3D Seafloor Reflectivity Reconstruction for Shallow Water Multiple Elimination
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Solution Overview
Problem
Existing marine seismic exploration systems face challenges in accurately modeling and eliminating shallow water multiples, which are difficult to predict due to move-out issues and geometry limitations, especially in shallow seafloor conditions where travel distances are short.
Innovation Solution
A method and system for reconstructing the seafloor reflectivity image using seismic data, estimating 1D prediction deconvolution operators, migrating these operators to create 3D prediction deconvolution operators, and using the wave equation to determine and subtract surface multiples from seismic data, enabling improved imaging of shallow water environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional seismic data processing is used, then standard imaging is achieved, but shallow water multiples cannot be accurately predicted or eliminated
Solution Approach 1:
The patent changes the fundamental parameters of seismic data processing by transitioning from conventional 2D convolution operations to 3D wave equation modeling. This involves changing the mathematical operators, the dimensionality of the processing space, and the physical assumptions underlying the multiple prediction process, thereby achieving accurate multiple prediction in shallow water conditions where conventional methods fail.
Solution Approach 2:
The patent introduces a third dimension to the processing by using full 3D wave equation modeling instead of 2D convolution. The 3D predictive deconvolution operators are applied in addition to the conventional 2D migration operators, creating a three-dimensional processing framework that accurately captures the complex wave propagation paths in shallow water environments.
2Ease of manufacture
If 2D convolution operations are used for multiple prediction, then processing is simpler, but prediction fails for short offset lengths in shallow seafloor conditions
Solution Approach 1:
The patent performs preliminary 3D predictive deconvolution to estimate sea floor reflectivities before the main imaging process. This preliminary action of reconstructing the sea floor model using 3D wave equation modeling provides accurate multiple prediction capabilities that are then used in subsequent processing steps, ensuring both accuracy and computational efficiency.
Solution Approach 2:
The patent replaces the mechanical convolution operation with a wave equation-based modeling approach. Instead of using simple 2D convolution that assumes linear superposition, the patent uses the full 3D wave equation to model wave propagation, thereby substituting a more physically accurate but computationally intensive mechanism that works for short offsets.
3Productivity
If primary reflections are used directly for imaging, then standard imaging workflow is maintained, but imaging quality degrades in shallow water where primary reflections are not directly usable
Solution Approach 1:
The patent introduces 3D predictive deconvolution operators as an intermediary step between the raw seismic data and the final image. These operators, derived from 3D wave equation modeling of sea floor reflectivities, act as a mediator that corrects the data before standard imaging workflows are applied, thereby maintaining workflow efficiency while improving image accuracy in shallow water conditions.
Solution Approach 2:
The patent segments the imaging workflow into distinct stages: first estimating sea floor reflectivities using 3D predictive deconvolution, then using these estimates to predict and remove multiples, and finally applying standard imaging to the corrected data. This segmentation allows each stage to be optimized independently, maintaining overall workflow efficiency while improving subsurface image accuracy.
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 allows for the construction of a 3D migrated shallow reflectivity section, effectively removing surface multiples and providing a more accurate image of the subsurface geological structure, even in conditions where primary reflections are not directly usable.
Implementation Method 1
evaluating a seismic wave equation using, as an input, the reconstructed seafloor reflectivity image to determine surface multiples
Implementation Method 2
seismic waves generated artificially have been used for more than 50 years for the imaging of geological layers... reflected waves and, more precisely, reflected compressional waves
Data Source
AI summary
A method for modeling shallow water multiples modeling using a predicted sea floor reconstruction is provided. A seafloor reflectivity image is reconstructed using acquired seismic data. Surface multiples are determined by evaluating a seismic wave equation using, as an input, the reconstructed seafloor reflectivity image. The determined surface multiples are subtracted from the acquired seismic data.