Method for optimizing stacking parameters of seismic common reflection surface

Abstract

The invention provides a method for optimizing the stacking parameters of a seismic common reflection surface, which includes the following steps: S1, acquiring seismic data, and acquiring the wavefront curvature radius of an initial reflection point and the wavefront curvature radius and inclination angle of an initial reflection surface based on the seismic data; and S2, acquiring the optimal values of the wavefront curvature radius of the initial reflection point and the wavefront curvature radius and inclination angle of the initial reflection surface according to the wavefront curvature radius of the initial reflection point and the wavefront curvature radius and inclination angle of the initial reflection surface and based on an objective function. The invention provides a method foroptimizing the stacking parameters of a seismic common reflection surface. In the first step, three initial parameters are found, the initial parameters are searched one by one, and simple linear search can be used. In the second step, an optimal combination solution is searched near the initial parameters by using a global optimization algorithm. Thus, the problem on how to fast scan the CRS imaging parameters by a CMAES algorithm is solved.

Description

technical field [0001] The invention relates to the technical field of geological survey, and more specifically, to a method for realizing the optimization of stacking parameters of seismic common reflection surfaces. Background technique [0002] Common reflection surface (CRS) stacking is a special zero-offset imaging method, which has the characteristics of not relying on the macroscopic velocity model and being completely data-driven. Since the CRS theory introduces the concept of the reflector and limits it to the first Fresnel zone, it can enhance the signal-to-noise ratio of the stacked section by increasing the number of stacking times, while maintaining a certain resolution. Therefore, the CRS stacking method is more suitable for seismic data with low signal-to-noise ratio and low coverage times. Specifically, the common reflection surface element (CRS) superposition method uses the Fresnel principle to expand the reflection surface element (for two-dimensional, to...

AI Technical Summary

Problems solved by technology

One-dimensional space search can use linear search, but three-dimensional space needs more advanced and fast optimization search algorithm

At present, simulated annealing algorithm and gradient-based algorithm are widely used, which are relatively inefficient and easy to fall into local minimum, which limits the popularization and application of CRS technology.

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