Seismic Internal Multiple Attenuation via Horizon-Based Adaptive Subtraction
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Solution Overview
Problem
Current methods for removing internal multiples from seismic data are inefficient and require significant knowledge of subsurface structures, making them impractical for effective attenuation.
Innovation Solution
A method that predicts internal multiples for each horizon using an internal multiple prediction algorithm, creates separate models for each horizon, and iteratively subtracts these models from seismic data using an adaptive subtraction technique, allowing for efficient removal of internal multiples in a single pass.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex ray tracing schemes are used to generate synthetic multiple waves for subtraction, then the accuracy of multiple removal is improved, but the complexity of the method and the knowledge required increases significantly
Solution Approach 1:
The patent uses observed primary waves as templates to create synthetic multiple waves through convolution operations. Instead of complex ray tracing, the method copies the characteristics of primary waves and combines them to generate multiple waveforms that can be subtracted from the data, significantly reducing methodological complexity while maintaining effectiveness
Solution Approach 2:
The patent replaces the mechanical complexity of ray tracing schemes with a mathematical convolution approach. By substituting the physical ray tracing process with signal processing operations (convolution of primary waves), the method achieves multiple generation with much lower computational and knowledge requirements
2Reliability
If traditional multiple removal methods are used, then some multiples can be attenuated, but the process requires significant prior knowledge of subsurface structure making it impractical
Solution Approach 1:
The method uses the seismic data itself to generate the synthetic multiples needed for subtraction. By convolving the observed primary waves with themselves or with Green's functions, the system creates the multiple waveforms directly from the available data, eliminating the need for external subsurface structural knowledge
Solution Approach 2:
The convolution-based approach serves multiple functions: it generates synthetic multiples for subtraction, utilizes the primary wave data directly, and works without requiring detailed subsurface structural information. This multi-functionality makes the method broadly applicable and practical across different geological settings
3Measurement precision
If internal multiples are predicted and subtracted iteratively, then the removal accuracy is improved, but the processing time increases
Solution Approach 1:
The patent applies adaptive subtraction iteratively to progressively remove multiples from different depth ranges. By performing partial subtractions in sequence rather than attempting complete removal in a single step, the method achieves high accuracy while managing computational time through targeted, incremental processing
Data Source
AI summary
A method for removing internal multiples from collected data, such as seismic data. The method includes predicting internal multiples for each horizon in a plurality of horizons that created the internal multiples. The internal multiples may be predicted from the seismic data in one pass. After predicting the internal multiples, the method includes creating a separate model of internal multiples for each horizon based on the predicted internal multiples for each horizon. The method then iteratively subtracts each separate model of internal multiples for each horizon from the seismic data.