# Foreword to New developments in passive seismic imaging and monitoring

Nikolai Shapiro, Michel Campillo, Anne Obermann, Andrew Curtis

► To cite this version:

Nikolai Shapiro, Michel Campillo, Anne Obermann, Andrew Curtis. Foreword to New developments in passive seismic imaging and monitoring. Comptes Rendus. Géoscience, 2024, 356 (S4), pp.1-3. 10.5802/crgeos.281. hal-04881656

HAL Id: hal-04881656

https://hal.science/hal-04881656v1

Submitted on 14 Jan 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Comptes Rendus
## Géoscience
### Sciences de la Planète

Nikolai M. Shapiro, Michel Campillo, Anne Obermann and Andrew Curtis

**Foreword to New developments in passive seismic imaging and monitoring**

Published online: 2 December 2024

**Part of Special Issue:** New Developments in Passive Seismic Imaging and Monitoring

**Guest editors:** Michel Campillo (University Grenoble-Alpes, Institut des Sciences de la Terre, Grenoble, France),
Andrew Curtis (School of GeoSciences, University of Edinburgh, Scotland),
Anne Obermann (Swiss Seismological Service, ETH, Zurich, Switzerland) and Nikolai Shapiro (CNRS, Institut des Sciences de la Terre, Grenoble, France)

https://doi.org/10.5802/crgeos.281

<figure><img src="image_2.png" /></figure>

This article is licensed under the

CREATIVE COMMONS ATTRIBUTION 4.0 INTERNATIONAL LICENSE.

http://creativecommons.org/licenses/by/4.0/
# Foreword

## New Developments in Passive Seismic Imaging and Monitoring

## Foreword to New developments in passive seismic imaging and monitoring

Nikolai M. Shapiro<sup>a, c</sup>, Michel Campillo<sup>a, c</sup>, Anne Obermann<sup>b</sup> and Andrew Curtis<sup>c</sup>

**Funding.** ERC Advanced Grants F-Image, SEISMAZE, FaultScan.

During the last two decades, imaging and monitoring methods based on cross-correlations of ambient seismic noise have been extensively developed and have become widely used at different scales and in different natural and human-controlled environments. Application of these methods has been facilitated by improved availability of data from large and dense seismic networks and by several open software packages. At the same time, noise-based imaging and monitoring is far from becoming just a set of “standard” and “routine” methods. As discussed in this special issue, the origin and nature of the seismic noise wavefields, their correlation properties as well as their sensitivity to the medium structure and changes, remain areas of active study. Improving their understanding is necessary in order to refine the existing methods and to develop new approaches for imaging and monitoring. Therefore, noise-based passive seismology remains a dynamic field of research with some first-order problems yet to be solved. In this context, 13 years after the first thematic issue of Comptes Rendus Géoscience on passive seismic noise-based imaging and monitoring [e.g., Campillo et al., 2011] we introduce a new special issue devoted to this topic.

Most passive noise-based seismic imaging and monitoring methods are based on the so-called “noise cross-correlation theorem” [e.g., Lobkis and Weaver, 2001, Wapenaar, 2004, Roux et al., 2005, Campillo, 2006, Gouédard et al., 2008] which states that the time derivative of cross-correlation of an ideal fully diffuse wavefield converge to the Green’s function of the medium in which the waves are propagating. The fully diffuse wavefield can be defined either as being composed of all possible medium vibration modes with equally partitioned energy, or locally as composed of isotropic combination of plane waves, or as generated by homogenously distributed random sources. Neither of these definitions applies to the real Earth’s seismic noise whose main sources are inhomogeneously distributed over the surface. This makes direct application of the “full” cross-correlation theorem to real seismological data questionable, and requires that we further improve our understanding of seismic noise cross-correlations to develop accurate methods.

