Research Focus:
Exploring geophysical methods and their applications, combining seismology, applied mathematics, machine learning, and high-performance computing. Research topics include numerical simulation of seismic wavefield propagation, inversion and imaging of underground medium properties from seismic data, and the application of applied mathematics in geophysics. Dedicated to developing high-resolution, high-precision inversion and imaging methods for geophysical seismic data to provide theoretical and methodological support for accurately understanding underground structures.
Main Research Achievements:
Focused on efficient reverse time migration imaging of exploration seismic data, fast global optimization algorithms suitable for large-scale high-dimensional problems, and Bayesian full-waveform inversion based on fast sampling algorithms. These results can be applied in oil and gas exploration, deep earth exploration, geothermal resource utilization, and underground storage monitoring of greenhouse gases.
