PINNeik: Eikonal solution using physics-informed neural networks

U bin Waheed, E Haghighat, T Alkhalifah… - Computers & …, 2021 - Elsevier
The eikonal equation is utilized across a wide spectrum of science and engineering
disciplines. In seismology, it regulates seismic wave traveltimes needed for applications like …

Regularized elastic full-waveform inversion using deep learning

Z Zhang, T Alkhalifah - Advances in subsurface data analytics, 2022 - Elsevier
Elastic full-waveform inversion, which aims to match the waveforms of prestack seismic data,
potentially provides more accurate high-resolution reservoir characterization from seismic …

PINNtomo: Seismic tomography using physics-informed neural networks

U Waheed, T Alkhalifah, E Haghighat, C Song… - arxiv preprint arxiv …, 2021 - arxiv.org
Seismic traveltime tomography using transmission data is widely used to image the Earth's
interior from global to local scales. In seismic imaging, it is used to obtain velocity models for …

Joint inversion of multiple geophysical and petrophysical data using generalized fuzzy clustering algorithms

J Sun, Y Li - Geophysical Supplements to the Monthly Notices of …, 2016 - academic.oup.com
Joint inversion that simultaneously inverts multiple geophysical data sets to recover a
common Earth model is increasingly being applied to exploration problems. Petrophysical …

Ntfields: Neural time fields for physics-informed robot motion planning

R Ni, AH Qureshi - arxiv preprint arxiv:2210.00120, 2022 - arxiv.org
Neural Motion Planners (NMPs) have emerged as a promising tool for solving robot
navigation tasks in complex environments. However, these methods often require expert …

Adjoint‐state teleseismic traveltime tomography: Method and application to Thailand in Indochina Peninsula

J Chen, S Wu, M Xu, M Nagaso, J Yao… - Journal of …, 2023 - Wiley Online Library
We propose a novel framework for teleseismic traveltime tomography that requires no ray
tracing. The tomographic inverse problem is formulated as an Eikonal equation‐constrained …

A neural network based global traveltime function (GlobeNN)

MH Taufik, U Waheed, TA Alkhalifah - Scientific Reports, 2023 - nature.com
Global traveltime modeling is an essential component of modern seismological studies with
a whole gamut of applications ranging from earthquake source localization to seismic …

Laplace HypoPINN: physics-informed neural network for hypocenter localization and its predictive uncertainty

M Izzatullah, IE Yildirim, UB Waheed… - … Learning: Science and …, 2022 - iopscience.iop.org
Several techniques have been proposed over the years for automatic hypocenter
localization. While those techniques have pros and cons that trade-off computational …

A fast marching algorithm for the factored eikonal equation

E Treister, E Haber - Journal of Computational physics, 2016 - Elsevier
The eikonal equation is instrumental in many applications in several fields ranging from
computer vision to geoscience. This equation can be efficiently solved using the iterative …

Upwind, no more: Flexible traveltime solutions using physics-informed neural networks

MH Taufik, U bin Waheed… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The eikonal equation plays an important role across multidisciplinary branches of science
and engineering. In geophysics, the eikonal equation and its characteristics are used in …