Phase correction full waveform inversion method based on continuous wavelet transform

By performing phase correction in the wavelet domain and updating the model using automatic differentiation techniques, the periodic jump problem in traditional full-waveform inversion was solved, achieving high-precision underground velocity structure inversion.

CN122260436APending Publication Date: 2026-06-23CHINA UNIV OF MINING & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA UNIV OF MINING & TECH
Filing Date
2026-03-24
Publication Date
2026-06-23

AI Technical Summary

Technical Problem

Traditional full-waveform inversion methods are prone to getting stuck in local minima when the initial model is poor or lacks low-frequency components, leading to periodic jump problems. Furthermore, the computational complexity of the accompanying state method is high, making it difficult to obtain high-precision underground velocity structures.

Method used

Seismic data is transformed into the wavelet domain using continuous wavelet transform, and phase correction is performed. A phase correction inversion objective function is then constructed in the wavelet domain. By combining automatic differentiation techniques and the Adam optimizer to update the velocity model, period jumps are avoided, and inversion accuracy is improved.

Benefits of technology

This effectively avoids periodic jumps, improves the resolution and stability of full waveform inversion, and obtains a high-precision underground velocity model.

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Abstract

The present application relates to a kind of phase correction full waveform inversion methods based on continuous wavelet transform, specifically is using continuous wavelet transform to transform time domain seismic signal to wavelet domain, then in wavelet domain to observed data is carried out phase correction, and corresponding wavelet domain objective function is constructed, relies on automatic differentiation technique to solve gradient, realizes a kind of method of velocity modeling.First, to seismic wave data is carried out continuous wavelet transform, extracts the wavelet domain phase information of observed data and simulated data, by introducing phase correction factor ε, constructs exponential phase difference, and establishes the objective function of phase correction inversion in wavelet domain;Second, the loss of objective function is transmitted back under the automatic differentiation framework, to avoid with source derivation, to obtain update gradient;Finally, using Adam optimizer updates velocity model.The present application can be reduced to within half cycle by phase correction so that observed data and simulated data phase difference, to effectively avoid period jump phenomenon, finally obtain high-precision inversion result.
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