Advancing seismic imaging: From kinematics to dynamics with elastic full-waveform inversion

Abstract Elastic full-waveform inversion (EFWI) combined with long-offset sparse ocean-bottom node seismic data demonstrates a transformative approach for advancing seismic imaging in the Gulf of Mexico. By using the full seismic wavefield, including diving waves, reflections, multiples, and prismatic waves, EFWI iteratively refines high-resolution velocity models that effectively capture complex geologic features, particularly in challenging subsalt environments. The EFWI-derived reflectivity (EFDR) offers balanced amplitudes, improved signal-to-noise ratio (S/N), and enhanced imaging of steeply dipping and subsalt structures, addressing the inherent limitations of conventional migration methods. Prestack EFDR gathers further extend EFWI's utility for reliable amplitude variation with offset analysis. To accelerate high-frequency EFDR generation, the FWI impedance image (referred to as FWI3 in this paper) workflow introduces a “frequency jump” strategy, bypassing intermediate frequency steps to efficiently achieve high-resolution results. Additionally, its multiparameter inversion framework simultaneously inverts for P-wave velocity and P impedance, effectively mitigating crosstalk between primary and multiple wavefields. Together, these advancements highlight a paradigm shift in seismic imaging, enabling dynamic amplitude-consistent solutions for structural interpretation and reservoir characterization in complex geologic settings, moving beyond conventional kinematic-focused structural approaches.

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Publication Details

Journal
The Leading Edge
Published
2025-05-01
DOI
https://doi.org/10.1190/tle44050362.1
Citations
2
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
3.73
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article

Advancing seismic imaging: From kinematics to dynamics with elastic full-waveform inversion

Denes Vigh, Zongcai Feng, Kate Glaccum, Jian Mao et al.
2 citations
The Leading Edge
Seismic Imaging and Inversion Techniques
3.73
article

Advancing seismic imaging: From kinematics to dynamics with elastic full-waveform inversion

Denes Vigh, Zongcai Feng, Kate Glaccum, Jian Mao, Yu Yao, Xin Cheng
article en
2 citations

Abstract

Abstract Elastic full-waveform inversion (EFWI) combined with long-offset sparse ocean-bottom node seismic data demonstrates a transformative approach for advancing seismic imaging in the Gulf of Mexico. By using the full seismic wavefield, including diving waves, reflections, multiples, and prismatic waves, EFWI iteratively refines high-resolution velocity models that effectively capture complex geologic features, particularly in challenging subsalt environments. The EFWI-derived reflectivity (EFDR) offers balanced amplitudes, improved signal-to-noise ratio (S/N), and enhanced imaging of steeply dipping and subsalt structures, addressing the inherent limitations of conventional migration methods. Prestack EFDR gathers further extend EFWI's utility for reliable amplitude variation with offset analysis. To accelerate high-frequency EFDR generation, the FWI impedance image (referred to as FWI3 in this paper) workflow introduces a “frequency jump” strategy, bypassing intermediate frequency steps to efficiently achieve high-resolution results. Additionally, its multiparameter inversion framework simultaneously inverts for P-wave velocity and P impedance, effectively mitigating crosstalk between primary and multiple wavefields. Together, these advancements highlight a paradigm shift in seismic imaging, enabling dynamic amplitude-consistent solutions for structural interpretation and reservoir characterization in complex geologic settings, moving beyond conventional kinematic-focused structural approaches.

The Leading EdgeVol. 44(5)
SwissLitho (Switzerland) (CH)
Openalex Percentile: Top 9%
Seismic Imaging and Inversion Techniques
3.73
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Advancing seismic imaging: From kinematics to dynamics with elastic full-waveform inversion — Denes Vigh, Zongcai Feng, et al. · The Leading Edge (2025) | TGRS Research Map | TGRS