A Joint Denoising Method for Seismic Data

Abstract

The invention discloses a joint denoising method of seismic data, comprising the following steps: S1, using variational mode decomposition to decompose and process seismic section data to obtain new data; S2, using an improved total variation method for the new data Perform denoising processing; S3, combine and reconstruct the denoised data; obtain the final seismic section data. The present invention utilizes the good multi-scale feature of variational mode decomposition and the edge-preserving feature of the total variation regularization method, and can protect the boundary features of effective signals while suppressing random noise. The combined denoising method based on variational pattern decomposition and total variation regularization in the present invention, on the basis of variational patterns, combines it with the improved total variation regularization method to further improve the quality of the seismic section, The Baobian seismic records with high signal-to-noise ratio are obtained, which is beneficial to the subsequent seismic data processing and interpretation, making the results more reliable.

Description

technical field [0001] The invention relates to a joint denoising method for seismic data, which belongs to the technical field of seismic denoising. Background technique [0002] In the process of seismic data acquisition in the field, various random disturbances generated by the external environment will make the signal-to-noise ratio of the acquired seismic records low. Due to the limitation of seismic resolution and the existence of various noises, it is difficult to identify thin layers and complex structures on the seismic profile, and it is necessary to suppress noise through various technical means to improve the signal-to-noise ratio and resolution. Conventional methods often destroy effective information, such as the boundary features of seismic data, after processing to improve the signal-to-noise ratio, and the discontinuity information in seismic reflections is smoothed and blurred, so it is often difficult to take into account high signal-to-noise ratio and hi...

AI Technical Summary

Problems solved by technology

Conventional methods often destroy effective information, such as the boundary features of seismic data, after processing to improve the signal-to-noise ratio, and the discontinuity information in seismic reflections is smoothed and blurred, so it is often difficult to take into account high signal-to-noise ratio and high fidelity, which requires in-depth research to find a balance between the preservation of structural information and noise attenuation, in this regard, there is still room for improvement

Images