A 3-D algorithm based on the combined inversion of Rayleigh and Love waves for imaging and monitoring of shallow structures. Issue 1 (6th January 2017)

• Record Type: Journal Article
• Authors: Pilz, Marco; Parolai, Stefano; Woith, Heiko
• Is Part Of: Geophysical journal international. Volume 209:Issue 1(2017:Apr.)
• Page Start: 152
• Page End: 166
• Publication Date: 2017-01-06
• Subjects: Surface waves and free oscillations -- Seismic tomography; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggx005
• Languages: English
• ISSNs: 0956-540X

Abstract

Summary: In recent years, there has been increasing interest in the study of seismic noise interferometry as it can provide a complementary approach to active source or earthquake-based methods for imaging and continuous monitoring the shallow structure of the Earth. This meaningful information is extracted from wavefields propagating between those receiver positions at which seismic noise was recorded. Until recently, noise-based imaging relied mostly on Rayleigh waves. However, considering similar wavelengths, a combined use of Rayleigh and Love wave tomography can succeed in retrieving velocity heterogeneities at depth due to their different sensitivity kernels. Here, we present a novel one-step algorithm for simultaneously inverting Rayleigh and Love wave dispersion data aiming at identifying and describing complex 3-D velocity structures. The algorithm may help to accurately and efficiently map the shear wave velocities and the Poisson ratio of the surficial soil layers. In the high-frequency range, the scattered part of the correlation functions stabilizes sufficiently fast to provide a reliable estimate of the velocity structure not only for imaging purposes but also allows for changes in the medium properties to be monitored. Such monitoring can be achieved with a high spatial resolution in 3-D and with a time resolution as small as a few hours. In this paper, we describe a recent array experiment in a volcanic environment in Solfatara (Italy) and we show that this novel approach has identified strong velocity variations at the interface between liquids and gas-dominated reservoirs, allowing localizing a region which is highly dynamic due to the interaction between the deep convection and its surroundings.