Variable-Depth Streamer Demultiple via Wavefield Separation
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Solution Overview
Problem
Existing seismic data processing methods are ineffective in removing multiples, particularly in shallow water environments or at near offsets, due to limitations in moveout discrimination and adaptive subtraction requirements, especially when data is not well spatially sampled.
Innovation Solution
The method involves obtaining up-going and down-going wavefields at a predetermined datum using de-ghosting techniques and identifying multiples for effective removal, allowing for the generation of a geological formation image under the seabed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radon demultiple is used to remove multiples, then multiple energy can be identified and removed, but the method is ineffective in shallow water environments or at near offsets where moveout discrimination is not apparent
Solution Approach 1:
The patent transforms the data from time-domain to frequency-wavenumber (f-k) domain, changing the parameter space in which multiples are identified. In the f-k domain, multiples are separated based on their wavenumber characteristics rather than moveout, making the method effective in shallow water and near offset regions where traditional moveout-based methods fail.
Solution Approach 2:
The patent replaces the mechanical moveout correction and parabolic radon modeling approach with a spectral filtering approach in the frequency-wavenumber domain. This substitution allows for more flexible and accurate multiple identification by exploiting the spectral characteristics of multiples rather than relying on kinematic moveout differences.
2Measurement precision
If surface-related multiple elimination (SRME) is used, then a multiple model with correct kinematic timing can be produced, but the method is difficult to use when input data is not sufficiently well spatially sampled and requires adaptive subtraction
Solution Approach 1:
The patent replaces the convolution-based SRME approach with a spectral filtering method in the frequency-wavenumber domain. This substitution eliminates the need for dense spatial sampling and adaptive subtraction by directly filtering multiples based on their spectral characteristics, simplifying the processing workflow while maintaining accuracy.
Solution Approach 2:
The patent changes the processing domain from time-space to frequency-wavenumber, allowing multiples to be identified and removed based on spectral parameters rather than spatial sampling density. This parameter transformation reduces the stringent spatial sampling requirements of SRME.
3Ease of manufacture
If deconvolution is applied, then a prediction operator can be built to remove multiples, but the method is often only suitable for shallow water and for simple structures
Solution Approach 1:
The patent replaces the autocorrelation-based deconvolution approach with a spectral filtering method in the frequency-wavenumber domain. This substitution provides a more robust framework that can handle complex subsurface structures and deep water environments by exploiting the directional characteristics of multiples in the spectral domain rather than relying on simple autocorrelation patterns.
Data Source
AI summary
Methods and systems for processing data acquired using a variable-depth streamer, obtain up-going and down-going wavefields at a predetermined datum, and use them to identify multiples included in the up-going wavefield. An image of a geological formation under the seabed is then generated using the data from which the multiples have been removed, and/or the multiples.