Method and device for denoising seismic data based on curvelet transform and clustering
A technology of curvelet transform and seismic data, applied in the field of signal processing, can solve problems such as inability to guarantee signal integrity
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Embodiment 1
[0056] figure 1 It is a flow chart of the seismic data denoising method based on curvelet transform and clustering provided by Embodiment 1 of the present invention.
[0057] refer to figure 1 , the method includes the following steps:
[0058] Step S101, acquiring first seismic data, and performing curvelet transformation on the first seismic data to obtain first curvelet transformation coefficients;
[0059] Here, the curvelet transform is the Curvelet transform. The first seismic data can refer to figure 2 .
[0060]Curvelet transform is a multi-scale anisotropic transform. Seismic data has the optimal sparse expression in the Curvelet domain, so random noise can be removed by thresholding. In the process of denoising, the selection of the preset threshold is very critical. A larger preset threshold can eliminate random noise, but at the same time, part of the effective signal will be lost, resulting in rough edges of seismic waves; a smaller preset threshold can The...
Embodiment 2
[0093] Figure 4 It is a schematic diagram of a seismic data denoising device based on curvelet transform and clustering provided in Embodiment 2 of the present invention.
[0094] refer to Figure 4 , the device includes a curvelet transform unit 10, a denoising processing unit 20, a clustering processing unit 30 and an inverse curvelet transform unit.
[0095] A curvelet transformation unit 10, configured to acquire first seismic data, and perform curvelet transformation on the first seismic data to obtain first curvelet transformation coefficients;
[0096] A denoising processing unit 20, configured to perform denoising processing on the first curvelet transform coefficients to obtain second curvelet transform coefficients;
[0097] A clustering processing unit 30, configured to perform clustering processing on the second curvelet transform coefficients to obtain a third curvelet transform coefficient;
[0098] The inverse curvelet transform unit 40 is configured to perf...
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