报告人：Martin Schimmel（研究员）

时间：2023.10.30 15:00-16:30

地点：测绘馆206会议室

报告人简介

Martin Schimmel is a seismologist and received the degree “Diplom Geophysiker” (Master in Geophysics) from the University of Karlsruhe, Germany in 1992, and the Ph.D. degree from the Utrecht University, The Netherlands, in 1997. Since 2008, he is a research staff member of the GEO3BCN-CSIC (Barcelona, Spain). He is experienced and internationally recognized on the detection/identification of weak seismic signals and their use to constrain Earth structure, the study and usage of seismic noise for imaging and structural health monitoring, and the design of independent strategies to enhance seismic signals and/or to turn ambient noise into signals. M. Schimmel has more than 140 research articles with more than 110 indexed in the Science Citation Index most of them involving topics across seismology. Presently, he works on interferometric methods to image sedimentary basins and crustal structure, as well as to monitor structural variability in active mines. Since 2017, he collaborates with NASA-InSight to reveal the internal structure of Mars.

报告简介

Seismic ambient noise studies for structural monitoring and imaging purposes have gained increasing importance in seismology and surrounding research fields. This is mainly due to the ubiquity of noise sources and recent advances on how to use the seismic noise wave field. All of these noise studies are based on interferometric principles in which empirical Green functions (EGFs) or robust seismic noise responses are extracted, mostly by employing cross-correlations and subsequent correlogram stacking. During this presentation we will shortly revisit the concept of seismic interferometry and the phase coherence approach (phase weighted stacking and phase cross-correlation) to then discuss noise-based imaging and monitoring examples. Among the examples, we show how we use noise autocorrelations to achieve an approximation of the zero‐offset reflection response of the structure beneath seismic stations to finally map the Paleozoic basement of the Ebro Basin in North Spain, and how we detect structural variability before and during volcanic intrusions.