So far, the surface wave part of Green’s functions has been most reliably reconstructed from the correlations of the ambient seismic noise. Since initial demonstration of this possibility [e.g., Shapiro

<footnote><sup>a</sup> Institut des Sciences de la Terre, University Grenoble Alpes, CNRS, University Savoie
Mont Blanc, IRD, University Gustave Eiffel, Grenoble, France</footnote>

<footnote><sup>b</sup> Swiss Seismological Service, ETH Zurich, Switzerland</footnote>

<footnote><sup>c</sup> School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FE, UK</footnote>

<footnote>E-mails: nikolai.shapiro@univ-grenoble-alpes.fr (N. M. Shapiro), michel.campillo@univ-grenoble-alpes.fr (M. Campillo), anne.obermann@sed.ethz.ch (A. Obermann), andrew.curtis@ed.ac.uk (A. Curtis)</footnote>
and Campillo, 2004, Shapiro et al., 2005, Sabra et al., 2005a,b) a family of methods known as Ambient Noise Surface Wave Tomography (ANSWT) has been developed and successfully applied in many studies [e.g., Ritzwoller et al., 2011, Shapiro, 2018]. A systematic application of this approach to image the European Alps is presented by Paul et al. [2024]. The authors show how methodological advances of this approach evolving from simple isotropic group velocity tomography to wave-equation based inversions, and those based on trans-dimensional Bayesian formalism and including anisotropy, significantly improved knowledge of the structure of the crust and shallow mantle beneath the Alps-Apennines system.

Giammarinaro et al. [2024] use two-dimensional simulations of wave propagation to investigate the lateral resolution power of an alternative approach to ANSWT: seismic Rayleigh wave focal spot imaging. They demonstrate that the station configuration can be tuned to improve image quality and properties, and that high-quality data from dense networks can result in super-resolution.

Lavoué et al. [2024] investigate the applicability of the ANSWT at small scales, i.e., those of a single sedimentary basin, to resolve the near-surface structure for estimation of site amplifications required for seismic hazard models. They show that, while ANSWT results reproduce well the main geological structures of the basin, they have limited capability to accurately predict the numerical amplification near the basin edges and other locations with significant 3D wave propagation effects. This allows the authors to suggest perspectives for future improvement of ANSWT, that shows promise for site effect assessment in low- to moderate-seismicity contexts.

Boué and Tomasetto [2024] investigate how the teleseismic body waves are generated by oceanic forcing on the Earth's surface, resulting in a spatially inhomogeneous distribution of microseismic sources. The authors show that, despite the inherent complexity of these noise sources, cross-correlation based methods applied to properly selected pairs of stations result in the isolation of coherent waves for imaging applications and propose a workflow based on ocean sea state models to extract robust interferences.

Influence of the heterogeneous distribution of noise sources on the accuracy of noise-based seismic monitoring is studied by Stehly et al. [2024] who

perform a single station analysis at all available European broadband stations. They show that at short periods (<3 s), the noise field in Europe is dominated by surface waves coming from two sources: (1) the north Atlantic Ocean dominating during winters, and (2) the Adriatic and Aegean Seas increasing in summer. The interplay of these two source regions leads to time and space dependent convergence of the coda part of cross-correlations, and thus in across-Europe variations of the accuracy and temporal resolution of detected seismic velocity changes.

Other important aspects of the noise-based seismic monitoring are addressed by Canel et al. [2024] who investigate the physical mechanisms that could explain the seismic velocity changes measured from the noise cross-correlations in the vicinity of active fault zones. The authors perform a set of numerical experiments to test a simple model of a cohesive granular medium and to study the relationship between the damage and velocity of elastic waves. They show that the microscopic deformation of cohesive discrete media quickly becomes very heterogeneous with a small amount of damage inducing a strong decrease in the elastic velocity. As a consequence, they suggest that monitoring the wave velocities in such media could measure subtle transient deformation processes, such as earthquake initiation phases.

## Acknowledgments

The content of the present thematic Issue was discussed during the 6th edition of the school on Passive Imaging and Monitoring in Wave Physics: From Seismology to Ultrasound, that was held on April 18–22, 2022 at the Institut d'Études Scientifiques de Cargèse in Corsica, France. We thank the contributors of the special issue and the participants to the workshop as well as all people who contributed to its logistics. The workshop and the organization of this issue were made possible by the support of CNRS (France), and Université Grenoble Alpes (Grenoble, France). The authors acknowledge support from the ERC Advanced Grants F-Image, SEISMAZE, and FaultScan.

