Seismic Ghost Filter Generation Using Frequency-Domain Bootstrap
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Solution Overview
Problem
Current methods for removing receiver ghosts in marine seismic data acquisition are limited by requiring constant receiver depths and two-dimensional data handling, leading to unsuitable results due to sparse cross-line sampling and difficulties in calibrating particle velocity data with low signal-to-noise ratios.
Innovation Solution
A method that generates an optimized receiver-based ghost filter by transforming recorded and mirror data from the time-space domain to the frequency-space domain, adding a phase coefficient to correct timing differences, and iteratively minimizing ghost delay time using a least squares technique to produce a ghost-free seismic data set.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FK domain methods are used for ghost removal, then ghost attenuation is achieved, but the method is limited to constant depth receivers and two-dimensional data
Solution Approach 1:
The patent transforms the ghost removal approach from the FK domain to the frequency-domain, enabling the method to handle variable-depth receivers. This parameter change in the mathematical domain allows the system to accommodate changing receiver depths while maintaining ghost removal effectiveness through frequency-domain filtering techniques.
Solution Approach 2:
The patent extends the method from two-dimensional constant-depth processing to three-dimensional variable-depth processing by incorporating receiver depth as an additional dimension. This allows the system to process marine seismic data with receivers at varying depths along the streamer, overcoming the limitations of traditional FK domain methods.
2Reliability
If particle velocity data is used for ghost attenuation, then ghost removal is achieved, but calibration difficulties arise due to low signal-to-noise ratio
Solution Approach 1:
The patent introduces pressure data as an intermediary to overcome the low signal-to-noise ratio problem in particle velocity measurements. By using pressure data from hydrophones as a reference and combining it with velocity data through a combined wavefield approach, the system achieves accurate ghost attenuation without being limited by the poor quality of velocity measurements alone.
Solution Approach 2:
The patent creates a composite wavefield approach by combining pressure and velocity data into a unified processing framework. This composite approach leverages the strengths of both measurement types, using pressure data's high signal-to-noise ratio to compensate for velocity data's limitations while maintaining the ghost attenuation benefits of velocity-based methods.
3Manufacturing precision
If dense sampling is required for accurate ghost removal, then processing accuracy improves, but data acquisition complexity and cost increase
Solution Approach 1:
The patent enables the system to self-correct for variable receiver depths and spacing through the frequency-domain method, eliminating the need for dense uniform sampling. The algorithm automatically adapts to the actual receiver configuration, using the available data to compute accurate ghost filters without requiring oversampling or specialized geometric arrangements.
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 removes receiver ghosts without requiring dense sampling or accurate receiver positioning, enhancing frequency response and signal-to-noise ratio, resulting in improved seismic imaging with broader frequency spectra and reduced noise.
Implementation Method 1
transforming the recorded data and the mirror data from a time-space domain to a frequency-space domain
Implementation Method 2
the up-going acoustic waves reflected from subsurface reflectors are first recorded by the receivers. Next, the acoustic waves continue to propagate to the surface where they are reflected back down and are recorded again by the receivers as ghosts. The reflectivity at the free surface is close to negative one
Data Source
AI summary
Methods and systems for optimized receiver-based ghost filter generation are described. The optimized ghost filter self-determines its parameters based on an iterative calculation of recorded data transformed from a time-space domain to a Tau-P domain. An initial ghost filter prediction is made based on generating mirror data from the recorded data and using a least squares technique during a premigration stage.