报告人：杨积忠研究员

报告题目：Full waveform inversion based on random gradient sampling

摘要：Full-waveform inversion (FWI) has the great potential to provide high-resolution models of the subsurface by using the full information contents of the observed seismic data, if a highly accurate starting velocity model and the low-frequency information in the observed seismic data are readily available. To mitigate these requirements, we apply the gradient sampling algorithm (GSA) introduced for nonsmooth, nonconvex optimization problems to FWI. The search space is hugely expanded to have more freedom to accommodate large velocity errors in the starting model. The proposed method can be flexibly implemented both in the time domain and in the frequency domain. The computational costs and memory requirements of the proposed method are the same as conventional FWI. To be applied to real data, we also adopt the variable projection method to further mitigate the dependence on the accurate estimation of the source signature. Multiple numerical examples will be used in the presentation to demonstrate that the proposed method alleviates the cycle-skipping problem of conventional FWI when starting from very crude initial velocity models without low-frequency data and with unknown source wavelet.

报告时间：2022年8月18日周四下午3:00-5:00

报告形式：腾讯会议701-329-072

报告人简介：杨积忠，同济大学海洋与地球科学学院特聘研究员，博士生导师，2021年入选上海市海外高层次引进人才。2020年3月至2021年2月任同济大学海洋与地球科学学院副研究员。2017年2月至2020年2月在新加坡国立大学土木与环境工程系从事博士后研究工作。杨积忠的主要研究方向包括：地震波传播与模拟、地震波反演与成像、VSP地震数据处理、分布式光纤声波传感地震数据采集与处理以及机器学习在地球物理中的应用。杨积忠在勘探地震学领域的《Geophysics》、《Geophysical Journal International》等权威期刊上共发表34篇SCI论文。现任《Geophysics》期刊副主编，《Geophysics》、《Geophysical Journal International》、《Geophysical Prospecting》、《IEEE Transactions on Geoscience and Remote Sensing》和《Petroleum Science》等期刊审稿人。主持国家自然科学基金青年科学基金项目1项。