## References

- Boué, P. and Tomasetto, L. (2024). Opportune detections of global P-wave propagation from microseisms interferometry. *C. R. Géosci.*, 356(S4), 1–16. (Online first).
Campillo, M. (2006). Phase and correlation in 'random' seismic fields and the reconstruction of the green function. *Pure Appl. Geophys.*, 163, 475-502.

Campillo, M., Sato, H., Shapiro, N. M., and van der Hilst, R. D. (2011). New developments on imaging and monitoring with seismic noise. *C. R. Géosci.*, 343(8-9), 487-495.

Canel, V., Campillo, M., Jia, X., and Ionescu., I. R. (2024). Damage in cohesive granular materials: simulations and geophysical implications. *C. R. Géosci.*, 356(S4), 1-21. (Online first).

Giammarinaro, B., Tsarsitalidou, C., and Hillers, G. (2024). Investigating the lateral resolution of the Rayleigh wave focal spot imaging technique using two-dimensional acoustic simulations. *C. R. Géosci.*, 356(S4), 1-17. (Online first).

Gouédard, P., Stehly, L., Brenguier, F., et al. (2008). Cross-correlation of random fields: mathematical approach and applications. *Geophys. Prospect.*, 56, 375-393.

Lavoué, F., Froment, B., Gélis, C., et al. (2024). Potential and limitations of noise-based surface-wave tomography for numerical site effect estimation: a case study in the French Rhône valley. *C. R. Géosci.*, 356(S4), 1-26. (Online first).

Lobkis, O. I. and Weaver, R. L. (2001). On the emergence of the Green's function in the correlations of a diffuse field. *J. Acoust. Soc. Am.*, 110(6), 3011-3017.

Paul, A., Pedersen, H. A., Bodin, T., Kästle, E., Soergel, D., Alder, C., Lu, Y., and Nouibat, A. (2024). Methodological advances in seismic noise imaging of the Alpine area. *C. R. Géosci.*, 356(S4), 1-35. (Online first).

Ritzwoller, M. H., Lin, F-C., and Shen, W. (2011).

Ambient noise tomography with a large seismic array. *C. R. Géosci.*, 343(8), 558-570.

Roux, P., Sabra, K. G., Kuperman, W. A., and Roux, A. (2005). Ambient noise cross correlation in free space: Theoretical approach. *J. Acoust. Soc. Am.*, 117(1), 79-84.

Sabra, K. G., Gerstoft, P., Roux, P., Kuperman, W. A., and Fehler, M. C. (2005a). Extracting time-domain Green's function estimates from ambient seismic noise. *Geophys. Res. Lett.*, 32, article no. L03310.

Sabra, K. G., Gerstoft, P., Roux, P., Kuperman, W. A., and Fehler, M. C. (2005b). Surface wave tomography from microseisms in Southern California. *Geo-phys. Res. Lett.*, 32, article no. L14311.

Shapiro, N. M. (2018). Applications with surface waves extracted from ambient seismic noise. In Nakata, N., Gualtieri, L., and Fichtner, A., editors, *Seismic Ambient Noise*. Cambridge University Press, Cambridge.

Shapiro, N. M. and Campillo, M. (2004). Emergence of broadband Rayleigh waves from correlations of the ambient seismic noise. *Geophys. Res. Lett.*, 31, article no. L07614.

Shapiro, N. M., Campillo, M., Stehly, L., and Ritzwoller, M. H. (2005). High resolution surface wave tomography from ambient seismic noise. *Science*, 307, 1615-1618.

Stehly, L., Delouche, E., Tomasetto, L., and Ranjan, P. (2024). Dynamic of seismic noise sources in the Mediterranean Sea: implication for monitoring using noise correlations. *C. R. Géosci.*, 356(S4), 1-24. (Online first).

Wapenaar, K. (2004). Retrieving the elastodynamic Green's function of an arbitrary inhomogeneous medium by cross correlation. *Phys. Rev. Lett.*, 93(25), article no. 254301.