Joint denoising method for seismic data

Abstract

The invention discloses a joint denoising method for seismic data, comprising the following steps: step 1, by utilizing the variation pattern decomposition of seismic data is decomposed to get new data; step 2, the invention uses the revised total variation method to denoise the new data; step 3, combining and refactoring the new data after the denoising, and getting the seismic section data. The invention utilizes a variation mode decomposition has good characteristic of multi-scale and the edge preserving property of total variation regularization method, thus the boundary feature of desired signal can be protected in suppressing random noise at the same time. The joint denoising method of the present invention based on the variational model decomposition and the total variation-based regularization, according to variational model, combining with modified total variation-based regularization, which further increases the quality of the seismic profile, and gets the high signal-noise ratio edge-preserving seismographic record. The joint denoising method for seismic data is used for processing and explanation of subsequent seismic data, and makes 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

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