The Earth's coda correlation wavefield: Rise of the new paradigm and recent advances

Tkalčić, Hrvoje; Phạm, Thanh‐Son; Wang, Sheng

doi:10.1016/j.earscirev.2020.103285

Cited by 41 publications

(60 citation statements)

References 95 publications

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“…A promising direction for further application is to extend the proposed framework to correlation-based deep Earth seismology, either using ocean microseism (Boué et al 2014;Retailleau et al 2020) or late earthquake coda waves (Pha . m et al 2018;Tkalčić et al 2020;. For microseism sources observed at teleseismic distances, we expect the problem to be similar to the case presented above using train traffic, i.e.…”

Section: Discussionsupporting

confidence: 58%

“…Although this approach has been tremendously successful over the last two decades, recent developments address its shortcomings by interpreting correlations as self-consistent observables (Tromp et al 2010;Hanasoge 2013;Pha . m et al 2018;Sager et al 2018b;Tkalčić et al 2020). A subset of these studies relies on forward modeling correlation wavefields instead of correlating simulated wavefields.…”

Section: Modeling Correlations and Computing Sensitivity Kernelsmentioning

confidence: 99%

See 1 more Smart Citation

Modeling P waves in seismic noise correlations: Advancing fault monitoring using train traffic sources

Sager¹,

Tsai²,

Sheng³

et al. 2022

Preprint

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The theory of Green's function retrieval essentially requires homogeneously distributed noise sources. Even though these conditions are not fulfilled in nature, low-frequency (<1 Hz) surface waves generated by ocean-crust interactions have been used successfully to image the crust with unprecedented spatial resolution. In contrast to low-frequency surface waves, high-frequency (>1 Hz) body waves have a sharper, more localized sensitivity to velocity contrasts and temporal changes at depth. In general, their retrieval using seismic interferometry is challenging, and recent studies focus on powerful, localized noise sources. They have proven to be a promising alternative but break the assumptions of Green's function retrieval. In this study, we present an approach to model correlations between P waves for these scenarios and analyze their sensitivity to 3D Earth structure. We perform a series of numerical experiments to advance our understanding of these signals and prepare for an application to fault monitoring. In the considered cases, the character of the signals strongly diverges from Green's function retrieval, and the sensitivity to structure has significant contributions in the source direction. An accurate description of the underlying physics allows us to reproduce observations made in the context of monitoring the San Jacinto Fault in California using train-generated seismic waves. This approach provides new perspectives for detecting and localizing temporal velocity changes previously unnoticed by commonly exploited surface-wave reconstructions.

show abstract

Section: Discussionsupporting

confidence: 58%

Section: Modeling Correlations and Computing Sensitivity Kernelsmentioning

confidence: 99%

Modeling P waves in seismic noise correlations: Advancing fault monitoring using train traffic sources

Sager¹,

Tsai²,

Sheng³

et al. 2022

Preprint

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show abstract

“…Here we present a new observation of IC shear-wave anisotropy based on recent advances in global codacorrelation wavefield Tkalčić et al, 2020). We observe stable time and amplitude variations for the coda-correlation feature I2-J sensitive to Jwave speed at the periods 15-50 s when its constituents sample the IC in different directions.…”

Section: Introductionmentioning

confidence: 88%

Shear-wave Anisotropy in the Earth’s Inner Core

Wang¹,

Tkalčić²

2021

Preprint

Self Cite

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Earth’s inner core anisotropy is widely used to infer the deep Earth's evolution and present dynamics. Many compressional-wave anisotropy models have been proposed based on seismological observations. In contrast, inner-core shear-wave (J-wave) anisotropy – on a par with the compressional-wave anisotropy – has been elusive. Here we present a new class of the J-wave anisotropy observations utilizing earthquake coda-correlation wavefield. We establish that the coda-correlation feature I2-J, sensitive to J-wave speed, exhibits time and amplitude changes when sampling the inner core differently. J-waves traversing the inner core near its center travel faster for the oblique than equatorial angles relative to the Earth’s rotation axis by at least ~5 s. The simplest explanation is the J-wave cylindrical anisotropy with a minimum strength of ~0.8%, formed through the lattice-preferred-orientation mechanism of iron. Although we cannot uniquely determine its stable iron phase, the new observations rule out one of the body-centered-cubic iron models.

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“…Although this approach has been tremendously successful over the last two decades, recent developments address its shortcomings by interpreting correlations as self-consistent observables (Tromp et al 2010;Hanasoge 2013;Pha . m et al 2018;Sager et al 2018b;Tkalčić et al 2020). A subset of these studies relies on forward modelling correlation wavefields instead of correlating simulated wavefields.…”

Section: O D E L L I N G C O R R E L At I O N S a N D C O M P U T I N G S E N S I T I V I T Y K E R N E L Smentioning

confidence: 99%

ModellingPwaves in seismic noise correlations: advancing fault monitoring using train traffic sources

Sager

Tsai

Sheng

et al. 2021

Geophysical Journal International

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Summary The theory of Green’s function retrieval essentially requires homogeneously distributed noise sources. Even though these conditions are not fulfilled in nature, low-frequency (<1 Hz) surface waves generated by ocean-crust interactions have been used successfully to image the crust with unprecedented spatial resolution. In contrast to low-frequency surface waves, high-frequency (>1 Hz) body waves have a sharper, more localized sensitivity to velocity contrasts and temporal changes at depth. In general, their retrieval using seismic interferometry is challenging, and recent studies focus on powerful, localized noise sources. They have proven to be a promising alternative but break the assumptions of Green’s function retrieval. In this study, we present an approach to model correlations between P waves for these scenarios and analyze their sensitivity to 3D Earth structure. We perform a series of numerical experiments to advance our understanding of these signals and prepare for an application to fault monitoring. In the considered cases, the character of the signals strongly diverges from Green’s function retrieval, and the sensitivity to structure has significant contributions in the source direction. An accurate description of the underlying physics allows us to reproduce observations made in the context of monitoring the San Jacinto Fault in California using train-generated seismic waves. This approach provides new perspectives for detecting and localizing temporal velocity changes previously unnoticed by commonly exploited surface-wave reconstructions.

show abstract

The Earth's coda correlation wavefield: Rise of the new paradigm and recent advances

Cited by 41 publications

References 95 publications

Modeling P waves in seismic noise correlations: Advancing fault monitoring using train traffic sources

Modeling P waves in seismic noise correlations: Advancing fault monitoring using train traffic sources

Shear-wave Anisotropy in the Earth’s Inner Core

ModellingPwaves in seismic noise correlations: advancing fault monitoring using train traffic sources

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