Constrained Polarization Filtering for Seismic Surface Wave Noise
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current seismic prospecting methods face challenges in accurately filtering out surface waves, known as ground roll, which can mask weaker reflected body waves, leading to incomplete imaging of subsurface formations and reservoir property analyses due to the lack of distinct characteristics between surface waves and body waves.
Innovation Solution
A method involving constrained polarization filtering of multi-component seismic data using time-frequency analysis to identify and remove surface wave noise by employing characteristics such as rise angle, inverse ellipticity ratio, and polarization direction, while minimizing the impact on body wave signals, and iteratively refining the filtering process to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a low cut filter is used to eliminate surface waves, then surface wave amplitudes are reduced, but body wave amplitudes are also reduced leading to loss of low frequency information
Solution Approach 1:
The patent applies polarization filtering by analyzing the polarization characteristics (rise angle, inverse ellipticity ratio, polarization direction) of seismic waves to distinguish surface waves from body waves. This parameter-based differentiation allows selective attenuation of surface waves while preserving body waves across the full frequency spectrum, avoiding the information loss inherent in frequency-based low cut filtering.
2Object-affected harmful factors
If velocity filtering or FK filtering is used to remove ground roll, then surface waves are attenuated, but the method requires sufficiently short receiver spacing to avoid aliasing
Solution Approach 1:
The patent transforms the filtering approach from spatial domain (velocity filtering requiring specific receiver spacing) to polarization domain. By analyzing polarization attributes in the time-frequency domain, the method can effectively remove surface waves regardless of receiver spacing, eliminating the aliasing problem that plagues velocity and FK filtering methods.
3Object-affected harmful factors
If polarization filtering is applied without constraints, then surface waves are removed, but body wave signals may also be affected
Solution Approach 1:
The patent applies constrained polarization filtering where filtering is selectively applied only in time-frequency regions where surface waves are dominant. By using thresholds on polarization attributes and time-frequency boundaries, the method partially applies filtering action only where needed, preserving body wave signals in regions where they dominate while still effectively removing surface wave noise.
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 effectively isolates and removes surface wave noise while preserving body wave signals, leading to improved imaging of subsurface structures and more accurate reservoir analysis by employing a combination of polarization and time-frequency criteria to distinguish between surface waves and body waves.
Implementation Method 1
employing a combination of polarization and time-frequency criteria to distinguish between surface waves and body waves
Data Source
AI summary
An exemplary method for filtering multi-component seismic data is provided. One or more characteristics of the seismic data corresponding to a relative manifestation of surface wave noise on the different components, such as polarization attributes, are identified. A time-frequency boundary in the seismic data is also identified in the time-frequency transform domain, the time-frequency boundary delineating portions of the seismic data estimated to contain surface wave noise (302). Finally, filtered seismic data are created (306) by removing portions of the seismic data that correspond to the identified characteristics of surface waves and that are within the time-frequency boundary (303).