Phase Cross-Correlation Seismic Velocity Modeling for Cycle-Skipping
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Solution Overview
Problem
Conventional seismic data processing methods suffer from cycle-skipping issues during full waveform inversion, leading to inaccuracies in seismic velocity models and subterranean imaging.
Innovation Solution
A method and system that utilize phase cross-correlation and a penalty function to form trace pairs, determine an extremum of an objective function, and update the seismic velocity model by combining seismic velocity increments, thereby improving the alignment and accuracy of seismic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional full waveform inversion is used to update seismic velocity models, then the process can be completed with standard methods, but cycle-skipping issues occur leading to inaccuracies in seismic velocity models and subterranean imaging
Solution Approach 1:
The patent introduces phase cross-correlation as an intermediary mechanism between observed and simulated seismic traces. Instead of directly inverting waveforms (which causes cycle-skipping), the method uses phase correlation to establish reliable phase relationships first, then uses this information to guide the velocity model updating process. This intermediary approach bridges the gap between noisy direct comparison and accurate velocity estimation.
Solution Approach 2:
The patent transforms the inversion problem by changing the parameter space from direct waveform amplitude comparison to phase correlation-based metrics. By reformulating the objective function to use phase cross-correlation coefficients and penalty functions that reward phase consistency, the method changes the optimization landscape to avoid cycle-skipping local minima while maintaining convergence to accurate velocity models.
2Measurement precision
If phase cross-correlation and penalty functions are used to form trace pairs and update velocity models, then alignment accuracy improves and cycle-skipping is reduced, but the computational complexity increases
Solution Approach 1:
The patent segments the seismic trace comparison process into distinct components: phase extraction, phase cross-correlation calculation, penalty function evaluation, and velocity model updating. By dividing the complex inversion process into these manageable segments, each can be optimized independently. The phase cross-correlation is computed only for relevant trace pairs, and the penalty function selectively penalizes only the most problematic cycle-skipping cases, reducing overall computational burden.
Solution Approach 2:
The patent applies partial action by using phase cross-correlation selectively for trace pairs that are most likely to exhibit cycle-skipping behavior, rather than computing full waveform inversion for all traces. The penalty function is applied with varying weights depending on the specific trace pair characteristics, applying stronger corrections only where needed. This partial application of the complex methodology reduces computational complexity while maintaining alignment accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method enhances the alignment of observed and simulated seismic traces, reducing cycle-skipping and improving the accuracy of seismic velocity models and subterranean imaging, facilitating better decision-making for hydrocarbon exploration.
Implementation Method 1
a seismic source generates seismic waves which propagate through the subterranean region of interest are and detected by seismic receivers
Implementation Method 2
A cross-correlation between a simulated seismic dataset, an observed seismic dataset, and a penalty function is determined
Data Source
AI summary
A method for forming an image of a subterranean region of interest, using an observed seismic dataset, a seismic velocity model and a simulated seismic dataset based in part, on the seismic velocity model is provided. This method includes forming trace pairs from the simulated and observed seismic dataset, wherein each of the trace pairs comprises of an observed trace and a simulated trace. An objective function is formed based on a penalty function and a phase cross-correlation between the observed and simulated seismic trace of each of the trace pairs. This method further includes determining an extremum of the objective function and a seismic velocity increment based on the extremum. The seismic velocity model is updated by combining the seismic velocity increment and the seismic velocity model and the image of the subterranean region of interest is formed based in part, on the seismic velocity model.


