Seismic Image Processing Using Wavelet Convolution
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Solution Overview
Problem
Existing seismic image processing methods struggle to provide a clear and interpretable representation of subsurface structures, especially in areas with noise, limiting the ability to distinguish geological features effectively.
Innovation Solution
A method that reprocesses synthesized seismic images by combining them with original seismic images using signed amplitudes and applying spatial convolution with a wavelet kernel, enhancing the structural information and making the images more realistic and easier to interpret.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If synthesized images are generated by accumulation along estimated horizons, then structural information is enhanced, but the images become less clear and lose physical information
Solution Approach 1:
The patent combines the synthesized image (containing structural information from accumulation along horizons) with the original seismic image (containing physical amplitude information) by adding a scaled version of the synthesized image to the original image. This merging operation preserves both structural enhancement and physical information, resolving the contradiction between gaining structural information and maintaining image clarity.
2Loss of information
If synthesized images are processed to provide structural information, then geological feature interpretation is improved, but noise reduction is insufficient
Solution Approach 1:
The patent applies local quality enhancement by using the gradient-based horizon estimation to identify local structural features and selectively enhancing those regions. The accumulation process focuses on local continuity along estimated horizons, providing targeted structural information while the combination with the original image preserves local noise characteristics for further processing.
3Productivity
If automatic horizon estimation is performed by gradient propagation, then processing efficiency is improved, but accuracy in noisy areas deteriorates
Solution Approach 1:
The patent implements feedback by iteratively refining horizon estimates using the accumulated structural information. The initial gradient propagation provides a first-order estimate, which is then used to guide subsequent processing steps that incorporate feedback from the accumulated horizons to improve accuracy in noisy areas while maintaining processing efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method enhances the readability and interpretability of seismic images by adding structural information, improving the visualization of geological structures and reducing noise, making it easier for geophysicists to analyze and identify subsurface features.
Implementation Method 1
The seismic representation may be seen as a seismic image enhanced by the addition of structural information coming from the synthesized image
Data Source
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AI summary
The processing comprises an analysis of a seismic image to estimate seismic horizons in an area of the subsurface and the calculation of an accumulation value associated with each pixel of the seismic image by accumulation along a set of estimated seismic horizons to form a synthesized image composed of accumulation values. This synthesized image is transformed to obtain a seismic representation in which signed amplitudes are allocated to the pixels of the synthesized image. The transformation comprises a convolution with a wavelet or another convolution kernel.