Results 61 to 70 of about 2,936 (205)

Space Correlation Constrained Physics Informed Neural Network for Seismic Tomography

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Physics‐informed neural networks (PINNs) integrate physical constraints with neural architectures and leverage their nonlinear fitting capabilities to solve complex inverse problems. Tomography serves as a classic example, aiming to reconstruct subsurface velocity models to improve seismic exploration.
Yonghao Wang, Zhuo Jia, Bowu Jiang, Wenkai Lu   +3 more
wiley   +1 more source

Feasibility study of full waveform inversion of Love-SH waves for detecting small-scale shallow anomalies

AIP Advances
In engineering surveys, conventional SH-wave seismic exploration methods exhibit limited resolution for detecting small-scale shallow anomalies, often failing to meet practical requirements.
Xu Sun, Wei Xu, Yingju Xiong, Yong Li, Xiaoqing Song   +4 more
doaj   +1 more source

DL-AWI: Adaptive Full Waveform Inversion Using a Deep Twin Neural Network

Geosciences
Full waveform inversion (FWI) iteratively improves the accuracy of the model by minimizing the discrepancies between the predicted and the observed data.
Chao Li, Yangkang Chen
doaj   +1 more source

Extrapolated full-waveform inversion: An image-space approach [PDF]

, 2018
The primary factor that prevents full waveform inversion from universal success is the band-limited nature of seismic data, resulting in a gap between the low wavenumber background velocity model and the high wavenumber seismic images.
Demanet, Laurent, Li, Yunyue
core   +1 more source

Transient Wave‐Based Data Assimilation for Localizing Multiple Leaks in Water Pipe Networks

Water Resources Research, Volume 62, Issue 4, April 2026.
Abstract Due to aging without timely renewal, hidden leaks continually occur in urban water distribution systems. Time‐domain full‐waveform inversion is a robust and flexible method for localizing multiple leaks in water pipe networks. However, as a deterministic estimator, this method assumes precise knowledge of model parameters and only gives a ...
Qiuru Chen, Jiangjiang Zhang, Huan‐Feng Duan, Tong‐Chuan Che   +3 more
wiley   +1 more source

Seismic Multi-Parameter Full-Waveform Inversion Based on Rock Physical Constraints

Applied Sciences
Seismic multi-parameter full-waveform inversion (FWI) integrating velocity and density parameters can fully use the kinematic and dynamic information of observed data to reconstruct underground models. However, seismic multi-parameter FWI is a highly ill-
Cen Cao, Deshan Feng, Jia Tang, Xun Wang
doaj   +1 more source

Studies on modified limited-memory BFGS method in full waveform inversion

Frontiers in Earth Science, 2023
Full waveform inversion (FWI) is a non-linear optimization problem based on full-wavefield modeling to obtain quantitative information of subsurface structure by minimizing the difference between the observed seismic data and the predicted wavefield. The
Meng-Xue Dai, Bing-Shou He, Bing-Shou He, Wei-Sen Huang   +3 more
doaj   +1 more source

A Semi‐Analytical Approach to Model Borehole Tube Waves for Interpretation of Downhole Seismic Data in Fault Zones

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 3, March 2026.
Abstract Understanding fault‐zone permeability is crucial in model‐based assessment of fluid migration, earthquake nucleation, and hydrothermal or hydrocarbon systems. Vertical seismic profiling (VSP) often captures Stoneley (tube) waves generated by fluid‐formation coupling in and around a borehole.
Shohei Minato, Ranajit Ghose, Tsutomu Kiguchi   +2 more
wiley   +1 more source

Full-Waveform Inversion of Two-Parameter Ground-Penetrating Radar Based on Quadratic Wasserstein Distance

Remote Sensing
Full-waveform inversion (FWI) is one of the most promising techniques in current ground-penetrating radar (GPR) inversion methods. The least-squares method is usually used, minimizing the mismatch between the observed signal and the simulated signal ...
Kai Lu, Yibo Wang, Heting Han, Shichao Zhong, Yikang Zheng   +4 more
doaj   +1 more source

Traveltime Tomography to Unravel the Chalk Group Structures at the Gassum CCS Site, Denmark

Geophysical Prospecting, Volume 74, Issue 3, March 2026.
ABSTRACT In carbon capture and storage (CCS) projects, it is important to investigate the seal properties, which often include the shallower part of the investigated area. Reflection seismic data in most of the Danish Basin appear less strong and coherent in the top 500 m, and hence reflectivity alone cannot be used to study the integrity of these ...
Emmanouil Konstantinidis, Michael Westgate, Alireza Malehmir, Ulrik Gregersen, Marie Keiding   +4 more
wiley   +1 more source