Reflection FWI Density Velocity Model Update
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Solution Overview
Problem
Conventional Full Waveform Inversion (FWI) methods are limited in updating velocity models due to reliance on diving waves, which restricts depth and requires accurate density models for using reflection data, making it difficult to fully utilize low-wavenumber information from reflection data for enhancing seismic imaging.
Innovation Solution
The method separates high-wavenumber and low-wavenumber components of the FWI gradient to update density and velocity models respectively, using reflection data to extend the applicability of FWI workflow beyond the limitations of diving waves, allowing for deeper subsurface exploration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional FWI methods use diving waves to update velocity model, then velocity model can be updated, but the maximum depth is restricted and accurate density model is required
Solution Approach 1:
The patent separates the FWI gradient into high-wavenumber and low-wavenumber components, and further divides the updating process into two distinct phases: first updating density model using high-wavenumber component, then updating velocity model using low-wavenumber component. This segmentation allows each parameter to be updated with the most appropriate gradient information, extending the depth of velocity model updates beyond the limitations of diving waves alone.
2Length of moving object
If reflection data is used in conventional FWI, then deeper areas can be probed, but it requires accurate density model and lacks low frequencies
Solution Approach 1:
The patent performs density model updating using high-wavenumber component of the gradient before performing velocity model updates. This preliminary action of establishing an improved density model first provides a reliable foundation for subsequent velocity model updates using low-wavenumber information from reflection data, eliminating the circular dependency problem.
3Length of moving object
If low-wavenumber information from reflection data is used, then deeper subsurface can be explored, but conventional FWI cannot fully utilize it due to method limitations
Solution Approach 1:
The patent implements a two-phase updating workflow that segments the complex task of utilizing low-wavenumber information into manageable steps: Phase 1 updates density model using high-wavenumber component, and Phase 2 updates velocity model using low-wavenumber component. This structured segmentation makes the complex workflow systematic and implementable while fully utilizing low-wavenumber information from reflection data.
Data Source
AI summary
A reflection full waveform inversion method updates separately a density model and a velocity model of a surveyed subsurface formation. The method includes generating a model-based dataset corresponding to the seismic dataset using a velocity model and a density model to calculate an objective function measuring the difference between the seismic dataset and the model-based dataset. A high-wavenumber component of the objective function's gradient is used to update the density model of the surveyed subsurface formation. The model-based dataset is then regenerated using the velocity model and the updated density model, to calculate an updated objective function. The velocity model of the surveyed subsurface formation is then updated using a low-wavenumber component of the updated objective function's gradient. A structural image of the subsurface formation is generated using the updated velocity model.