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Multi-scale unsupervised seismic wave velocity inversion method based on observation data self-coding

An observational data, unsupervised technology, applied in the field of geophysical exploration, can solve problems such as the difficulty of applying deep learning seismic inversion methods, and achieve the effect of improving performance and reducing the degree of nonlinearity and difficulty

Pending Publication Date: 2022-03-01
SHANDONG UNIV
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Problems solved by technology

This brings difficulties to the application of deep learning seismic inversion method in practical engineering

Method used

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  • Multi-scale unsupervised seismic wave velocity inversion method based on observation data self-coding
  • Multi-scale unsupervised seismic wave velocity inversion method based on observation data self-coding
  • Multi-scale unsupervised seismic wave velocity inversion method based on observation data self-coding

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Experimental program
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Effect test

Embodiment 1

[0078] Specifically, the method provided in this embodiment, such as figure 1 shown, including the following steps:

[0079] Step S1, obtain the geological wave velocity model by intercepting two-dimensional slices from the three-dimensional SEG / EAGE nappe model released by the International Society of Exploration Geophysicists SEG / European Association of Geoscientists and Engineers EAGE, and obtain the corresponding seismic observation data database through computer numerical simulation ;

[0080] The size of the nappe body model intercepted in this embodiment is 1600m×5000m, and the horizontal and vertical grid sizes are both 25m. A sponge-absorbing boundary of 50 meshes is set around the model. The seismic wave velocity models all contain a water layer with a depth of 9 grids, and the seismic wave velocity is 1800m / s. The geological structure under the water layer mainly includes folds, faults, etc. The wave velocity is set according to the original SEG / EAGE nappe model,...

Embodiment 2

[0113] A multi-scale unsupervised seismic wave velocity inversion system based on self-encoding of observation data, characterized by: including:

[0114] The inversion database construction module is configured to construct and calculate corresponding seismic observation data according to actual geological conditions, and form an unsupervised seismic wave velocity inversion database based on each seismic observation data and geological wave velocity model;

[0115] The earthquake observation data self-encoding module is configured to use the simulated earthquake observation data to train multiple self-encoders, and different self-encoders encode the global key information in the earthquake observation data into low-dimensional vectors of different lengths;

[0116] The building block of the predicted wave velocity model is configured to add a position feature information code to each seismic channel of the actual observation data, which is used to determine the position inform...

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Abstract

The invention provides a multi-scale unsupervised seismic wave velocity inversion method based on observation data self-encoding, which extracts large-scale information in the data through self-encoding of the observation data, and utilizes the information to guide an inversion network to complete recovery of different scale features in a velocity model, thereby reducing the non-linear degree of inversion and improving the accuracy of the inversion. On the basis, a trained observation data auto-encoder coding structure is embedded into the inversion network to complete effective extraction of seismic observation data information by the front end of the inversion network, so that the inversion network can better analyze information contained in seismic data and better establish a mapping relation between the seismic data and a velocity model; the inversion method is completely unsupervised, position codes are added to the observation data input into the network to assist the layout form of a network awareness observation system, and practical engineering application is facilitated. According to the method, an accurate inversion effect of the seismic velocity model can be obtained under the condition that no real geologic model is used as a network training label.

Description

technical field [0001] The invention belongs to the technical field of geophysical exploration, and in particular relates to a multi-scale unsupervised seismic wave velocity inversion method based on observation data self-encoding. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] Seismic exploration technology has played an important role in production practices such as oil and gas resource exploration, coal field exploration, and tunnel unfavorable geological detection. Among them, the basic working principle of reflected wave seismic exploration is to excite seismic waves through artificial seismic sources, and the seismic waves encounter rock interface or geological structures to reflect, and then these seismic wave signals containing geological information are received by geophones arranged on the ground, and used for subsequent Proces...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06N3/04G06N3/08G06F111/10
CPCG06F30/27G06N3/049G06N3/084G06N3/088G06F2111/10G06N3/045G01V1/303G01V2210/6222G01V2210/66
Inventor 刘斌任玉晓蒋鹏杨森林王清扬许新骥李铎
Owner SHANDONG UNIV
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