3D geophysical data joint inversion with the concept of multimodal fusion
September 2025
•Geophysical multi-physical joint inversion is formulated as a multimodal fusion problem, so tools developed for machine learning can be adopted.•A deep neural network is proposed to take multiple types...
Recovering missing regions of earth magnetic anomaly grid data (EMAG2) using RePaint based on diffusion model
June 2025
•We employed a diffusion-based model, RePaint, to recover the missing data in EMAG2.•A recovered complete version of EMAG2 has been released along with open-source code....
Using multi-regression machine learning to assess uncertainties of surface wave phase velocities derived from ambient noise
June 2025
With the increasing use of ambient seismic noise to investigate the crust and uppermost mantle structures, accurately estimating the uncertainties of surface wave phase velocities derived from noise...
BDCNet: An effective method for extracting the borehole dispersion curves and obtaining formation P- and S-wave velocities
June 2025
This study introduces Borehole Dispersion Curves Network (BDCNet), a deep learning framework built on the DeepLabV3+ architecture, designed to automate the extraction and classification of borehole...
Resolving shallow shear wave velocity structure and radial anisotropy beneath the Los Angeles basin from ambient seismic noise
September 2025
The Los Angeles basin, situated at the transform margin between the North American and Pacific plates, has experienced complex tectonic evolution, leading to significant hydrocarbon accumulation and...
MSSInvNet: a multi-component surface-wave dispersion spectrogram inversion network
September 2025
The estimation of near-surface shear-wave (Vs) velocity models plays a critical role in environmental and engineering geophysics. Traditional surface-wave methods usually rely on the manual extraction...