Research Interests

Guang develops systems for real-time wellbore casing inspection and 3D visualization. He constructs novel neural networks for electromagnetic inspection tools developed in conjunction with the MERGE team, which generates casing cross-sectional images from spatio-temporal data. In addition, Guang is interested in programming drilling simulators in Java and Python.

Education Profile

• B.Sc., Aeronautics and Astronautics Engineering, National Cheng Kung University, Taiwan, 2017
• M.Sc., Electrical Engineering, King Abdullah University of Science and Technology, Saudi Arabia, 2019

Dissemination

• Multi-frequency Data Acquisition Model And Hybrid Neural Network For Precise Electromagnetic Wellbore Casing Inspection
• Ooi, G.A, Khater M., Özakin, M.B., Mostafa, T.M., Bagci, H., Ahmed, S.  and Larbi Zeghlache, M.
  SPE Abu Dhabi International Petroleum Exhibition Conference (ADIPEC), (2022)
• Near- And Remotefield Eddy Current Data Fusion: Wellbore Casing Inspection With Hybrid Neural Networks
  Ooi, G.A, Mostafa, T.M., Özakin, M.B., Khater M.,  Bagci, H., Ahmed, S.  and Larbi Zeghlache, M.
  SPE Abu Dhabi International Petroleum Exhibition Conference (ADIPEC), (2022)
• EM-Based 2D Corrosion Azimuthal Imaging using Physics Informed Machine Learning PIML 
  Ooi, G.A., Özakin, M.B., Mostafa, T.M., Bagci, H., Ahmed, S. and Larbi Zeghlache, M.
  SPE Offshore Europe Conference & Exhibition. OnePetro, (2021)

Awards and Distinctions

• CEMSE Dean’s List Award for Academic year 2021/2022