Seismic Data Wavelet Decomposition for Noise Attenuation
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Solution Overview
Problem
Seismic data traces often contain unwanted noise components that overwhelm desired seismic reflections, reducing the accuracy of subterranean formation property interpretation in seismic prospecting.
Innovation Solution
The method involves decomposing seismic data traces into a set of predefined wavelets, reconstructing them using a subset of these wavelets, and applying techniques like gain control and filtering to produce modified seismic data that better represents the target subterranean formation, thereby improving interpretation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic data processing methods are used, then data acquisition and basic processing can be completed, but noise components overwhelm desired seismic reflections and reduce interpretation accuracy
Solution Approach 1:
The patent applies wavelet decomposition to segment the seismic data trace into multiple wavelet components. Each wavelet represents a specific frequency content and can be independently processed. This segmentation allows selective removal of noise wavelets while preserving signal wavelets, thereby improving interpretation accuracy without losing valuable seismic information.
Solution Approach 2:
The patent extracts and removes unwanted noise components from the seismic data by identifying and eliminating specific wavelet components that correspond to noise. The noise wavelets are extracted from the decomposed set and removed, leaving only the desired signal wavelets. This extraction process directly addresses the harmful noise factors that were overwhelming the seismic reflections.
2Measurement precision
If noise attenuation methods are applied to improve signal-to-noise ratio, then interpretation accuracy improves, but processing complexity increases
Solution Approach 1:
By segmenting the seismic data into wavelet components, the patent simplifies the noise attenuation process. Instead of processing the entire complex signal at once, the system works with individual wavelet components that can be easily identified and processed. This segmentation reduces the effective complexity of noise attenuation while improving the signal-to-noise ratio.
Solution Approach 2:
The patent uses predefined wavelet templates to represent expected signal characteristics. These templates are used to compare against the decomposed wavelets to identify and retain only those that match the expected signal pattern. This copying approach simplifies the decision-making process for noise attenuation by providing clear reference patterns for what constitutes valid signal versus noise.
Data Source
AI summary
A method is provided for processing seismic data for interpretation. The method includes recording an original seismic data trace, decomposing the original seismic data trace into a set of predefined wavelets, and reconstructing a seismic data trace from, at least a subset of, the set of wavelets.