Seismic wavelet signal extraction method based on maximum joint entropy

A technology of maximum correlation entropy and seismic wavelet, applied in seismic signal processing, seismology, geophysical measurement, etc., can solve the problems of low precision, calculation error, seismic data noise, etc., and achieve high precision and strong robustness Effect

Active Publication Date: 2017-05-31
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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Problems solved by technology

[0024] The purpose of the present invention is to solve the deterministic wavelet estimation method based on the least squares method in the prior art due to noise in the seismic data in the actual measurement process, and factors such as inaccura

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  • Seismic wavelet signal extraction method based on maximum joint entropy
  • Seismic wavelet signal extraction method based on maximum joint entropy
  • Seismic wavelet signal extraction method based on maximum joint entropy

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Embodiment 1

[0087] In the embodiment of the present invention, we use artificially constructed seismic wavelets, and use the maximum correlation entropy to extract the wavelets.

[0088] In actual seismic records, seismic wavelets are often of mixed phase, so we directly use the mixed phase wavelet ( image 3 ) is used to calculate synthetic seismic records for the model, and the reflection coefficient is known as Figure 4 As shown, the reflection coefficient and seismic wavelet are convolved to form a seismic record as Figure 5 As shown, below we test the extracted wavelet results according to the maximum correlation entropy criterion. In order to verify the robustness of the algorithm, we also compare the estimated wavelet results under the least squares condition. Figure 4 In order to synthesize seismic records and extract wavelet results in a noise-free environment, it can be found that in a noise-free environment, both methods can obtain better estimation results.

[0089] In or...

Embodiment 2

[0091] In the embodiment of the present invention, we use the actual work area of ​​an oilfield in western my country to estimate the seismic wavelet. Firstly, the well seismic records are extracted, and the well curves are divided into blocks to obtain the reflection coefficient sequence, and then the seismic wavelet is estimated by the maximum correlation entropy criterion and the least squares criterion, and the results are as follows: Figure 7 shown. In order to verify the validity of the results, we verified by comparing the synthetic records with the synthetic records near the well. Figure 8 It is the maximum correlation entropy criterion to extract the wavelet synthetic seismic record, and the least squares criterion to extract the wavelet synthetic record and compare it with the side-hole seismic trace. The error is 2.3, while the overall mean square error of the seismic wavelet synthesis record obtained under the least squares criterion is 3.6. It can be seen that ...

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Abstract

The invention discloses a seismic wavelet signal extraction method based on the maximum joint entropy; a seismic wavelet estimate method in the exploration geophysics and the maximum joint entropy criterion in information theory learning are combined, and the maximum joint entropy criterion can replace the original least squares criterion, thus allowing an object function can better solve non-gauss noises. Compared with the conventional least squares criterion, the seismic wavelet signal extraction method based on the maximum joint entropy is better in robustness, higher in precision, and can better process the geology exploration data.

Description

technical field [0001] The invention belongs to the technical field of seismic data processing, and in particular relates to the design of a method for extracting seismic wavelet signals based on maximum correlation entropy. Background technique [0002] Seismic wavelet is the basis for high-resolution processing of seismic data, forward modeling and reservoir parameter inversion. Inaccurate wavelets will lead to unreliable impedance obtained by inversion, which will lead to the failure of high-resolution processing of seismic data to obtain ideal high-fidelity profiles. Therefore, the precise estimation of seismic wavelets has always been one of the core issues in the field of exploration geophysics. The basic framework of seismic wavelet extraction is a convolution model, including wavelets, reflection coefficient sequences, and seismic traces with noise. The common methods for seismic wavelet estimation can be divided into two categories: one is the statistical extracti...

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Application Information

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IPC IPC(8): G01V1/28
CPCG01V1/288
Inventor 王峣钧李文昊厍斌程三胡光岷张家树
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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