Method and apparatus for constructing near-surface velocity model

By processing three-dimensional surface wave data from seismic guns, a more accurate near-surface velocity model was constructed, which solved the problem of low accuracy of near-surface velocity models in traditional methods and enabled accurate characterization of stratum thickness and number of layers.

CN116299689BActive Publication Date: 2026-07-14CHINA NAT PETROLEUM CORP +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA NAT PETROLEUM CORP
Filing Date
2021-12-21
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Traditional near-surface velocity models based on P-wave seismic data are not very accurate, especially in terms of accurately representing the thickness and number of strata in western oilfield areas.

Method used

Using three-dimensional surface wave data from seismic artillery, high signal-to-noise ratio phase spectrum imaging and batch automatic picking were performed by acquiring surface wave data from multiple receivers to establish an initial model of the variable layer. The near-surface velocity model was constructed by using dispersion curves and half-wavelength curves and combining them with a three-dimensional interpolation algorithm.

Benefits of technology

It improves the characterization accuracy of the near-surface velocity model, enabling it to better represent the detailed features of surface changes and solving the problem of low accuracy in near-surface detail characterization in traditional methods.

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Abstract

The application discloses a method for constructing a near-surface velocity model, and belongs to the field of seismic exploration. The method comprises the following steps: acquiring linear surface wave data in seismic shot three-dimensional surface wave data of a target region, processing to obtain dispersion curve data, establishing an initial model of a variable layer of the target region, setting the initial model of the variable layer as a target model, calculating predicted dispersion curve data, optimizing the target model based on a difference between the dispersion curve data and the predicted dispersion curve data and a correction value of the velocity of each stratum at each geophone in the target model, processing a variable layer optimization model to obtain a three-dimensional variable layer velocity model of the target region, establishing a work area elevation surface model of the target region, fusing the three-dimensional variable layer velocity model and the work area elevation surface model to obtain a near-surface velocity model of the target region. By using the application, the problem that the near-surface detail description precision is not high when a velocity model is constructed by using P-wave seismic data can be solved.
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