A Velocity Modeling Method for Full Waveform Inversion Based on Sensitive Kernel Function Optimization

A full waveform inversion and velocity modeling technology, applied in the field of exploration geophysics, to achieve high computing efficiency, avoid cycle jumping problems, and reduce nonlinear effects

Active Publication Date: 2022-03-04
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

A basic requirement for the successful realization of multi-scale full waveform inversion is that the field observation data contain low-frequency signals (usually the lowest frequency is required to be 2-3 Hz), but the lowest frequency of conventional geophones is often greater than or equal to 5 Hz, so for seismic data collected by conventional geophones It is still quite challenging to directly apply full waveform inversion to the data, and it is urgent to develop a stable full waveform inversion method suitable for routine data acquisition

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  • A Velocity Modeling Method for Full Waveform Inversion Based on Sensitive Kernel Function Optimization
  • A Velocity Modeling Method for Full Waveform Inversion Based on Sensitive Kernel Function Optimization
  • A Velocity Modeling Method for Full Waveform Inversion Based on Sensitive Kernel Function Optimization

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[0042] The specific embodiment of the present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0043] The conventional full waveform inversion uses the P-wave velocity as the inversion parameter, and the velocity gradient calculated in the local optimization algorithm contains all the scattering angle information. Using this information in general to update the velocity model will easily make the inversion process fall into a local extremum. The Langerian multiplier method was used to derive the velocity and impedance sensitive kernel functions. Through analysis, it was found that the velocity sensitive kernel function is mainly forward scattering angle information, which mainly reflects the low wave number part of the subsurface parameter model, while the impedance sensitive kernel function is mainly backscattering The angular information mainly reflects the middle and high wavenumber part of the parametric model.

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Abstract

The invention discloses a full waveform inversion speed modeling method optimized by a sensitive kernel function, and relates to the field of exploration geophysics. The inversion method increases the forward scattering angle information in the early stage of iteration to restore the low wavenumber part of the model, and gradually enhances the backscattering angle information as the number of iterations increases to construct the middle and high wavenumber part of the model. This inversion process can not only naturally weaken the nonlinearity of inversion, avoid falling into local extremum, but also reduce the calculation cost of multi-scale inversion, and has a good application prospect.

Description

technical field [0001] The invention relates to the field of exploration geophysics, in particular to a full waveform inversion speed modeling method optimized by a sensitive kernel function. Background technique [0002] Velocity modeling is a crucial step in seismic data processing, and the accuracy of modeling directly determines the quality of subsequent migration imaging processing. Conventional velocity modeling methods include migration velocity analysis and ray tomography inversion. Since these methods use seismic wave traveltime information, the estimated velocity model is mainly low wavenumber parts, while the middle and high wavenumber parts are missing, so it is difficult to obtain the full High resolution velocity model in the wavenumber band. In order to solve this problem, full waveform inversion came into being, which uses the seismic full wave field information (travel time, amplitude, multiple waves, scattered waves, etc.), and uses synthetic data to fit t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01V1/30
CPCG01V1/303G01V2210/6222
Inventor 杨继东徐洁黄建平李振春孙加星田祎伟
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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