Broadband Seismic Wavelet Estimation via Multi-Stack Misfit Constraints
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Solution Overview
Problem
Existing wavelet estimation methods for seismic data are labor-intensive and result in large variations between stacks, particularly for broadband wavelet estimation, as they are typically estimated independently, which does not accurately represent the underlying physics of the subsurface.
Innovation Solution
A method for estimating broadband wavelets using a misfit function that constrains the wavelet with an amplitude-only long wavelet and an amplitude-and-phase short wavelet, allowing for more efficient and automated wavelet estimation across multiple seismic stacks, while honoring the underlying physics and reducing variability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If wavelets are estimated independently for each stack, then the estimation process is simpler to implement, but large variations occur between stacks and the process becomes labor intensive
Solution Approach 1:
The patent combines multiple wavelet estimations into a unified framework by stacking wavelet equations across different stacks and solving them simultaneously. This merging approach enforces consistency across stacks while maintaining the ability to process multiple stacks together, resolving the contradiction between ease of independent estimation and consistency across stacks.
Solution Approach 2:
The patent creates a universal wavelet estimation framework that can handle multiple stacks simultaneously with a single set of equations. The misfit function and optimization approach work universally across different stacks, providing consistent wavelet estimates without requiring separate processing for each stack, thus improving both ease of use and consistency.
2Ease of operation
If traditional wavelet estimation methods are used, then the process is easier to implement, but it becomes very labor intensive for broadband wavelet estimation
Solution Approach 1:
The patent replaces manual, iterative wavelet estimation procedures with an automated optimization framework based on misfit functions. The computer-implemented method automatically adjusts wavelet parameters to minimize the misfit between observed and modeled data, eliminating labor-intensive manual adjustments while maintaining ease of operation through standardized software procedures.
Solution Approach 2:
The wavelet estimation system performs self-optimization by automatically minimizing the misfit function through iterative adjustment of wavelet parameters. The system serves itself by finding optimal wavelet solutions without requiring continuous human intervention, thereby improving productivity while keeping the operation simple for users.
Data Source
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AI summary
Computing device, computer instructions and method for estimating a broadband wavelet associated with a given seismic data set. The method includes receiving (600) broadband seismic data; constructing and populating (608) a misfit function; calculating (610) the broadband wavelet based on the misfit function and the broadband seismic data; and estimating (612) physical reservoir properties of a surveyed subsurface based on the broadband wavelet. The broadband wavelet is constrained, through the misfit function, by (1) an amplitude only long wavelet, and (2) an amplitude and phase short wavelet. The amplitude and phase short wavelet is shorter in time than the amplitude only long wavelet.