al-Fakih, A., & Koeshidayatullah, Kaka. (2023). Reservoir Property Prediction in the North Sea Using Machine Learning. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3336623.
  4. Al-Fakih, A., Kaka, S. Application of Artificial Intelligence in Static Formation Temperature Estimation. Arab J Sci Eng 48, 16791–16804 (2023). https://doi.org/10.1007/s13369-023-08096-x.
  5. Al-Fakih, A., Ibrahim, A.F., Elkatatny, Abdulraheem, et al. (2023). Estimating electrical resistivity from logging data for oil wells using machine learning. J Petrol Explor Prod Technol. https://doi.org/10.1007/s13202-023-01617-2.

Conference Papers

  1. Al-Fakih, A. Koeshidayatullah, N. Saraih and S. Kaka1, Bridging Reservoir‑ and Pore‑Scale Modeling with Pix2Pix cGANs, Second EAGE Workshop on Advances in Carbonate Reservoirs: from Prospects to Development, Kuwait, Apr 2026, Volume 2026, p.1 – 3. https://doi.org/10.3997/2214-4609.2026649005.
  2. Al-Fakih, A., Hanafy, S., Saraih, N., Koeshidayatullah, A., and Kaka, S.: Data-efficient enhanced Pix2Geomodel.v2 for complex facies settings, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2220, 2026.
  3. Saraih, Al-Fakih, A. Koeshidayatullah, N. Saraih and S. Kaka1 Improving Facies and Property Prediction in Complex Reservoirs Using Enhanced Pix2Pix-Based Modeling, Second EAGE Workshop on Advances in Carbonate Reservoirs: from Prospects to Development, Kuwait, Apr 2026, Volume 2026, p.1 – 3. https://doi.org/10.3997/2214-4609.2026649024.
  4. Kaka, S., Al-Fakih, A., Saraih, N., Koeshidayatullah, A., and Hanafy, S.: Bidirectional translation + spatial continuity validation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2222, 2026.
  5. Al-Fakih, Koeshidayatullah, Saraih, Mukerji, Kanfar, Alali, Kaka.Pix2geomodel: Domain-To-Domain Translation for Next-Generation Reservoir Geomodeling.AAPG Decision-Based Integrated Reservoir Modeling GTW.Al Khobar, Saudi Arabia, Nov. 2025.Accepted as an Oral Presentation.
  6. Al-Fakih, Koeshidayatullah, Mukerji, Kaka.Application of Pix2pix Gan for Geological Property Modeling: A Case Study on Porosity, Permeability, And Water Saturation in The Groningen Field, North Sea. The Middle East Oil, Gas, and Geosciences/ (MEOS GEO 2025). 25MEOS-P-87-SPE. Manama, Bahrain, Sept. 2025.Accepted as an Oral Presentation.
  7. Al-Fakih, Koeshidayatullah, Mukerji, Kaka. Advanced Well Log Forecasting and Anomaly Detection Using TimeGPT: A Time-series Foundation Model Approach. The Middle East Oil, Gas, and Geosciences/ (MEOS GEO 2025). 25MEOS-P-104-SPE. Manama, Bahrain, Sept. 2025.Accepted as an Oral Presentation.
  8. Al-Fakih, A., Koeshidayatullah, Kaka, S. (2025, January). End-to-End GANs and TimeGPT for Multidimensional Reservoir Characterization. Innovative Technology for Reservoir Optimization, Apr 2025, Volume 2025, p.1 – 5. European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.2025638001.
  9.  Al-Fakih, A., Koeshidayatullah, A., Mukerji, Kaka. Next-generation GAN for well log data augmentation and integrity. AAPG Unlocking Hidden Potential GTW. Kuwait, Apr. 2025.
  10.  Al-Fakih. End-to-End GANs for Multidimensional Reservoir Characterization. SPE AI Symposium: Navigating the Nexus—Where Energy Meets AI and Sustainability. Al Khobar, Saudi Arabia. Feb.2025. Oral Presentation. https://www.spe-events.org/symposium/artificial-intelligence/attend/schedule.
  11. Al-Fakih, A., Koeshidayatullah, A., Mukerji,Alazani,  Kaka. Innovative GANs and AI for well log data synthesis, imputation, and anomaly detection. AAPG International Conference and Exhibition (ICE) Muscat, Oman, 30 September – 2 October 2024.
