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Seismic thin layer detection method based on ICEEMDAN constrained generalized S transformation

A thin layer detection and generalized technology, applied in the field of seismic exploration, can solve problems such as difficult application, and achieve the effect of good data characteristics

Pending Publication Date: 2021-11-05
YANGTZE UNIVERSITY
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Problems solved by technology

However, the practical application of this method is difficult, mainly because the original method is to decompose the time-frequency structure of the composite signal, and the frequency is closely related to the size of the time window.

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  • Seismic thin layer detection method based on ICEEMDAN constrained generalized S transformation
  • Seismic thin layer detection method based on ICEEMDAN constrained generalized S transformation
  • Seismic thin layer detection method based on ICEEMDAN constrained generalized S transformation

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Embodiment Construction

[0045] The implementation of the present invention will be described in detail below in conjunction with the examples, but they do not constitute a limitation of the present invention, and are only examples. At the same time, the advantages of the present invention will become clearer and easier to understand.

[0046] Such as figure 1 As shown, a kind of seismic thin layer detection method based on ICEEMDAN constrained generalized S transform of the present embodiment comprises the following steps:

[0047] S1: read in the original seismic data;

[0048] S2: The original seismic data read in step S1 is decomposed by ICEEMDAN, and the obtained signal components of each layer represent the frequency components in the original signal respectively, and are arranged in order from high frequency to low frequency;

[0049] S3: Using the results obtained in step S2, using ICEEMDAN’s high-frequency to low-frequency sequence arrangement and the characteristics of noise existing in hi...

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Abstract

The invention belongs to the technical field of thin layer detection in seismic exploration, and particularly relates to an ICEEMDAN-constrained generalized S-transform detection method, which is characterized in that non-recursive and adaptive decomposition is carried out on a composite signal through ICEEMDAN, and a high-frequency component is reconstructed, so that a time-frequency structure obtained by the method can better adapt to frequency distribution corresponding to a thin layer, the limitation of time window factors is reduced, and the accuracy of time-frequency analysis is improved; the time-frequency analysis is carried out on the reconstructed signal (specific component) of the signal through the generalized S transformation, and the frequency values obtained through the generalized S transformation are superposed and de-averaged, so that the corresponding relation between the frequency and the stratum can be intuitively displayed, and the operability is strong.

Description

technical field [0001] The invention belongs to the technical field of seismic exploration, and specifically relates to a thin-seismic detection method based on ICEEMDAN constrained generalized S-transformation. The invention aims to propose a new method for seismic detection of continental thin layers. Background technique [0002] In recent years, time-frequency analysis has played an important role in the interpretation of seismic data. The various frequencies contained in thin layers at different time periods represent the characteristics of different depths. Fourier transform can realize the possibility of mutual conversion of signals in the time domain and frequency domain, so that the characteristics of time domain signals can be well reflected in the frequency domain, and can effectively analyze seismic data, which can be used for seismic interpretation and thin layer Forecasting helps a lot. At present, there are many conversion methods in the time domain and frequ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/28G01V1/30
CPCG01V1/282G01V1/306G01V2210/64
Inventor 许辉群赵桠松
Owner YANGTZE UNIVERSITY