Well-constrained velocity spectrum pickup method for low-SNR (signal-to-noise ratio) seismic data

Abstract

The invention provides a well-constrained velocity spectrum pickup method for low-SNR (signal-to-noise ratio) seismic data, and belongs to the field of seismic data processing. The method comprises (1), well logging preprocessing: input interval transit time or acoustic velocity is corrected, and a corrected acoustic velocity is obtained; (2), acoustic logging data shallow layer compensation and downward extension processing are performed on the corrected acoustic velocity, and the acoustic velocity subjected to shallow layer compensation and downward extension is obtained; (3), time-depth conversion is performed on the acoustic velocity subjected to shallow layer compensation and downward continuation to obtain an interval velocity, and the interval velocity is subjected to root-mean-square velocity conversion to obtain a root-mean-square velocity; (4), projection of the root-mean-square velocity on the velocity spectrum is acquired. With adoption of the method, pickup randomness is reduced, and the velocity pickup accuracy is improved.

Description

technical field [0001] The invention belongs to the field of seismic data processing, and in particular relates to a well-constrained velocity spectrum picking method for low signal-to-noise ratio seismic data. Background technique [0002] Spectrum-based velocity analysis is an important means to obtain stacking velocity in seismic data processing, and a basic tool for velocity analysis. This method picks stacking velocity according to the strength of energy groups in the velocity spectrum. For seismic data with low signal-to-noise ratio , the energy clusters in the velocity spectrum are very weak, or even have no energy clusters, or false energy clusters appear. Correction, denoising, etc. Although the latter can improve the quality of the velocity spectrum to a certain extent, it requires a lot of manpower and material resources, and often has little effect on some particularly poor seismic data. [0003] The velocity spectrum of seismic data with low signal-to-noise rat...

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Problems solved by technology

[0002] Spectrum-based velocity analysis is an important means to obtain the stacking velocity in seismic data processing, and is a basic tool for velocity analysis. This method picks up the stacking velocity according to the strength of the energy group in the velocity spectrum. For seismic data with low signal-to-noise ratio , the energy clusters in the velocity spectrum are very weak, or even there are no energy clusters, or false energy clusters appear. Correction, denoising, etc. Although the latter can improve the quality of the velocity spectrum to a certain extent, it requires a lot of manpower and material resources, and often has little effect on some particularly poor seismic data

[0003] The velocity spectrum of seismic data with low signal-to-noise ratio generally has problems such as weak energy and out-of-focus, which cause great difficulties in velocity picking, and the accuracy of velocity picking is low. At present, there is no particularly effective method

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