  12. Al-Fakih, A. A., Kaka, S., & Koeshidayatullah, A. (2024, September). AI-Driven Reservoir Management: GANs and GMM for Enhanced Control. ECMOR 2024. European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.202437004.
  13. Al-Fakih, Al-Khudafi, Koeshidayatullah, Kaka. Exploring Machine Learning Techniques for Predicting Geothermal Temperature in Western Yemen. SPWLA-SAC 14th Workshop – Advances in Geothermal Energy Exploration and Development.Al Khobar, Saudi Arabia, May 2024.
  14. Al-Fakih, A., Kaka, S., & Koeshidayatullah, A. (2024, April). Revolutionizing Carbonate Reservoir Characterization and Monitoring Through Generative Deep Learning. First EAGE Workshop on Advances in Carbonate Reservoirs. European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.2024634006.
  15. Al-Fakih, A., Kaka, S., & Koeshidayatullah, A. (2024). Enhancing Geoscience Analysis: AI-Driven Imputation of Missing Data in Well Logging Using Generative Models. EGU24-10627. Copernicus Meetings. https://doi.org/10.5194/egusphere-egu24-10627.
  16. Al-Fakih, A., Kaka, S., & Koeshidayatullah, A. (2024). Deep Learning in Reservoir Characterization: a GAN-based Approach. European Association of Geoscientists & Engineers. DOI: 10.3997/2214-4609.202430003.
  17. Al-Fakih, A., & Al-Khudafi, A. (2024, February). Unlocking the Potential of Geothermal Energy in Yemen: A Comparative Analysis with Global Trends. 49th Workshop on Geothermal Reservoir Engineering. Stanford University. SGP-TR-227.
  18. Al-Fakih, A., Kaka, S., & Koeshidayatullah, A. (2024, January). Utilizing GANs for Synthetic Well Logging Data Generation: A Step Towards Revolutionizing Near-Field Exploration. EAGE/AAPG Workshop on New Discoveries in Mature Basins. European Association of Geoscientists & Engineers. https://doi.org/10.3997/2214-4609.202471016.
  19. Al-Fakih, A., & Li, K. (2022). Estimation of Bottom-Hole Temperature Based on Machine/Deep Learning. In: Lin, J. (eds) Proceedings of the 2021 International Petroleum and Petrochemical Technology Conference. Springer, Singapore. https://doi.org/10.1007/978-981-16-9427-1_33.
  20. Al-Gathe, A.A., Al-Khudafi, A.M., Al-Fakih, A., Al-Wahbi, A.A. (2022). Neuro-Fuzzy Approach for Gas Compressibility Factor Prediction. Proceedings of the 2021 International Petroleum and Petrochemical Technology Conference. Springer, Singapore. https://doi.org/10.1007/978-981-16-9427-1_15.
  21. Al-Fakih A, Li K. Study of geothermal energy resources of Yemen for electric power generation. GRC Trans. Reno, Nevada, USA. 2019:42(2018).

Awards & Honors

  • Awarded (Full Grant) – International Summer School on Smart Civil Engineering PHASE VIII, Northeastern University, Shenyang, Liaoning, China, July 2025.
  • Awarded (Full Grant) – PROM Programme from the Institute of Geological Sciences, Jagiellonian University, Kraków, Poland, June 2025.
  • Nominated for the SPE Middle East and North Africa Student Paper Contest, Abu Dhabi, May 2025.
  • Third place, SPE-KSA AI Hackathon, Saudi Arabia, Feb. 2025
  • Invited speaker: MEOS GEO ’2025, SPE AI ’2025, Sinopec DTV ’2025.
  • First place, GEO4.0 Hackathon, Saudi Arabia, 2024.
  • First place, IADC DrillTech Arena Contest, Oman, 2024.
  • Awarded full scholarships for Master’s (China),2017-2020, and PhD (Saudi Arabia), 2021-2025.
  • Leadership: Graduate Ambassador at KFUPM, Active in SPE, SEG, SPWALA, IADC, AAPG
  • Nominated in the SPWLA paper contest at SPWLA -KFUPM-Aramco RDD, Dhahran, March 2023
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