Results 21 to 30 of about 4,186 (258)
Regional-scale joint seismic body- and surface-wave travel time tomography
地球与行星物理论评, 2023 To make full use of seismograms to put tight constraints on the structure of subsurface and earthquake sources has always been the research focus in seismology.
Hongjian Fang +3 more
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Full Waveform Inversion for NDT using ultrasonic linear arrays
Research and Review Journal of Nondestructive Testing, 2023 Ultrasonic (UT) imaging is a widespread technique for nondestructive testing (NDT). The state-of-the-art UT image reconstruction algorithms are based on delay-and-sum (DAS) operations, which assume constant acoustic velocity across the tested objects ...
Daniel Rossato +5 more
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Convolution Coding and Amplitude Attenuation-Based Full Waveform Inversion
IEEE Access, 2020 Full waveform inversion (FWI) is a powerful method to reconstruct the properties of the subsurface media. However, the standard FWI is a non-unique and ill-posed inversion problem, which requires proper techniques to avoid cycle skipping phenomena ...
Shiqi Dong +4 more
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Full waveform inversion for bore reconstruction of woodwind-like instruments
Acta Acustica, 2021 The internal geometry of a wind instrument can be estimated from acoustic measurements. For woodwind instruments, this involves characterizing the inner shape (bore) but also the side holes (dimensions and location).
Ernoult Augustin +3 more
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On the use of neural networks for full waveform inversion
Computer Methods in Applied Mechanics and Engineering, 2023 Neural networks have recently gained attention in solving inverse problems. One prominent methodology are Physics-Informed Neural Networks (PINNs) which can solve both forward and inverse problems. In the paper at hand, full waveform inversion is the considered inverse problem. The performance of PINNs is compared against classical adjoint optimization,
Leon Herrmann +3 more
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Transfer Learning Enhanced Full Waveform Inversion*
2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2023 We propose a way to favorably employ neural networks in the field of non-destructive testing using Full Waveform Inversion (FWI). The presented methodology discretizes the unknown material distribution in the domain with a neural network within an adjoint optimization.
Stefan Kollmannsberger +2 more
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Frontiers in Earth Science, 2022 To better interpret the subsurface structures and characterize the reservoir, a depth model quantifying P-wave velocity together with additional rock’s physical parameters such as density, the S-wave velocity, and anisotropy is always preferred by ...
Zhonghan Liu +2 more
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Acoustic 2D full waveform inversion to solve gas cloud challenges
Annals of Geophysics, 2015 The existing conventional inversion algorithm does not provide satisfactory results due to the complexity of propagated wavefield though the gas cloud.
Srichand Prajapati, Deva Ghosh
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A Physics-Based Neural-Network Way to Perform Seismic Full Waveform Inversion
IEEE Access, 2020 Seismic full waveform inversion is a common technique that is used in the investigation of subsurface geology. Its classic implementation involves forward modeling of seismic wavefield based on a certain type of wave equation, which reflects the physics ...
Yuxiao Ren +4 more
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Reflection full waveform inversion [PDF]
Science China Earth Sciences, 2017 Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of
Gang Yao, Di Wu
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