Model-driven and data-driven inverse problems with AI analysis

王彦飞 研究员

中国科学院 地质与地球物理研究所

2024.03.29（星期五）15:00，理科二号楼2821

摘要：

In the field of geophysics, big data, AI, and inverse problems involve cross-disciplinary integration of computer science, mathematics, statistics, and geophysics. This approach enables the development of accurate subsurface property models by analyzing vast amounts of geophysical data. Traditionally, various geophysical methods were used to study geological anomalies, but the use of big data and AI has shown potential to enhance this process. This talk will introduce both model-driven and data-driven inverse problems and explain how optimizing algorithms are used to solve for physical properties of the earth's subsurface from geophysical data collected at the surface.

报告人简介：

       王彦飞，中国科学院地质与地球物理研究所，研究员。从事反问题基础理论及方法、反问题的数学优化算法、计算及勘探地球物理、地学大数据与人工智能分析研究工作。曾主持国家杰出青年基金等多项科研项目，入选国家高层次人才计划，获中国青年科技奖等多项科研奖励。