Covariance Interpolation for Spatial Varying Wavelet Estimation
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Solution Overview
Problem
Traditional methods for spatial varying wavelet estimation in seismic processing face inaccuracies and instability, especially in complex geological situations with sparse known discrete locations and rapid phase spectrum changes, leading to inaccurate interpolation and instability.
Innovation Solution
The use of covariance interpolation method to estimate spatial varying wavelets by interpolating coefficients in the data space, combining global and local angle-dependent wavelets, rather than directly interpolating in time or frequency domains, which simplifies seismic processing and reduces computational time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional direct interpolation methods are used in time or frequency domains, then the process is straightforward, but the estimation becomes inaccurate and unstable in complex geological situations with sparse well locations and rapid phase spectrum changes
Solution Approach 1:
The patent introduces covariance as an intermediary mechanism to mediate the interpolation process. Instead of directly interpolating wavelets in time or frequency domains, the method uses covariance relationships between different locations to guide the interpolation, providing a stable and accurate estimation even in complex geological situations with sparse well locations
Solution Approach 2:
The patent transforms the interpolation problem from the time or frequency domain to a parameter space based on covariance. By changing the domain of interpolation and using covariance parameters to guide the process, the method achieves both accuracy and stability that traditional direct interpolation methods cannot provide
2Measurement precision
If complex interpolation methods are used to improve accuracy in sparse well locations, then estimation precision improves, but computational time and complexity increase
Solution Approach 1:
The patent segments the wavelet estimation process into distinct components: global wavelet estimation, local wavelet estimation at well locations, and covariance-based interpolation between them. This segmentation allows each component to be computed efficiently and independently, reducing overall computational time while maintaining high accuracy
Solution Approach 2:
The patent performs preliminary estimation of global and local wavelets at well locations before performing the interpolation step. This preliminary action prepares the necessary components in advance, so that the actual spatial interpolation using covariance can be performed efficiently without redundant computations
Data Source
AI summary
A computing program product and method for interpolating wavelets coefficients and estimating spatial varying wavelets using the covariance interpolation method in the data space over a survey region having multiple well locations, are disclosed. The method and computing program product, embodied in a non-transitory computer readable device, that stores instructions for performing by a device are based on interpolating coefficient models in the data space domain using covariance analysis methods to overcome inaccuracy and instability issues commonly observed during wavelet estimation and interpolation.