Results 31 to 40 of about 672 (170)

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

Wavelet‐Based Hurst Exponent Estimation

WIREs Computational Statistics, Volume 18, Issue 3, September 2026.
The review explores how wavelet‐based methods for estimating the Hurst parameters have developed from their theoretical roots to real‐world applications in fields like biology, engineering, and telecommunications. The review aims to highlight key techniques, compare their strengths and limitations, and point out challenges that still need to be ...
Dixon Vimalajeewa, Fabrizio Ruggeri, Brani Vidakovic   +2 more
wiley   +1 more source

A Machine Learning-Based Seismic Data Compression and Interpretation Using a Novel Shifted-Matrix Decomposition Algorithm

Applied Sciences, 2021
Seismic data provides integral information in geophysical exploration, for locating hydrocarbon rich areas as well as for fracture monitoring during well stimulation.
Milan Brankovic, Eduardo Gildin, Richard L. Gibson, Mark E. Everett   +3 more
doaj   +1 more source

Deep Seismic Tremors in the 2025 Santorini Seismo‐Volcanic Crisis Highlight Magmatic Feeding From a Mid‐Crustal Reservoir

Geophysical Research Letters, Volume 53, Issue 16, 28 August 2026.
Abstract An intense seismic swarm started on 27 January 2025 in the Santorini‐Amorgos region and lasted for approximately 45 days. A widely observed seismic tremor on 14 February 2025 suggested a volcanic origin for the 2025 Santorini crisis. Here we present an in‐depth combined seismological analysis of the earthquakes and tremors that occurred during
Jean Soubestre, Jannes Münchmeyer, Quentin Higueret, Nikolai M. Shapiro, Florent Brenguier, Anthony Lomax   +5 more
wiley   +1 more source

Seismic Random Noise Attenuation Based on PCC Classification in Transform Domain

IEEE Access, 2020
Random noise attenuation of seismic data is an essential step in the processing of seismic signals. However, as the exploration environment is becoming more and more complicated, the energy of valid signals is weaker and the signal to noise (SNR) is much
Yu Sang, Jinguang Sun, Xiangfu Meng, Haibo Jin, Yanfei Peng, Xinjun Zhang   +5 more
doaj   +1 more source

Locating Moonquakes With Single‐Station Seismology

Geophysical Research Letters, Volume 53, Issue 16, 28 August 2026.
Abstract Renewed international interest in lunar seismometer deployments requires robust single‐station location approach for the highly scattering Moon's crust. We present an event‐location strategy using major lunar event types recorded by the Apollo seismic network. Frequency‐dependent polarization analysis provides P‐wave back‐azimuth and incidence,
Doyeon Kim, Jung‐Hun Song, Nicholas C. Schmerr   +2 more
wiley   +1 more source

Non-Parametric Simultaneous Reconstruction and Denoising via Sparse and Low-Rank Regularization

Frontiers in Earth Science, 2022
Spatial irregular sampling and random noise are two important factors that restrict the accuracy of seismic imaging. Seismic wavefield reconstruction and denoising based on sparse representation are two popular antidotes to these two inevitable issues ...
Lingjun Meng, Zhanzhan Shi, Zhanzhan Shi, Yan Ye, Yuanjun Wang, Yuanjun Wang   +5 more
doaj   +1 more source

Dislocation Bands and Subboundaries in Experimentally Deformed Olivine

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 8, August 2026.
Abstract Transmission electron microscopy imaging of dislocations in olivine indicates heterogeneous structures and diversity of dislocation types. However, the volumes imaged at high resolution are smaller than individual grains even of fine‐grained samples.
Ulrich Faul
wiley   +1 more source

An adaptive parameter-free seismic data denoising approach by combining general cross-validation thresholding and pixel connectivity in synchrosqueezed domain

Earth, Planets and Space
High signal-to-noise ratio (SNR) seismic waveform data are conductive to various studies in seismology. Seismic denoising aims to enhance SNR by eliminating additive noise through signal processing while preserving important features of the seismic ...
Zhiyi Zeng, Peng Han, Wei Zhang, Yong Zhou, Xubiao Deng, Da Zhang, Yaqian Shi, Ying Chang, Hu Ji, Rui Dai, Jianzhong Zhang   +10 more
doaj   +1 more source

A Convolutional Neural Network to Spiking Neural Network Conversion Framework for Seismic Denoising

IEEE Access
This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus on two challenges: optimal spike encoding strategy adaptation for
Shuna Chen, Zhege Liu, Ziyu Qin, Xinyi Liu, Yajuan Xue, Junxing Cao   +5 more
doaj   +1 more source