Seismic Moveout Correction Using Wavefront Kinematic Analysis
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Solution Overview
Problem
Existing seismic imaging methods, such as those using hyperbolic moveout corrections, inaccurately reflect subterranean structures, leading to loss of information and reduced signal/noise ratios in subsurface imaging.
Innovation Solution
The application of homeomorphic imaging principles for complex kinematic analysis, which adaptively computes moveout corrections based on wavefront parameters like emergence angle and curvature, to align and stack seismic traces, enhancing image accuracy and detail by accounting for velocity changes and layer curvature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If homeomorphic imaging with complex kinematic analysis is used, then imaging accuracy and detail are improved, but computational complexity increases
Solution Approach 1:
The patent transforms the seismic imaging problem by changing the parameter space from traditional hyperbolic moveout parameters to wavefront parameters (incident angle, radius of curvature). This parameter transformation enables accurate representation of velocity changes and curvature effects while providing a systematic framework for computation.
Solution Approach 2:
The patent segments the complex imaging problem into distinct computational stages: (1) computing moveout corrections using wavefront parameters, (2) sorting traces into sub-gathers based on these parameters, (3) stacking within sub-gathers, and (4) combining results. This segmentation makes the computationally intensive task manageable and implementable.
2Ease of manufacture
If hyperbolic moveout correction is used, then computational simplicity is maintained, but imaging accuracy deteriorates due to loss of information and stretching effects
Solution Approach 1:
The patent replaces the traditional hyperbolic moveout parameterization with wavefront parameters (incident angle and radius of curvature). This parameter change allows the moveout correction to accurately reflect actual subsurface characteristics including velocity variations and curvature, eliminating the information loss and stretching artifacts inherent in hyperbolic approximation.
Solution Approach 2:
The patent introduces dynamic adaptability by computing moveout corrections based on local wavefront characteristics rather than applying a fixed hyperbolic formula. The method adapts to local velocity changes and curvature variations throughout the subsurface, providing accurate imaging across heterogeneous media while maintaining a systematic computational approach.
Data Source
AI summary
A computer-implemented method for processing data includes receiving a collection of traces corresponding to signals received over time at multiple locations due to reflection of seismic waves from subsurface structures. A measure of correlation among the traces as is computed a function of a set of wavefront parameters, which determine respective moveout corrections to be applied in aligning the traces. A matrix having at least three dimensions is generated, wherein the elements of the matrix include the computed measure of the correlation. Using the matrix, values of the wavefront parameters are identified automatically or interactively along the time axis or along selected horizons to maximize the measure of the correlation, and a seismic image of the subsurface structures is generated by aligning and integrating the traces using the moveout corrections that are determined by the identified values of the wavefront parameters.