Seismic Random Noise Suppression Method Jointly Constrained by Nuclear Norm and Generalized Total Variation

Abstract

The invention provides a seismic random noise suppression method constrained jointly by nuclear norm and generalized total variation, including (1) inputting a three-dimensional seismic data volume; (2) constructing an objective function; (3) adopting a split Bergman iteration strategy to convert the objective The function is decomposed into two sub-problems; (4) use the singular value soft thresholding algorithm to solve the sub-problem 1, and obtain the auxiliary variable matrix; (5) use the gradient projection algorithm to solve the sub-problem 2, and obtain the seismic data matrix; (6) judge Whether to stop the Bergman iteration, if stop the iteration, output the seismic data matrix; (7) Compute the whole seismic data volume to get the final denoised seismic data volume. The invention organically combines generalized total variation constraints in image processing, nuclear norm constraints in matrix analysis, and split Bergman iterative optimization theory, and is suitable for random noise suppression processing of seismic data, etc., effectively improving the signal-to-noise ratio of seismic data with fidelity.

Description

technical field [0001] The invention belongs to the technical field of petroleum geophysical exploration, and the specific technology is a seismic random noise suppression method constrained jointly by nuclear norm and generalized total variation, which can effectively suppress random noise in seismic data, improve the signal-to-noise ratio of seismic data, and maintain The local smoothness of seismic data improves the fidelity of seismic data. Background technique [0002] With the development of petroleum exploration to today, exploration and development are gradually shifting to complex, subtle, deep and unconventional oil and gas reservoirs, and the requirements for seismic data quality are getting higher and higher. Affected by the complex acquisition environment, the seismic data collected in the field often contain strong random noise, and even the effective information is completely submerged in severe cases. Seismic random noise suppression is an important problem ...

AI Technical Summary

Problems solved by technology

However, in many cases, the sparseness of seismic data may not be able to effectively represent the internal structural characteristics of seismic data, especially the waveform similarity between adjacent seismic traces

However, noise suppression methods based on the similarity of adjacent seismic trace waveforms, such as noise suppression with nuclear norm constraints, seldom take into account the local smoothness of seismic data, so that random noise suppresses seismic data at the edge of geological bodies. "staircase chatter" phenomenon

Images