Seismic data weighted stacking method based on dynamic time warping

A technology of dynamic time warping and weighted stacking, which is applied in seismology, seismic signal processing, geophysical measurement, etc., can solve the problem of not being able to make full use of seismic trace reflection information, achieve good application effects, and prove the effect of practicability

Active Publication Date: 2020-09-01
CHONGQING UNIV OF TECH
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Problems solved by technology

[0005] Aiming at the technical problem that the existing weighted stacking methods usually use some weights with small weights or even zero weights to reduce the influence of these abnormal seismic traces on the stacking results, but these methods cannot make full use of the reflection information of these misaligned seismic traces, the present invention Provide a weighted stacking method for seismic data based on dynamic time warping

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  • Seismic data weighted stacking method based on dynamic time warping
  • Seismic data weighted stacking method based on dynamic time warping
  • Seismic data weighted stacking method based on dynamic time warping

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[0031] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific illustrations.

[0032] Please refer to figure 1 , Figure 2a with Figure 2b As shown, the present invention provides a method for weighted stacking of seismic data based on dynamic time warping, comprising the following steps:

[0033] S1. Select a reference seismic trace, which is set as the arithmetic mean value of the pre-stack seismic data matrix in the spatial direction, namely:

[0034]

[0035] Among them, A i (t) is the i-th pre-stack seismic trace A i The sampling value at time t, C is the number of pre-stack seismic traces, R(t) is the sampling value of reference seismic trace R at time t; Figure 2b , the number of pre-stack seismic traces is C=4, and the reference seismic traces calculated by using the formula in this step are as follows ...

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Abstract

The invention provides a seismic data weighted stacking method based on dynamic time warping. The method comprises the steps of S1 selecting a reference seismic trace, and setting the reference seismic trace as an arithmetic mean value of a pre-stack seismic data matrix in a spatial direction; S2 calculating DTW matching points between each pre-stack seismic trace and the reference seismic trace through the following formula, and searching sampling points associated with each sampling point of the reference seismic trace in the CMP trace set; S3 setting the weight of each sampling point according to the noise of each related sampling point; S4 updating each sampling point of the reference seismic trace as a weighted average value of the sampling points related to the sampling point; and S5repeating the steps S2 to S4 until convergence, and outputting the reference seismic trace as a final superimposed seismic trace. According to the method, the advantages of a DTW method and a weighted stacking method are combined, the influence of seismic trace time migration errors and seismic data noise on data stacking is overcome, and a good application effect is obtained through testing on synthetic data and real seismic data.

Description

technical field [0001] The invention relates to the technical field of seismic data, in particular to a method for weighted stacking of seismic data based on dynamic time warping. Background technique [0002] The stacking of common midpoint gathers (CMP) can improve the signal-to-noise ratio of seismic data and plays an important role in seismic data interpretation. The simplest stacking method is to calculate the arithmetic mean of the pre-stack data along the offset direction. If the time calibration of the pre-stack seismic gathers is accurate and only Gaussian white noise is included, simple averaging can obtain the best stacking results. However, due to the inaccuracy of static calibration and velocity picking, abnormal offset, irregularity and non-Gaussian random noise often appear in actual CMP gathers, and the average stacking method cannot effectively suppress the existing noise, so it cannot meet the actual needs. [0003] In order to overcome the above problems,...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/36
CPCG01V1/362G01V2210/52
Inventor 宋承云李凌轩陈韵清武子腾
Owner CHONGQING UNIV OF TECH
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