[HTML][HTML] State-of-The-Art application and challenges of optical fibre distributed acoustic sensing in civil engineering

MF Ghazali, H Mohamad, MYM Nasir, A Hamzh… - Optical Fiber …, 2024 - Elsevier
Abstract Distributed Acoustic Sensing (DAS) technology has rapidly gained prominence
across various applications. Integrating DAS with fibre-optic cables can bolster critical …

Noise attenuation in distributed acoustic sensing data using a guided unsupervised deep learning network

OM Saad, M Ravasi, T Alkhalifah - Geophysics, 2024 - library.seg.org
Distributed acoustic sensing (DAS) is a promising technology introducing a new paradigm in
the acquisition of high-resolution seismic data. However, DAS data often show weak signals …

Three-dimensional distributed acoustic sensing at the Sanford Underground Research Facility

E Cunningham, N Lord, D Fratta, A Chavarria… - Geophysics, 2023 - library.seg.org
Distributed acoustic sensing (DAS) is a valuable tool for monitoring seismic signals as it
provides high spatial and temporal resolution strain sensing along the length of a fiber-optic …

Mitigation of numerical dispersion in seismic data in spectral domain with neural networks

K Gadylshin, E Gondyul, V Lisitsa, K Gadylshina… - Soil Dynamics and …, 2024 - Elsevier
Seismic modeling has various engineering applications, including exploration seismology,
seismic monitoring of greenhouse gas sequestration, and earthquake engineering …

Classification of images derived from submarine fibre optic sensing: detecting broadband seismic activity from hydroacoustic signals

I Matthaiou, A Masoudi, E Araki… - Geophysical Journal …, 2025 - academic.oup.com
Distributed acoustic sensing (DAS) is an optoelectronic technology that utilizes fibre optic
cables to detect disturbances caused by seismic waves. Using DAS, seismologists can …

Unsupervised denoising for seismic data with complementary mask blind spot strategy

L Gao, D Liang, F Min - Journal of Applied Geophysics, 2024 - Elsevier
Attenuation of incoherent noise can effectively improve signal-to-noise ratio (SNR) of
seismic data. Recently, unsupervised denoising methods have emerged as solutions for the …

Unsupervised learning with waveform multi-branch attention mechanism for erratic noise attenuation

C Fu, Y Huo, G Li, Y Chen - IEEE Transactions on Geoscience …, 2024 - ieeexplore.ieee.org
High signal-to-noise ratio (SNR) seismic data are crucial for oil and gas exploration,
particularly for advanced high-precision migration processes and sophisticated reservoir …

Physics-guided full waveform inversion using Encoder-Solver convolutional neural networks

MM Goren, E Treister - Inverse Problems, 2024 - iopscience.iop.org
Abstract Full Waveform Inversion (FWI) is an inverse problem for estimating the wave
velocity distribution in a given domain, based on observed data on the boundaries. The …

Efficient signal-to-noise ratio enhancement model for severely contaminated distributed acoustic sensing seismic data based on heterogeneous knowledge distillation

Q Feng, S Wang, Y Li - Geophysics, 2024 - library.seg.org
Distributed acoustic sensing (DAS) is an emerging seismic acquisition technique with great
practical potential. However, various types of noise seriously corrupt DAS signals, making it …

Artificial-neural-network-assisted distributed directional optical fiber torsion sensor with the SSAF-based Sagnac interferometer

J Cao, B Wang, B Huang, S Lou… - Journal of Lightwave …, 2024 - ieeexplore.ieee.org
A distributed optical fiber torsion sensor assisted by an artificial neural network (ANN) is
designed based on the single stress-applying fiber (SSAF)-based Sagnac interferometer …