Poststack seismic data denoising based on 3-D convolutional neural network
Deep learning has been successfully applied to image denoising. In this study, we take one
step forward by using deep learning to suppress random noise in poststack seismic data …
step forward by using deep learning to suppress random noise in poststack seismic data …
Self-adaptive denoising net: Self-supervised learning for seismic migration artifacts and random noise attenuation
Seismic noise attenuation is essential for seismic interpretation and reservoir
characterization. Recently, many researchers have applied convolutional neural network …
characterization. Recently, many researchers have applied convolutional neural network …
Applications of savitzky-golay filter for seismic random noise reduction
Y Liu, B Dang, Y Li, H Lin, H Ma - Acta Geophysica, 2016 - Springer
Abstract This article utilizes Savitzky–Golay (SG) filter to eliminate seismic random noise.
This is a novel method for seismic random noise reduction in which SG filter adopts …
This is a novel method for seismic random noise reduction in which SG filter adopts …
Seismic noise filtering based on generalized regression neural networks
This paper deals with the application of Generalized Regression Neural Networks to the
seismic data filtering. The proposed system is a class of neural networks widely used for the …
seismic data filtering. The proposed system is a class of neural networks widely used for the …
Düşey Elektrik Sondajı Verilerinin Genelleştirilmiş Regresyon Sinir Ağları ile Ters Çözümü
Düşey elektrik sondajı (DES) verilerinin ters çözümü doğrusal olmayan bir problem olması
nedeniyle zor bir işlemdir. Bu çalışmada, genelleştirilmiş regresyon sinir ağlarının özdirenç …
nedeniyle zor bir işlemdir. Bu çalışmada, genelleştirilmiş regresyon sinir ağlarının özdirenç …