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Introduction to Denoising and Data Gap Filling of Seismic Reflection Data

2020
Seismic data is a mixture of several wanted (reflections, refractions) and unwanted (ground roll, diffractions, airwave etc.) signals. Different wave fields recorded by the seismic receiver can be seen from Fig. 1.1. Separation of wanted signal from such unwanted noises is therefore fundamental in geophysical signal processing.
R. K. Tiwari, R. Rekapalli
openaire   +1 more source

Application of improved AlexNet for seismic data denoising

International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 2023
ji shangran   +4 more
openaire   +1 more source

Similarity-Informed Self-Learning and Its Application on Seismic Image Denoising

IEEE Transactions on Geoscience and Remote Sensing, 2022
Naihao Liu   +2 more
exaly  

An adaptive seismic signal denoising method based on variational mode decomposition

Measurement: Journal of the International Measurement Confederation, 2021
Qiuzhan Zhou, Pingping Liu
exaly  

A denoising method of seismic data based on self-supervised learning

2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2022
Zhenbin Xia   +4 more
openaire   +1 more source

Study of Parameters in Dictionary Learning Method for Seismic Denoising

IEEE Transactions on Geoscience and Remote Sensing, 2022
Lakshmi Kuruguntla   +2 more
exaly  

Seismic data denoising by deep-residual networks

SEG Technical Program Expanded Abstracts 2018, 2018
Yuchen Jin   +4 more
openaire   +1 more source

Poststack Seismic Data Denoising Based on 3-D Convolutional Neural Network

IEEE Transactions on Geoscience and Remote Sensing, 2020
Dawei Liu, Xiaokai Wang, Wenchao Chen
exaly  

Seismic data inversion with curvelet denoising preconditioning

15th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 31 July-3 August 2017, 2017
V. M. Gomes   +5 more
openaire   +1 more source

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