Wavefield Separation Using Kirchhoff Datuming for Dual-Sensor Data
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Solution Overview
Problem
Conventional methods for wavefield separation in dual-sensor data face challenges in efficiently correcting for spatial aliasing, particularly in marine seismic surveys with asymmetrical spatial sampling, which can lead to data aliasing and require seismic trace interpolation.
Innovation Solution
A method involving weighted integral operators is applied to dual-sensor data to extrapolate and separate wavefields into up-going and down-going components, allowing for wavefield separation in the time-space domain without the need for seismic trace interpolation, accommodating irregular receiver separations and heterogeneous earth models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods are used for wavefield separation in dual-sensor data, then the processing can be performed with standard algorithms, but spatial aliasing occurs and seismic trace interpolation is required
Solution Approach 1:
The patent applies a weighted integral operator (Kirchhoff-type datuming) to extrapolate the dual-sensor data to a first position above the acquisition surface before performing wavefield separation. This preliminary extrapolation step corrects for spatial aliasing artifacts by redistributing the aliased energy in the correct spatial locations, allowing accurate separation of up-going and down-going wavefields without requiring subsequent trace interpolation
Solution Approach 2:
The patent introduces an intermediate extrapolated dataset at a first position above the acquisition surface. This intermediate dataset serves as a mediator between the original aliased data and the final separated wavefields. By performing the separation operation on this intermediate extrapolated data rather than directly on the original data, the method eliminates spatial aliasing effects while maintaining accuracy in the final wavefield separation
2Object-affected harmful factors
If seismic trace interpolation is used to correct spatial aliasing, then aliasing can be reduced, but the processing complexity and time increase
Solution Approach 1:
The patent replaces the mechanical interpolation process with a mathematical extrapolation operation using a weighted integral operator. Instead of interpolating traces to correct aliasing, the method extrapolates the entire dual-sensor dataset to a first position above the acquisition surface, which inherently corrects spatial aliasing. This substitution of the correction mechanism eliminates the need for time-consuming interpolation while achieving the same aliasing correction goal more efficiently
3Ease of operation
If standard wavefield separation methods are applied, then the process is straightforward, but irregular receiver separations and heterogeneous earth models cannot be adequately handled
Solution Approach 1:
The patent changes the spatial parameter by extrapolating the data to a first position above the acquisition surface before performing separation. This parameter transformation (changing from original sensor positions to elevated positions) allows the method to handle irregular receiver separations and heterogeneous earth models effectively. The extrapolation to an elevated position creates a more uniform sampling geometry that accommodates irregularities in the original receiver layout while maintaining processing simplicity through the standardized integral operator approach
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 corrects for spatial aliasing and improves the accuracy of wavefield separation, enhancing the ability to image subsurface structures and increase the likelihood of identifying petroleum accumulations by providing more precise seismic data processing and display.
Implementation Method 1
A first weighted integral operator (e.g., a Kirchhoff-type datuming operator) is applied to dual-sensor data to extrapolate the dual-sensor data to a first position above an acquisition surface
Implementation Method 2
A second weighted integral operator (e.g., a Kirchhoff-type migration operator) is applied to the extrapolated data to extrapolate the extrapolated data to a second position, generating wavefield separated data
Data Source
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AI summary
A first weighted integral operator is applied to dual-sensor data to extrapolate the dual-sensor data to a first position above an acquisition surface, generating extrapolated data. A second weighted integral operator is applied to the extrapolated data to extrapolate the extrapolated data to a second position, generating wavefield separated data. One of the integral operators is applied to a scaled combination of the dual sensor data.