Multi-Stage FWI Process for Multiple-Free Seismic Data
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Solution Overview
Problem
Conventional seismic inversion methods rely primarily on primary reflections, treating multiple reflections as noise and struggling to effectively remove surface-related multiples, especially when they overlap with primary reflections, which can damage the data and render it unusable for inversion.
Innovation Solution
A multi-stage Full Wavefield Inversion (FWI) process is performed with a free-surface boundary condition to generate a subsurface model, predict and remove surface-related multiples, and then apply an absorbing boundary condition for a second FWI process to produce a multiple-free data set, utilizing Born modeling and adaptive subtraction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If conventional multiple suppression methods are applied to remove surface-related multiples, then multiple reflections are eliminated, but primary reflection data is damaged and rendered unusable for inversion
Solution Approach 1:
The patent converts the harmful surface-related multiples into a beneficial resource by using them as input data for Full Wavefield Inversion. Instead of removing multiples and risking primary data damage, the method utilizes the multiples-containing data to invert for subsurface properties, thereby transforming the previously harmful factor into a useful signal for subsurface characterization.
Solution Approach 2:
The patent applies inversion by using the observed seismic data containing multiples to generate a subsurface model through FWI. The process inverts the forward modeling operation, taking the recorded wavefields (with multiples) and determining the subsurface velocity or acoustic impedance model that produces them, thus reversing the conventional approach of removing multiples before inversion.
2Adaptability or versatility
If full wavefield inversion is applied to data containing surface-related multiples, then the full seismic record is utilized, but accurate modeling of surface-related multiples is required which is extremely sensitive to errors
Solution Approach 1:
The patent applies preliminary action by performing a first FWI stage with free-surface boundary conditions to generate an initial subsurface model before the multiple removal step. This preliminary model is then used in the second FWI stage with absorbing boundary conditions, allowing the system to benefit from both multiple-containing and multiple-free data without requiring perfect multiple modeling accuracy.
Solution Approach 2:
The patent segments the FWI process into two distinct stages: a first stage using free-surface boundary conditions to handle multiple reflections, and a second stage using absorbing boundary conditions to process multiple-free data. This segmentation allows each stage to optimize for its specific conditions, reducing the sensitivity to modeling errors in the overall process.
3Object-generated harmful factors
If absorbing boundary condition is used in FWI, then multiple-free synthetic data are generated, but surface-related multiples cannot be modeled
Solution Approach 1:
The patent segments the boundary condition application across two FWI stages: the first stage uses free-surface boundary conditions to model and utilize surface-related multiples, while the second stage uses absorbing boundary conditions to generate multiple-free synthetic data. This temporal segmentation allows the system to achieve both multiple modeling capability and multiple-free data generation without compromise.
Solution Approach 2:
The patent performs preliminary FWI with free-surface boundary conditions to generate an initial subsurface model that accurately represents the multiple-containing data. This preliminary model then serves as the foundation for the second FWI stage with absorbing boundary conditions, allowing the system to leverage the multiple information captured in the preliminary stage while producing multiple-free output in the second stage.
Data Source
AI summary
A multi-stage FWI workflow uses multiple-contaminated FWI models to predict surface-related multiples. A method embodying the present technological advancement, can include: using data with free surface multiples as input into FWI; generating a subsurface model by performing FWI with the free-surface boundary condition imposed on top of the subsurface model; using inverted model from FWI to predict multiples; removing predicted multiples from the measured data; using the multiple-free data as input into FWI with absorbing boundary conditions imposed on top of the subsurface model; and preparing a multiple free data set for use in conventional seismic data processing.