地球与空间科学学院 • 研究员
办公地址:
北京大学理科二号楼8楼
电子邮件:
zy.zhao at pku.edu.cn
地球与空间科学学院 • 研究员
办公地址:
北京大学理科二号楼8楼
电子邮件:
zy.zhao at pku.edu.cn
助理教授
主要研究方向
科研方向以探索地球物理方法及其应用为主,结合地震学、应用数学,机器学习和高性能计算等交叉学科。研究课题包括数值模拟地震波场传播过程、地震数据地下介质物性反演和成像、应用数学在地球物理领域的应用等。致力于研究高分辨率、高精度的地球物理地震数据反演和成像方法,为准确了解地下构造提供理论和方法支持。
主要研究成果集中于勘探地震数据高效率逆时偏移成像、适用于大尺度高维度的快速全局优化算法、基于快速采样算法的贝叶斯全波形反演等。成果可应用于油气勘探,深地探索,地热资源利用,温室气体地下封存检测等领域。
近期代表性成果
Zhao, Z., M. K. Sen, B. Denial, D. Sun and P. Williams, 2022, A hybrid optimization framework for seismic full waveform inversion, Journal of Geophysical Research: Solid Earth 127(8), e2022JB024483
Hybrid optimization FWI for a blind test model of deep-water salt provinces in the Gulf of Mexico, a) Initial model, b) to d) are intermediate and final results.
Geng, Z., Z. Zhao*, Y. Shi, X. Wu, S. Fomel and M. K. Sen, 2022, Deep learning for velocity model building with common-image gathers, Geophysical Journal International 228(2), 1054-1070
Kardell, D., Z. Zhao, E. Ramos, J. Estep, G. Christeson and R. Reece, 2021, Tectonic activity near the Rio Grande Rise increases fluid flux in old oceanic crust, Geophysical Research Letter, 48(17), e2021GL094624
Seismic velocity model and associated uncertainty map. (a) Seismic P-wave velocity model from full-waveform inversion (FWI). (b) Standard deviation map for the estimated posterior distribution produced by gradient-based Markov chain Monte Carlo (GMCMC) FWI. (c) Average layer 2A velocity.
Kardell, D., Z. Zhao, E. Ramos, J. Estep, G. Christeson, R. Reece and M. Hesse, 2021, Permeability-constrained fluid flow models confirm hydrothermal cooling of 7-63 Ma South Atlantic crust, Journal of Geophysical Research - Solid Earth, 126(6)
Zhao, Z. and M. K. Sen, 2021, A gradient based McMC method for full waveform inversion and uncertainty analysis, Geophysics, 86(1), R15-R30