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Abstract Increasing deployment of dense arrays has facilitated detailed structure imaging for tectonic investigation, hazard assessment and resource exploration. Strong velocity heterogeneity and topographic changes have to be considered during passive source imaging. However, it is quite challenging for ray‐based methods, such as Kirchhoff migration or the widely used teleseismic receiver function, to handle these problems. In this study, we propose a 3‐D passive source reverse time migration strategy based on the spectral element method. It is realized by decomposing the time reversal full elastic wavefield into amplitude‐preserved vector P and S wavefields by solving the corresponding weak‐form solutions, followed by a dot‐product imaging condition to get images for the subsurface structures. It enables us to use regional 3‐D migration velocity models and take topographic variations into account, helping us to locate reflectors at more accurate positions than traditional 1‐D model‐based methods, like teleseismic receiver functions. Two synthetic tests are used to demonstrate the advantages of the proposed method to handle topographic variations and complex velocity heterogeneities. Furthermore, applications to the Laramie array data using both teleseismic P and S waves enable us to identify several south‐dipping structures beneath the Laramie basin in southeast Wyoming, which are interpreted as the Cheyenne Belt suture zone and agree with, and improve upon previous geological interpretations.
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WISE: Full-waveform variational inference via subsurface extensions
We introduce a probabilistic technique for full-waveform inversion, using variational inference and conditional normalizing flows to quantify uncertainty in migration-velocity models and its impact on imaging. Our approach integrates generative artificial intelligence with physics-informed common-image gathers, reducing reliance on accurate initial velocity models. Considered case studies demonstrate its efficacy producing realizations of migration-velocity models conditioned by the data. These models are used to quantify amplitude and positioning effects during subsequent imaging.
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- Award ID(s):
- 2203821
- PAR ID:
- 10528170
- Publisher / Repository:
- Society of Exploration Geophysicists
- Date Published:
- Journal Name:
- GEOPHYSICS
- Volume:
- 89
- Issue:
- 4
- ISSN:
- 0016-8033
- Page Range / eLocation ID:
- A23 to A28
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1190/geo2023-0744.1
