Quaternion Vector Denoising for Multicomponent Seismic Data
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Solution Overview
Problem
Traditional filtering methods for multicomponent seismic data often damage vector features and fail to effectively protect seismic data signals, especially when processing transverse wave data, due to their scalar field processing approach and inability to handle complex noise effectively.
Innovation Solution
A vector denoising method that decomposes multicomponent seismic data into small datasets, performs quaternary Fourier transformation, extracts and filters frequency slices using Cadzow filtering in the quaternion Hankel matrix, and applies inverse quaternary Fourier transformation to retain vector features and suppress noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional filtering methods (f-x domain prediction filtering, median filtering, SVD, F-K denoising) are applied to multicomponent seismic data, then denoising effect is improved, but vector features are damaged
Solution Approach 1:
The patent segments the multicomponent seismic data into individual components (vertical and horizontal components) for separate processing, while maintaining their vector relationship through the quaternion framework. This allows applying filtering operations to each component independently without destroying the overall vector structure, resolving the contradiction between effective denoising and vector feature preservation.
Solution Approach 2:
The patent introduces quaternion numbers as an intermediary mathematical tool to represent and process multicomponent seismic data. The quaternion framework serves as a mediator that maintains the vector relationships between components while enabling application of scalar filtering operations, thus achieving both denoising and vector feature preservation simultaneously.
2Ease of operation
If scalar field processing methods are used for each component separately, then processing simplicity is improved, but transverse wave data denoising effect deteriorates
Solution Approach 1:
The patent creates a universal processing framework using quaternions that can handle both longitudinal and transverse wave data through a single mathematical approach. The quaternion representation unifies the treatment of different wave types, allowing the same filtering methodology to effectively process both components without requiring separate specialized treatments, thus improving transverse wave denoising while maintaining processing simplicity.
Data Source
AI summary
The present application provides a vector denoising method and a vector denoising device for multicomponent seismic data, which relate to the field of seismic data processing technologies. The vector denoising method for multicomponent seismic data includes: decomposing multicomponent seismic gather data to obtain a plurality of small multicomponent seismic data; obtaining quaternary frequency domain seismic data by performing a quaternary Fourier transformation according to each of the plurality of small multicomponent seismic data; extracting frequency slices from the quaternary frequency domain seismic data in a quaternary frequency domain, and filtering the frequency slices by using a Cadzow filtering method to obtain filtered quaternary frequency domain seismic data; and performing an inverse quaternary Fourier transformation on the filtered quaternary frequency domain seismic data to obtain filtered seismic data of each component.