Wavelet Intercept Seismic Attribute Noise Stability
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Solution Overview
Problem
Existing seismic data analysis methods, particularly those using the Hölder exponent, are unstable and sensitive to noise, which can lead to inaccurate representation of subsurface structures and stratigraphy.
Innovation Solution
The method employs wavelet transforms, specifically using the Morlet wavelet, to calculate an intercept attribute from seismic trace data, which is more stable and less affected by noise, allowing for improved imaging and geological interpretation by graphing values relative to time or depth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the Hölder exponent is used for seismic trace analysis, then the analysis can be performed, but the results are unstable and sensitive to noise
Solution Approach 1:
The patent changes the mathematical parameter from Hölder exponent to wavelet transform intercept. This parameter transformation fundamentally alters how seismic trace characteristics are measured, moving from a scale-based exponent calculation to a wavelet coefficient intercept measurement. The wavelet intercept parameter is inherently more robust to noise because it represents the logarithmic amplitude at a specific scale, which is less susceptible to high-frequency noise contamination compared to the Hölder exponent calculation.
Solution Approach 2:
The patent replaces the mathematical mechanism of Hölder exponent calculation with wavelet transform-based intercept calculation. This substitution introduces a different computational approach that uses wavelet decomposition and logarithmic amplitude measurement instead of the previous exponent-based method. The wavelet transform mechanism provides better noise filtering properties and produces more stable results across varying seismic conditions.
2Measurement precision
If detailed changes in seismic data are detected, then geological interpretation accuracy improves, but the analysis becomes more sensitive to noise
Solution Approach 1:
The patent introduces a logarithmic amplitude dimension through the wavelet transform intercept measurement. By measuring the logarithm of the wavelet coefficient amplitude at different scales, the method creates an additional analytical dimension that captures detailed seismic characteristics while the logarithmic transformation inherently compresses the dynamic range, reducing the impact of noise on the measurement precision.
Data Source
AI summary
A wavelet-based method for improving the quality of seismic data utilizing the intercept determined by applying least squares regression to the wavelet transform of a seismic trace. The intercept is calculated for every time point of the wavelet transform for each seismic trace. The intercepts are then plotted versus time or depth. These plots are used in place of seismic traces themselves to create two dimensional and three dimensional seismic section images. In one embodiment, the real and imaginary portions of the selected wavelet transform are weighted to generate a finer representation of the intercept. In another embodiment, a minimum amplitude value is utilized to establish a noise floor, thus stabilizing the regression calculation. In yet another embodiment, a taper of the amplitude is applied to wavelet enhance the resolving power of the wavelet.