Seismic Spectral Balancing via Iterative Subtraction
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Solution Overview
Problem
Current seismic interpretation methods face challenges in accurately characterizing subsurface structures and improving seismic volume analysis for resource extraction due to limitations in processing seismic data, particularly in addressing amplitude decay and spectral leakage issues.
Innovation Solution
A computer-implemented method and system for seismic data processing that utilizes a simulation component with an object-based framework, incorporating features like mesh generation and spectral balancing techniques to enhance seismic data analysis, allowing for more accurate modeling and simulation of geologic environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scaling factors are applied to compensate for amplitude decay, then amplitude accuracy is improved, but spectral leakage artifacts are introduced
Solution Approach 1:
The patent extracts and removes spectral leakage artifacts from the seismic data through spectral subtraction techniques. The method identifies and eliminates the harmful spectral components introduced by scaling operations, thereby preserving the beneficial amplitude compensation while removing the detrimental artifacts.
Solution Approach 2:
The patent modifies spectral parameters through frequency-dependent scaling and spectral shaping operations. By changing the spectral characteristics of the data in controlled ways, the method achieves amplitude compensation while managing the introduction of artifacts through parameter optimization.
2Measurement precision
If spectral balancing is applied to improve frequency content, then seismic resolution is improved, but processing complexity increases
Solution Approach 1:
The patent segments the spectral balancing process into distinct operational stages: initial scaling factor application, spectral leakage identification, artifact removal through spectral subtraction, and final spectral shaping. This segmentation allows each processing step to be optimized independently, managing overall complexity while achieving high seismic resolution.
Solution Approach 2:
The patent performs preliminary spectral analysis and scaling factor determination before the main processing operations. By pre-calculating scaling factors and identifying spectral characteristics in advance, the method reduces the complexity of subsequent processing steps while maintaining high resolution outcomes.
3Measurement precision
If amplitude compensation is applied to enhance deep signal visibility, then subsurface characterization accuracy is improved, but noise amplification occurs
Solution Approach 1:
The patent applies local quality control by implementing frequency-dependent and depth-dependent processing parameters. Different regions of the frequency spectrum and different depth intervals receive tailored compensation factors, allowing enhanced visibility of deep signals while controlling noise amplification in specific frequency bands through localized parameter adjustment.
Data Source
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AI summary
A method can include receiving seismic data that has an associated bandwidth; for a number of frequency bands, for a number of frequency bands, iteratively filtering and adjusting the seismic data by applying band-pass filters to extract information associated with each of the frequency bands where the adjusting the seismic data includes, after each iteration, subtracting extracted information from the seismic data prior to a subsequent iteration; balancing the extracted information to generate spectrally balanced seismic data; and outputting the spectrally balanced seismic data.