4D Regularization for Seismic Wavefield De-aliasing
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Solution Overview
Problem
Current seismic data processing techniques face challenges in de-aliasing full wavefields, particularly in arid regions with complex near-surface heterogeneities, leading to strong noise contamination and reduced signal-to-noise ratios due to inadequate spatial sampling.
Innovation Solution
A four-dimensional (4D) anti-leakage anti-aliasing regularization algorithm is applied in successive steps, restricting computations to significant spatial dimensions, involving 4D regularization, F-Kx-Ky anti-alias dip reject filters, and 3D regularization to achieve de-aliasing of the full wavefield, reducing computational and geophysical complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional 3D wide-azimuth seismic surveys are used with standard shot and geophone spacing, then data acquisition is feasible, but the seismic data becomes severely aliased due to inadequate spatial sampling of low-velocity surface waves
Solution Approach 1:
The patent transitions from conventional 3D seismic surveying to 4D seismic surveying by adding the receiver x dimension to the traditional three dimensions (shot x, shot y, receiver y). This fourth dimension enables proper spatial sampling of surface waves without requiring excessive spacing reductions in the original dimensions, thereby resolving the aliasing problem while maintaining survey feasibility
Solution Approach 2:
The patent changes the sampling parameters by introducing a fourth spatial dimension (receiver x) with specific spacing relationships (Δreceiver x = Δshot x/2 = Δreceiver y/2). This parameter change allows the system to capture low-velocity surface waves adequately without making the survey configuration overly complex
2Measurement precision
If shot and geophone spacing is reduced to improve spatial sampling, then aliasing of surface waves is reduced, but the computational complexity and data processing burden increase significantly
Solution Approach 1:
The patent segments the 4D seismic data processing into distinct sequential steps: 4D regularization to achieve uniform sampling, F-K filtering to remove surface waves, and decimation to reduce data volume. This segmentation allows each processing stage to address specific aspects of the problem efficiently, reducing overall computational complexity compared to processing the full aliased dataset
Solution Approach 2:
By utilizing the fourth dimension (receiver x) for sampling, the patent achieves proper spatial coverage without requiring excessive reduction in the original dimensions. The regularized sampling in 4D space (with output spacing relationships Δoffset x=Δoffset y=Δshot x) enables effective surface wave suppression while maintaining manageable data volumes for computational processing
3Productivity
If conventional processing methods are used in areas with strong elastic property variation, then processing speed is maintained, but the signal-to-noise ratio deteriorates due to strong near-surface noise
Solution Approach 1:
The patent applies 4D regularization as a preliminary step before conventional processing, establishing uniformly sampled data in four spatial dimensions. This preliminary action ensures that subsequent processing steps operate on properly sampled data, preventing noise amplification and improving signal-to-noise ratio while maintaining processing efficiency
Solution Approach 2:
The patent replaces conventional mechanical filtering approaches with a 4D regularization algorithm that uses computational methods to achieve noise suppression. This substitution allows for more sophisticated noise handling in complex near-surface conditions while maintaining processing speed through efficient algorithmic implementation
Data Source
AI summary
Disclosed are methods, systems, and computer-readable medium for a full seismic wavefield de-aliasing workflow. To achieve the de-aliasing, the workflow employs a four-dimension (4D) anti-leakage anti-aliasing regularization algorithm. The workflow involves application of successive de-aliasing steps while restricting computations only to the significant spatial dimensions. In areas of strong elastic property variation in the near-surface, the benefit of de-aliasing the full wavefield is both significant and demonstrable. In addition to achieving de-aliased sampling of the full wavefield, the workflow reduces the complexity of both the computational and geophysical aspects of the problem of de-aliasing full wavefields.