Seismic wave imaging method based on particle swarm optimization CRS (Common Reflection Surface) super gather

A technology of particle swarm optimization and imaging method, applied in the field of seismic data processing for oil and gas exploration, can solve problems such as data curvature correction, and achieve the effects of improving the signal-to-noise ratio of seismic data, improving the signal-to-noise ratio of data, and eliminating formation effects

Inactive Publication Date: 2019-04-05
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

However, because the traditional CRS superposition process is relatively simple, and the data is not corrected for inclination and curvature, the influence of curvature and inclination in the processing res

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  • Seismic wave imaging method based on particle swarm optimization CRS (Common Reflection Surface) super gather
  • Seismic wave imaging method based on particle swarm optimization CRS (Common Reflection Surface) super gather
  • Seismic wave imaging method based on particle swarm optimization CRS (Common Reflection Surface) super gather

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Embodiment 1

[0041] Such as Figure 1 to Figure 6 As shown, a kind of CRS super-gather seismic wave imaging method based on particle swarm optimization of the present invention comprises the following steps:

[0042] Step S1. Optimizing distribution CRS superposition on the pre-stack data, and three wave field parameters α, R NIP , R N Use the particle swarm optimization algorithm to update, improve the accuracy of the wave field parameters and search for the optimal value of the CRS wave field parameters, where α is the exit angle of the zero-offset ray exiting to the surface, R N is the radius of curvature of the wave front of the Normal wave emitted to the surface, R NIP is the wavefront radius of curvature of the NIP wave;

[0043] The PSO algorithm defines a particle swarm in an M-dimensional space, and each particle maintains the memory and speed of its previous best position. At each iteration, the particle's velocity is adjusted based on the particle's best position and the ove...

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Abstract

The invention belongs to the field of seismic data processing for oil-gas exploration, and particularly relates to a seismic wave imaging method based on particle swarm optimization CRS (Common Reflection Surface) super gather. The method comprises the following steps of: step 1, optimizing distributed CRS superposition on pre-stack data, and updating three wave field parameters of a CRS superimposed surface of the superimposed final output by using a particle swarm optimization algorithm; step 2, performing curvature and inclination correction on the pre-stack data under the guidance of an optimal value of the CRS wave field parameter; step 3, inputting the optimal value of the CRS wave field parameters as a standard parameter, performing partial CRS superposition on the pre-stack data, and outputting a CRS optimized super-channel set; and step 4, performing CRS superposition and time offset on the output CRS optimized super gather to obtain an optimal CRS superposition profile and anoffset profile. The seismic wave imaging method based on the particle swarm optimization CRS super gather can effectively solve a problem that the inclination and curvature correction of the data arenot performed in the CRS superposition process in the prior art, so that the influence of the curvature and the inclination angle is amplified together with effective signals in a superposition process, thereby seriously affecting the imaging quality.

Description

technical field [0001] The invention belongs to the field of oil and gas exploration seismic data processing, and in particular relates to a CRS super-gather seismic wave imaging method based on particle swarm optimization. Background technique [0002] The common reflection surface element (CRS) superposition was first proposed by Professor Hurbal, based on the paraxial ray theory, through the CRS three parameters (α, R NIP , R N ) to superimpose the seismic data, taking all the reflections in the first Fresnel zone into consideration, improving the signal-to-noise ratio of the data and realizing more accurate imaging of complex subsurface media. Compared with the previous signal-based noise suppression algorithm, common reflection surface element (CRS) stacking has the advantage of effectively suppressing noise and improving the signal-to-noise ratio in the imaging process. Or it has broad application prospects in the exploration of unconventional oil and gas reservoirs....

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Application Information

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IPC IPC(8): G01V1/28G01V1/36
CPCG01V1/28G01V1/362G01V2210/514G01V2210/74
Inventor 孙小东依尔繁贾延睿宋煜李振春
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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