A Generalizable Automated Geophysical Agent Workflow for Accessible Subsurface Hydrology Analysis
Available online 27 January 2026
Geophysical methods are central to subsurface imaging, yet their end-to-end workflows from data ingestion and inversion to petrophysical conversion remain inaccessible to non-specialists due to steep...
Deep Learning-Based Recovery of Weak PcP Phases from Noisy Seismic Records
Available online 20 January 2026
Detecting weak seismic phases in noisy recordings remains a major challenge in geophysics, especially for improving our understanding of the Earth’s deep interior. Among these phases, PcP, a P-wave...
Application of cross validation approaches to examine soft computing systems for forecasting soil liquefaction
December 2025
The objective of this research is to assess the liquefaction potential of typical penetration test data using five distinct machine learning models: linear regression (LR), random forest (RF), decision...
Integrating artificial intelligence and physics in surface-wave methods: From automated analysis to physically consistent inversion
December 2025
Surface waves provide critical constraints on the Earth’s near-surface and crustal structure, yet conventional analysis remains hampered by subjective dispersion picking, nonlinear and non-unique inversions,...
Leveraging automated machine learning (AutoML) for urban climate emulation
December 2025
highlights•Location-independent urban climate emulators are developed using AutoML.•A feature importance analysis framework is proposed for AutoML models.•Location and urban surface parameters improve...
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...
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...
Adaptive forward modeling and inversion in geoelectromagnetic methods: A review
September 2025
Over the past few decades, significant advancements have been achieved in geoelectromagnetic modeling and inversion, with numerous research findings published. The accuracy of geoelectromagnetic modeling...
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...
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...
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....