Low-frequency seismic data are crucial for convergence of full-waveform inversion (FWI) to
reliable subsurface properties. However, it is challenging to acquire field data with an …

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 …

Building realistic and reliable models of the subsurface is the primary goal of seismic
imaging. We have constructed an ensemble of convolutional neural networks (CNNs) to …

Elastic properties from seismic data are important to determine subsurface hydrocarbon
presence and have become increasingly important for detailed reservoir characterization …

Target-oriented inversion (TOI) is an approach aimed at enhancing the ability of full-
waveform inversion (FWI) to achieve a high-resolution delineation of a reservoir. FWI has …

The anisotropic full-waveform inversion (FWI) is a seismic inverse problem for multiple
parameters, which aims to simultaneously reconstruct the vertical velocity and the …

Full‐waveform inversion (FWI) optimizes the subsurface properties of geophysical Earth
models in such a way that the modeled data, based on these subsurface properties, match …

Full waveform inversion in transversely isotropic media with a vertical symmetry axis
provides an opportunity to better match the data at the near and far offsets. However, multi …

Commonly-used seismic fracture characterization method assumes one single fracture set,
and this article aims to relax the limitation and demonstrate the feasibility of seismic …

Distributed acoustic sensing (DAS) technologies are now becoming widespread, particularly
in vertical seismic profiling (VSP). Being a spatially densely sampled recording of the …