High-Resolution Seismic Pseudo-Reflectivity Imaging with FWI and Migration
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Solution Overview
Problem
Conventional pseudo-reflectivity images suffer from limited resolution due to the frequency gap between inversion-based and migration-based seismic imaging processes, leading to the loss of fine subsurface structure details.
Innovation Solution
A method and apparatus that combines full waveform inversion (FWI) and migration-based processes to generate high-resolution pseudo-reflectivity images by constructing a velocity model, performing seismic migration, computing polarized normal vectors, and combining them with a velocity gradient to produce images at higher frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional inversion-based or migration-based seismic imaging processes are used separately, then the processing is relatively simple, but the image resolution is limited due to frequency gap
Solution Approach 1:
The patent combines full waveform inversion (FWI) and migration-based seismic imaging processes into a unified workflow. The velocity model from FWI is integrated with migration imaging, and polarized normal vectors are computed to enhance the pseudo-reflectivity image. This merging of previously separate processes resolves the frequency gap and achieves high-resolution imaging that neither method could achieve alone.
2Loss of information
If full waveform inversion and migration processes are combined to bridge the frequency gap, then fine subsurface structure details are preserved, but the computational complexity increases
Solution Approach 1:
The patent performs full waveform inversion to construct a velocity model before executing the migration process. This preliminary velocity model preparation enables the subsequent migration and polarized normal vector computation to proceed efficiently at higher frequencies, preserving fine subsurface details while managing computational resources through staged processing.
3Productivity
If conventional pseudo-reflectivity imaging is used, then the processing is faster, but fine subsurface structure details are lost due to limited resolution
Solution Approach 1:
The patent changes the frequency parameters by utilizing the velocity model from FWI to enable migration and polarized normal vector computation at higher frequencies. This parameter change allows the system to achieve both high processing efficiency and high-resolution imaging, overcoming the traditional trade-off between speed and detail preservation.
Data Source
AI summary
A method for generating a high-resolution pseudo-reflectivity image of a subsurface region includes receiving seismic data associated with a subsurface region and captured by one or more seismic receivers, constructing a velocity model of the subsurface region based on the received seismic data, performing a seismic migration of the received seismic data based on the constructed velocity model to obtain migrated seismic data, computing polarized normal vectors associated with one or more subsurface reflectors of the subsurface region based on the migrated seismic data, and generating a pseudo-reflectivity image of the subsurface region based on both the computed polarized normal vectors.