Azimuth Correction for 3D Seismic Trace Reconstruction
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Solution Overview
Problem
Current methods for 3D surface-related multiple prediction in marine seismic surveys face challenges due to under-sampling and positioning limitations, leading to incomplete data sets and inaccurate reconstruction of desired traces, which affects noise attenuation in seismic data processing.
Innovation Solution
The method employs azimuth correction to reconstruct desired traces by calculating and applying an azimuth correction to the best fitting trace, ensuring accurate data reconstruction for 3D surface-related multiple prediction, independent of wavefield propagation velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data reconstruction methods are used in 3D surface-related multiple prediction, then the process can be completed with existing seismic data, but the accuracy of trace reconstruction is insufficient due to under-sampling and positioning limitations
Solution Approach 1:
The patent applies azimuth correction by calculating and applying an azimuth correction factor to the best fitting trace. This parameter change transforms the trace from the original azimuth to the desired azimuth, effectively correcting the directional misalignment caused by under-sampling and positioning errors in marine seismic surveys.
Solution Approach 2:
The patent replaces conventional mechanical/physical data reconstruction approaches with a computational method that uses azimuth correction calculations. Instead of relying on geometric or physical interpolation, the system uses mathematical transformations to correct the azimuth angle and reconstruct accurate traces from incomplete data.
2Measurement precision
If azimuth correction is applied to reconstruct desired traces, then the accuracy of 3D surface-related multiple prediction is enhanced, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by first determining the best fitting trace and calculating the azimuth correction factor before applying the correction. This preliminary calculation of the correction factor based on the azimuth difference between the best fitting trace and desired trace simplifies the subsequent application process and reduces overall computational complexity.
Solution Approach 2:
The patent applies local quality by calculating and applying azimuth correction specific to each trace based on its individual azimuth difference from the desired azimuth. Rather than applying a global correction, the system tailors the correction factor to each specific trace, improving accuracy while managing computational load through localized processing.
3Productivity
If data reconstruction is performed without azimuth correction, then the processing time is reduced, but the noise attenuation performance deteriorates
Solution Approach 1:
The patent changes the parameter of trace azimuth by calculating and applying an azimuth correction factor. This parameter transformation ensures that the reconstructed traces have the correct azimuth orientation, which is essential for accurate multiple prediction and noise attenuation, thereby improving reliability without significantly impacting processing speed.
Data Source
AI summary
A best fitting trace in seismic data is determined for a desired trace to be reconstructed. An azimuth correction is calculated for the azimuth difference between the best fitting trace and the desired trace. The azimuth correction is applied to the best fitting trace to reconstruct the desired trace for 3D surface-related multiple prediction.