Results 41 to 50 of about 4,442 (191)

Denoising of Seismic Data Based on Block Dictionary Learning Theory

CT Lilun yu yingyong yanjiu, 2022
With the increasingly complex observation environment of oil and gas exploration, the seismic data collected are often mixed with various noise signals, resulting in the effective weak signal caused by the exploration target is covered, which seriously ...
Junjie ZHOU, Xiangling WU, Wenjie LI, Jinghe LI   +3 more
doaj   +1 more source

A Penalty Function Promoting Sparsity Within and Across Groups

, 2016
We introduce a new weakly-convex penalty function for signals with a group behavior. The penalty promotes signals with a few number of active groups, where within each group, only a few high magnitude coefficients are active.
Bayram, İlker, Bulek, Savaşkan
core   +1 more source

Application of 2D Variational Mode Decomposition Method in Seismic Signal Denoising

Elektronika ir Elektrotechnika
Seismic data are typical nonlinear and nonstationary data. In the acquisition and processing of seismic data, many factors interfere with it. Seismic data contain both effective waves and random noises, seriously affecting the quality of seismic data and
Chao Liu, Ziang Wang, Yaping Huang, Aiping Zeng, Hongming Fan   +4 more
doaj   +1 more source

A Joint Framework for Seismic Signal Denoising Using Total Generalized Variation and Shearlet Transform

IEEE Access, 2021
Seismic exploration is a remote-sensing tool applied in a great many projects for engineering and resource-exploration purposes. Random noise suppression is one of the key steps in seismic-signal processing, especially those with important details and ...
Xiannan Wang, Jian Zhang, Hao Cheng
doaj   +1 more source

Seismic Fault Preserving Diffusion

, 2007
This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We propose a pre-processing step based on a non linear diffusion filtering leading to a better detection of seismic faults. The non linear diffusion approaches are based on
Admasu, Bakker, Bakker, Berthoumieu, Bigün, Catte, Christian Germain, Dargent, Dargent, Dosil, Freeman, Gauthier, Gerig, Granlund, Koenderink, Marc Donias, Martens, Monteil, Naamen Keskes, Olivier Lavialle, Perona, Randen, Rao, Sebastien Guillon, Sorin Pop, Sønneland, Terebes, Terebes, Terebes, Van Ginkel, Van Kempen, Weickert, Weickert, Weickert, Weickert, Whitaker, Yannick Berthoumieu   +36 more
core   +4 more sources

Ground-Truth-Free 3D Seismic Denoising Based on Diffusion Models: Achieving Effective Constraints Through Embedded Self-Supervised Noise Modeling

Remote Sensing
Three-dimensional (3D) seismic data, essential for revealing subsurface structures and exploring oil and gas resources, are often contaminated by noise with an unknown prior distribution.
Zhonghan Zhang, Guihe Qin, Yanhua Liang, Minghui Sun, Yingqing Wang, Jiaru Song   +5 more
doaj   +1 more source

Random Noise Suppression Method of Micro-Seismic Data Based on CEEMDAN-FE-TFPF

Applied Sciences, 2022
As rock fractures caused by micro-seismic events has potential safety hazards to underground workers, it is often necessary to accurately locate the micro-seismic source for hidden danger investigation.
Jianting Chen, Jianfei Fu, Hao Cheng, Sanshi Jia, Yuzeng Yao, Di Yan   +5 more
doaj   +1 more source

Bolt Detection Signal Analysis Method Based on ICEEMD

, 2018
The construction quality of the bolt is directly related to the safety of the project, and as such, it must be tested. In this paper, the improved complete ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt detection signal ...
Guo, Chunhui, Xie, Xin, Yang, Zhengyu, Zhang, Zhan   +3 more
core   +2 more sources

SeisDeNet: an intelligent seismic data Denoising network for the internet of things

Journal of Cloud Computing: Advances, Systems and Applications, 2023
Deep learning (DL) has attracted tremendous interest in various fields in last few years. Convolutional neural networks (CNNs) based DL architectures have been successfully applied in computer vision, medical image processing, remote sensing, and many ...
Yu Sang, Yanfei Peng, Mingde Lu, Chen Zhao, Liquan Li, Tianjiao Ma   +5 more
doaj   +1 more source

Removing multiple types of noise of distributed acoustic sensing seismic data using attention-guided denoising convolutional neural network

Frontiers in Earth Science, 2023
In recent years, distributed optical fiber acoustic sensing (DAS) technology has been increasingly used for vertical seismic profile (VSP) exploration. Even though this technology has the advantages of high spatial resolution, strong resistance to high ...
Cong Wang, Xingguo Huang, Yue Li, Kristian Jensen   +3 more
doaj   +1 more source