Dr. Mingxuan Gu is an accomplished Assistant Research Fellow specializing in the geological storage of carbon dioxide at Huairou National Laboratory, Beijing. He holds a Ph.D. in Geological Resources and Geological Engineering and a strong academic foundation in exploration technology and petroleum engineering. His research focuses on multidimensional nuclear magnetic resonance (NMR) logging, reservoir evaluation, and the integration of artificial intelligence with physical meaning constraints for advanced subsurface analysis. Dr. Gu’s innovative contributions have significantly advanced the understanding and quantitative evaluation of fluid components in complex geological formations, particularly through the use of 2D and multidimensional NMR spectra. His scholarly work has been featured in leading international journals such as Marine and Petroleum Geology, Journal of Petroleum Science and Engineering, Energy & Fuels, and Computers and Geosciences. He has also presented his findings at prestigious global conferences, reflecting his engagement with the international scientific community. Dr. Gu has authored 12 research documents, which have collectively received 84 citations across 55 citing documents, demonstrating the growing recognition and impact of his work. He holds an h-index of 6, reflecting the quality and influence of his scholarly contributions in the field. His research emphasizes practical applications in carbon storage and reservoir characterization, contributing to cleaner and more efficient energy solutions. Through his dedication to advancing NMR-based methodologies and his commitment to sustainable subsurface exploration, Dr. Gu continues to establish himself as a leading researcher in the intersection of artificial intelligence, petrophysics, and carbon sequestration.
Featured Publications
Gu, M., Xie, R., & Jin, G. (2021). A machine-learning based quantitative evaluation of the fluid components on T2-D spectrum.
Gu, M., Xie, R., & Xiao, L. (2021). A novel method for NMR data denoising based on discrete cosine transform and variable length windows.
Gu, M., Xie, R., Jin, G., et al. (2021). A hybrid compression method for the NMR data based on Window Averaging and Discrete Cosine Transform.
Gu, M., Xie, R., Jin, G., et al. (2021). Quantitative evaluation for fluid components on 2D NMR spectrum using Blind Source Separation.
Gu, M., Xie, R., & Xiao, L. (2021). Two-step inversion method for NMR relaxometry data using norm smoothing and artificial fish swarm algorithm.