Self-Weighted Stacking for Seismic Image Noise Reduction
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Solution Overview
Problem
Current seismic data processing techniques struggle to produce high-quality images of subterranean formations with deposits that cause anomalous changes in acoustic wave velocities, such as salt domes, mobile shales, and carbonates, resulting in gaps and poor image quality, making it challenging to identify hydrocarbon reservoirs.
Innovation Solution
The implementation of self-weighted stacking (SWS) methods, which generate a smoothed-amplitude gather and use these smoothed amplitudes as weights for stacking seismic data, reducing noise and improving image quality without requiring user intervention, a priori information, or computation of model traces or thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional stacking techniques (e.g., straight stacking) are used, then the processing is simple and fast, but the image quality deteriorates in areas with anomalous velocity deposits
Solution Approach 1:
The patent implements self-weighted stacking where the stacking weights are automatically determined from the seismic data itself through smoothed amplitude calculations, eliminating the need for manual user intervention or a priori velocity models. The system serves itself by deriving all necessary parameters from the input data, thus improving image quality without proportionally increasing operational complexity
Solution Approach 2:
The patent performs preliminary smoothing of amplitude gathers before the stacking operation to pre-determine the weights that will be applied. This preliminary action of calculating smoothed amplitudes allows the stacking process to automatically adapt to velocity variations without requiring complex real-time adjustments during the stacking itself
2Manufacturing precision
If conventional stacking with user-defined weights is used, then some image quality improvement is achieved, but user expertise and a priori information are required
Solution Approach 1:
The system automatically determines stacking weights by calculating smoothed amplitudes from the seismic data without requiring user input or external velocity models. This self-service mechanism eliminates the need for user expertise in defining weights while maintaining high image quality through data-driven weight optimization
Solution Approach 2:
The patent replaces the manual mechanical process of user-defined weight selection with an automated computational system that calculates weights from smoothed amplitude gathers. This substitution eliminates the need for user intervention while achieving superior image quality through consistent algorithmic processing
3Productivity
If straight stacking is used, then processing is fast and simple, but noise reduction is insufficient
Solution Approach 1:
The patent performs preliminary smoothing of the amplitude gathers before stacking to pre-calculate optimal weights that will be applied during stacking. This preliminary smoothing action enables effective noise reduction while maintaining processing efficiency, as the weight calculation is performed once before the stacking operation rather than during iterative processing
Data Source
AI summary
This disclosure is directed to systems and methods for stacking seismic data. The methods receive seismic data collected from a survey of a subterranean formation. A gather of seismic data may have flattened reflection events obtained as a result of normal moveout (“NMO”) corrections or pre-stack migration. Alternatively, the gather may be an unmigrated gather with non-horizontal reflection events. A smoothed-amplitude gather is generated from the gather. Traces of the gather are stacked to generate a trace with significantly reduced noise using corresponding smoothed amplitudes of the smoothed-amplitude gather as weights.