Azimuthal Beam Convolution for Seismic Multiple Attenuation
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Solution Overview
Problem
Current seismic data processing methods struggle to accurately remove surface-related multiples in complex 3D seismic data, particularly in deep-water environments, due to challenges in interpolating or extrapolating data with large shot and receiver spacing, leading to issues like aliasing and damage to primary reflections.
Innovation Solution
A computer-implemented method that utilizes wide-azimuth seismic data to identify and adjust beam datasets by determining pegleg arrivals, identifying corresponding primary beams, and convolving modeled pegleg beams with primary beams to remove multiple arrivals, thereby enhancing the accuracy of seismic imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If traditional interpolation or extrapolation methods are used to handle large shot and receiver spacing, then data coverage is improved, but aliasing and damage to primary reflections occur
Solution Approach 1:
The patent introduces azimuth as an additional dimension to the conventional 2D seismic data processing. By organizing data into beam datasets with azimuthal information and processing in this extended dimensional space, the method achieves accurate multiple attenuation without requiring aggressive interpolation that causes aliasing. The azimuthal dimension provides additional constraints that enable precise multiple identification and removal while preserving primary reflections.
2Area of stationary object
If aggressive interpolation is applied to fill large shot and receiver spacing, then spatial coverage is improved, but aliasing artifacts are introduced
Solution Approach 1:
The method uses the existing wide-azimuth seismic data itself to predict and remove multiples, rather than relying on external interpolation models. By convolving the primary beam dataset with a predicted multiple dataset generated from the same data, the system achieves accurate multiple attenuation without introducing aliasing artifacts from aggressive interpolation. The data serves its own prediction and correction function.
3Productivity
If conventional multiple attenuation methods are used, then processing time is reduced, but accuracy in complex 3D geometries deteriorates
Solution Approach 1:
The patent performs preliminary organization of seismic data into beam datasets with azimuthal information before multiple attenuation processing. This pre-processing step structures the data in a way that enables efficient and accurate multiple prediction and removal. By establishing the azimuthal framework in advance, the method achieves both high processing efficiency and accurate multiple attenuation in complex 3D geometries without requiring iterative or computationally intensive post-processing.
Data Source
AI summary
The present invention incorporates the use of model-driven and data-driven methodologies to attenuate multiples in seismic data utilizing a prediction model which includes multiply-reflected, surface-related seismic waves. The present invention includes beam techniques that account for beam azimuth, and convolving a predicted multiples beam with a segment of a modeled pegleg beam to obtain a convolved multiples beam. The convolved multiples beam can then be deconvolved to attenuate the multiples that are present in the original input beam.