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Multi-task learning for low-frequency extrapolation and elastic model building from seismic data
Low-frequency (LF) signal content in seismic data as well as a realistic initial model are key
ingredients for robust and efficient full-waveform inversions (FWIs). However, acquiring LF …
ingredients for robust and efficient full-waveform inversions (FWIs). However, acquiring LF …
Deep learning for low-frequency extrapolation of multicomponent data in elastic FWI
H Sun, L Demanet - IEEE Transactions on Geoscience and …, 2021 - ieeexplore.ieee.org
Full-waveform inversion (FWI) strongly depends on an accurate starting model to succeed.
This is particularly true in the elastic regime: The cycle-skip** phenomenon is more …
This is particularly true in the elastic regime: The cycle-skip** phenomenon is more …
Improving the generalization of deep neural networks in seismic resolution enhancement
Seismic resolution enhancement is a key step for subsurface structure characterization.
Although many have proposed the use of deep learning (DL) for resolution enhancement …
Although many have proposed the use of deep learning (DL) for resolution enhancement …
Efficient progressive transfer learning for full-waveform inversion with extrapolated low-frequency reflection seismic data
The low-frequency seismic data provide crucial information for guiding the full-waveform
inversion (FWI), especially when strong reflectors exist in the velocity model. However …
inversion (FWI), especially when strong reflectors exist in the velocity model. However …
Deep learning-based low-frequency extrapolation and impedance inversion of seismic data
Seismic inversion is an indispensable part of the earth exploration to precisely obtain the
properties of subsurface media based on seismic data. However, the lack or inaccuracy of …
properties of subsurface media based on seismic data. However, the lack or inaccuracy of …
A convolutional neural network for creating near-surface 2D velocity images from GPR antenna measurements
I Iqbal, B ** problem in full-waveform inversion (FWI) can make the
iterative solution fall into local minima and produce an undesired inverted result when …
iterative solution fall into local minima and produce an undesired inverted result when …
Dual-band generative learning for low-frequency extrapolation in seismic land data
The presence of low-frequency energy in seismic data can help mitigate cycle-skip**
problems in full-waveform inversion. Unfortunately, the generation and recording of low …
problems in full-waveform inversion. Unfortunately, the generation and recording of low …