Seismic Noise Suppression Method Based on Unequilibrium Depth Desired Block Log-Likelihood Network
A log-likelihood, noise suppression technology, applied in neural learning methods, biological neural network models, image data processing, etc., to avoid errors, improve block denoising effect, and improve denoising strength.
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[0069] 1. Working conditions
[0070] The experimental platform of the present invention adopts Intel(R) Core(TM) i5-7500 CPU@3.40GHz 3.40GHz, the memory is 8GB, the PC runs Windows 7, and the language is python language. The running environment is python==3.7, torch==1.0.1, scipy==1.3.1 and matplotlib.
[0071] 2. Experiment content and result analysis
[0072] The experimental effect of the present invention will be described below through experiments on synthetic data and field actual data:
[0073] like figure 2 As shown in the figure, 100 channels of synthetic clean seismic data contain 4 signal axes, which are respectively generated by rake wavelets with dominant frequencies of [19Hz, 18Hz, 17Hz and 16Hz]. The synthetic desert random noise is as follows: image 3 shown. Figure 4 for the image 3 take part in figure 2 The desert seismic data polluted by desert noise obtained in , the signal-to-noise ratio is -4dB. In this example, the denoising results of the me...
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