Results 51 to 60 of about 4,442 (191)
Deep biosphere hosted by Archean granitoid basement of Deccan Traps showed depth‐wise microbial partitioning. Limited dispersion and variable selection control community assembly. Fewer abundant bacterial taxa were ubiquitous, while large numbers of rare taxa remained localized.
Rajendra Prasad Sahu +5 more
wiley +1 more source
Methods for Large Scale Hydraulic Fracture Monitoring
In this paper we propose computationally efficient and robust methods for estimating the moment tensor and location of micro-seismic event(s) for large search volumes. Our contribution is two-fold.
Aeron, Shuchin, Ely, Gregory
core +1 more source
A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials
This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu +13 more
wiley +1 more source
Denoising micro-seismic signals is paramount for ensuring reliable data for localizing mining-related seismic events and analyzing the state of rock masses during mining operations.
Jianxian Cai +4 more
doaj +1 more source
Rank-constrained seismic data interpolation and denoising
Rank-constrained seismic data interpolation methods have been used to cope with spatial sampling deficiencies, but some fundamental aspects are often neglected. Understanding their underlying features is the first step for developing new solutions to overcome existing limitations.
Quézia Cavalcante, Milton Porsani
openaire +1 more source
Fault Volume Digital Twin to Reproduce the Full Slip Spectrum, Scaling, and Statistical Laws
Abstract Seismological and geodetic observations of fault zones reveal diverse slip dynamics, scaling, and statistical laws. Existing mechanisms explain some but not all of these behaviors. We show that incorporating an off‐fault damage zone—characterized by distributed fractures surrounding a main fault—can reproduce many key features observed in ...
M. Almakari +9 more
wiley +1 more source
A Patch Based Denoising Method Using Deep Convolutional Neural Network for Seismic Image
The deep convolutional neural networks (CNNs) have been shown excellent performances for image denoising. However, the denoising CNN model trained with a specific noise level cannot deal with the images which have spatiotemporally variant random noise ...
Yushu Zhang +3 more
doaj +1 more source
Random Noise Attenuation Based on Residual Convolutional Neural Network in Seismic Datasets
Seismic random noise attenuation is a key step in seismic data processing. The random seismic data recorded by the detector tends to have strong noise, and this noisy seismic ratio can be seen as a low signal-to-noise ratio (SNR).
Liuqing Yang +4 more
doaj +1 more source
Abstract Detecting seismic activity on Saturn's icy moon Titan during the Dragonfly mission could provide crucial information on its internal structure. The geological complexity of the moon's surface suggests significant cyclic tidal deformation, likely leading to the fracturing of the ice shell.
L. Delaroque +9 more
wiley +1 more source
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 +10 more
doaj +1 more source

