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A passive inverse filter for Green's function retrieval.

Thomas Gallot¹, Stefan Catheline, Philippe Roux

¹Institut des Sciences de la Terre, CNRS, UMR5275 IFSTTAR Université de Savoie Université Joseph Fourier-Grenoble I INSU OSUG IRD: UR219, France. thomas.gallot@gmail.com

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Summary

This summary is machine-generated.

This study introduces a spatiotemporal inverse filter to reduce bias in passive Green's function recovery. The method effectively compensates for nonisotropic noise, improving seismic wavefield analysis.

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Area of Science:

Geophysics
Seismology
Wave Propagation

Background:

Passive seismic methods for Green's function recovery often assume isotropic noise sources.
Nonisotropic noise distribution introduces significant bias in reconstructed Green's functions.
Accurate Green's function retrieval is crucial for seismic imaging and monitoring.

Purpose of the Study:

To develop and validate a novel spatiotemporal inverse filter to mitigate bias in passive Green's function recovery.
To address the challenge of nonisotropic noise fields in ambient noise seismology.
To enhance the reliability of Green's functions derived from passive seismic data.

Main Methods:

A spatiotemporal inverse filter was designed to process ambient noise data.
The method was tested using a directive noise field derived from experimental active seismic data.
The filter manipulates spatiotemporal degrees of freedom within the complex wave field.

Main Results:

The proposed inverse filter successfully minimized bias caused by nonisotropic noise.
The method demonstrated efficient compensation for noise wavefield directivity.
Validation on experimental data confirmed the filter's effectiveness.

Conclusions:

The spatiotemporal inverse filter is a viable technique for improving passive Green's function recovery.
This method enhances the applicability of passive seismic techniques in realistic, nonisotropic noise environments.
Accurate Green's function reconstruction is achievable even with complex, directive noise sources.