Seismic Image Gather Computation Using Segmented Depth Migration
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Solution Overview
Problem
Current seismic data processing methods, particularly in the computation of common image gathers (CIGs) in the angle domain, are computationally expensive and require significant memory, especially for 3D cases, and often lack the resolution and azimuth information needed for accurate subsurface analysis.
Innovation Solution
A process involving depth migration techniques using cross-correlation and gradient-based imaging conditions to generate CIGs, with amplitude correction and illumination compensation, allowing for efficient computation and storage of seismic data, applicable to both isotropic and anisotropic media.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional depth migration techniques are used to compute common image gathers (CIGs) in the angle domain, then subsurface imaging is achieved, but computational cost and memory requirements become excessively high, especially for 3D cases
Solution Approach 1:
The patent segments the CIG computation into two separate images: one computed using cross-correlation imaging condition and another using gradient-based imaging condition. These segmented images are then combined to form the final CIGs, allowing efficient computation while maintaining imaging quality in both isotropic and anisotropic media
Solution Approach 2:
The patent changes the imaging condition parameter from a single conventional approach to a dual-approach system that switches between cross-correlation and gradient-based conditions. This parameter change enables the system to adapt to different media types (isotropic vs. anisotropic) and reduces computational burden while preserving subsurface imaging accuracy
2Measurement precision
If conventional depth migration techniques are used to compute common image gathers (CIGs) in the angle domain, then subsurface imaging is achieved, but memory requirements become excessively high, especially for 3D cases
Solution Approach 1:
The patent segments the CIG computation into two separate images that are computed and stored independently. By processing and combining these segmented results rather than storing complete CIGs during computation, the system significantly reduces memory requirements while maintaining imaging quality
Solution Approach 2:
The patent extracts only the essential image information needed for final CIG formation by computing separate cross-correlation and gradient-based images. This extraction approach avoids storing redundant intermediate data structures, thereby reducing memory consumption while preserving the necessary subsurface imaging quality
3Measurement precision
If conventional migration techniques are used, then CIGs can be generated, but they lack the resolution and azimuth information needed for accurate subsurface analysis
Solution Approach 1:
The patent performs preliminary computation of two distinct images (cross-correlation and gradient-based) before combining them to form the final CIGs. This preliminary action ensures that azimuth information and high-resolution details are captured in each separate image computation, preventing information loss that would occur in conventional single-step migration
Solution Approach 2:
The patent changes the imaging approach to include both cross-correlation and gradient-based conditions, which preserves azimuth information and enhances resolution. This parameter change allows the system to maintain accurate subsurface analysis capabilities by capturing directional information that conventional techniques would lose
Data Source
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AI summary
The process of obtaining seismic data includes deploying a seismic energy source and seismic receivers, actuating the source, and detecting seismic energy resulting therefrom at the receivers. The process further includes digitally sampling seismic energy detected at the receivers indexed with respect to time to form a plurality of traces and sorting the traces to form a plurality of shot gathers.