Post-Stack Seismic Diffraction Imaging via F-K Filter Multiplication
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current seismic imaging techniques face challenges in achieving high spatial resolution and computational efficiency, particularly in identifying geologic features like faults and fractures, due to limitations in separating diffraction and reflection signals and the high computational cost of traditional methods.
Innovation Solution
The implementation of post-stack edge detection using a multiplication imaging condition with frequency-wavenumber (F-K) filters to generate negative-dip and positive-dip structure images, allowing for diffraction-enhanced seismic imaging that is computationally less intensive and provides higher resolution without separating reflection and diffraction portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-stack imaging techniques are used to separate diffraction and reflection signals, then measurement precision of geologic features is improved, but computation time and cost increase significantly
Solution Approach 1:
The patent segments the imaging process by applying F-K filters to separate negative-dip and positive-dip structure images from the post-stack seismic data. This segmentation allows the multiplication imaging condition to be applied selectively to enhance diffraction features while maintaining computational efficiency compared to full pre-stack imaging.
Solution Approach 2:
The patent extracts diffraction-enhanced images by applying the multiplication imaging condition to the separated negative-dip and positive-dip structure images. This extraction process isolates the diffraction signals from the post-stack data without requiring the computationally intensive pre-stack separation process, thereby reducing computation time while maintaining spatial resolution.
2Reliability
If traditional seismic imaging methods are used to identify geologic features, then reliability of feature identification is improved, but device complexity and computational cost increase
Solution Approach 1:
The patent introduces F-K filters as an intermediary tool to process post-stack seismic data and generate negative-dip and positive-dip structure images. These filtered images serve as intermediaries that facilitate the application of the multiplication imaging condition, enabling reliable diffraction feature identification with reduced processing complexity compared to traditional pre-stack methods.
Solution Approach 2:
The patent changes the processing parameters by working with post-stack seismic data instead of pre-stack data. By applying F-K filtering and the multiplication imaging condition to post-stack data, the method achieves reliable geologic feature identification with simpler processing workflows and reduced computational requirements.
3Productivity
If post-stack imaging is used to reduce computational cost, then productivity is improved, but measurement precision of diffraction features deteriorates
Solution Approach 1:
The patent applies parameter changes by introducing the multiplication imaging condition in the post-stack domain. This parameter change allows the method to achieve diffraction-enhanced spatial resolution from post-stack data, maintaining measurement precision while benefiting from the computational efficiency of post-stack processing.
Solution Approach 2:
The patent substitutes the mechanical separation process of pre-stack imaging with a post-stack processing approach using F-K filters and multiplication imaging condition. This substitution replaces the computationally intensive pre-stack separation mechanism with a more efficient post-stack filtering and multiplication process, maintaining spatial resolution while improving productivity.
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
This approach enhances the spatial resolution of seismic images, enabling accurate identification of geologic features with reduced computational time and cost, while maintaining high-fidelity imaging comparable to pre-stack methods.
Implementation Method 1
applying a frequency-wavenumber (F-K) filter to the data volume to extract a negative-dip structure image and applying the frequency-wavenumber (F-K) filter to the data volume to extract a positive-dip structure image
Implementation Method 2
multiplying the positive-dip structure image with the negative-dip structure image to generate a diffraction-enhanced seismic image
Implementation Method 3
The seismic wave travels into the ground, is reflected by subsurface formations, and returns to the surface where it is recorded by sensors called geophones
Implementation Method 4
diffraction-enhanced seismic imaging that is computationally less intensive and provides higher resolution
Data Source
AI summary
A system for seismic imaging of a subterranean geological formation, the system includes a receiver configured to obtain seismic data comprising a data volume representing a post-stacked image. The system includes a filtering module configured to: apply frequency-wavenumber (F-K) filter to the data volume extract a negative-dip structure image and apply the frequency-wavenumber (F-K) filter to the data volume extract a positive-dip structure image. The system includes a diffraction rendering module configured to: multiply the positive-dip structure image with the negative-dip structure image and generate a diffraction-enhanced seismic image representing a geological formation of the data volume.