Microseismic source imaging using physics-informed neural networks with hard constraints
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Xinquan, Alkhalifah, Tariq |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks
by: Huang, Xinquan, et al.
Published: (2023)
by: Huang, Xinquan, et al.
Published: (2023)
DiffPINN: Generative diffusion-initialized physics-informed neural networks for accelerating seismic wavefield representation
by: Cheng, Shijun, et al.
Published: (2025)
by: Cheng, Shijun, et al.
Published: (2025)
Physics-informed waveform inversion using pretrained wavefield neural operators
by: Huang, Xinquan, et al.
Published: (2025)
by: Huang, Xinquan, et al.
Published: (2025)
Physics-informed neural wavefields with Gabor basis functions
by: Alkhalifah, Tariq, et al.
Published: (2023)
by: Alkhalifah, Tariq, et al.
Published: (2023)
Efficient physics-informed neural networks using hash encoding
by: Huang, Xinquan, et al.
Published: (2023)
by: Huang, Xinquan, et al.
Published: (2023)
Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network
by: Cheng, Shijun, et al.
Published: (2025)
by: Cheng, Shijun, et al.
Published: (2025)
An effective physics-informed neural operator framework for predicting wavefields
by: Ma, Xiao, et al.
Published: (2025)
by: Ma, Xiao, et al.
Published: (2025)
Controllable seismic velocity synthesis using generative diffusion models
by: Wang, Fu, et al.
Published: (2024)
by: Wang, Fu, et al.
Published: (2024)
Geological and Well prior assisted full waveform inversion using conditional diffusion models
by: Wang, Fu, et al.
Published: (2024)
by: Wang, Fu, et al.
Published: (2024)
Diffusion-based subsurface CO$_2$ multiphysics monitoring and forecasting
by: Huang, Xinquan, et al.
Published: (2024)
by: Huang, Xinquan, et al.
Published: (2024)
Learned frequency-domain scattered wavefield solutions using neural operators
by: Huang, Xinquan, et al.
Published: (2024)
by: Huang, Xinquan, et al.
Published: (2024)
Joint Microseismic Event Detection and Location with a Detection Transformer
by: Yang, Yuanyuan, et al.
Published: (2023)
by: Yang, Yuanyuan, et al.
Published: (2023)
Diffusion priors enhanced velocity model building from time-lag images using a neural operator
by: Ma, Xiao, et al.
Published: (2025)
by: Ma, Xiao, et al.
Published: (2025)
Least-Squares-Embedded Optimization for Accelerated Convergence of PINNs in Acoustic Wavefield Simulations
by: Abedi, Mohammad Mahdi, et al.
Published: (2025)
by: Abedi, Mohammad Mahdi, et al.
Published: (2025)
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks
by: Agata, Ryoichiro, et al.
Published: (2026)
by: Agata, Ryoichiro, et al.
Published: (2026)
Propagating the prior from far to near offset: A self-supervised diffusion framework for progressively recovering near-offsets of towed-streamer data
by: Cheng, Shijun, et al.
Published: (2026)
by: Cheng, Shijun, et al.
Published: (2026)
Joint Microseismic Event Detection and Location With a Detection Transformer
by: Yuanyuan Yang, et al.
Published: (2025)
by: Yuanyuan Yang, et al.
Published: (2025)
A new practical and effective source-independent full-waveform inversion with a velocity-distribution supported deep image prior: Applications to two real datasets
by: Song, Chao, et al.
Published: (2025)
by: Song, Chao, et al.
Published: (2025)
Diffusion Model-Based Posterior Sampling in Full Waveform Inversion
by: Taufik, Mohammad H., et al.
Published: (2025)
by: Taufik, Mohammad H., et al.
Published: (2025)
Meta-PINN: Meta learning for improved neural network wavefield solutions
by: Cheng, Shijun, et al.
Published: (2024)
by: Cheng, Shijun, et al.
Published: (2024)
Full waveform inversion with CNN-based velocity representation extension
by: Mu, Xinru, et al.
Published: (2025)
by: Mu, Xinru, et al.
Published: (2025)
Gabor-Enhanced Physics-Informed Neural Networks for Fast Simulations of Acoustic Wavefields
by: Abedi, Mohammad Mahdi, et al.
Published: (2025)
by: Abedi, Mohammad Mahdi, et al.
Published: (2025)
A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
by: Abedi, Mohammad Mahdi, et al.
Published: (2026)
by: Abedi, Mohammad Mahdi, et al.
Published: (2026)
Propagating the prior from shallow to deep with a pre-trained velocity-model Generative Transformer network
by: Harsuko, Randy, et al.
Published: (2024)
by: Harsuko, Randy, et al.
Published: (2024)
Slope assisted Physics‐informed neural networks for seismic signal separation with applications on ground roll removal and interpolation
by: Francesco Brandolin, et al.
Published: (2025)
by: Francesco Brandolin, et al.
Published: (2025)
Inspired by machine learning optimization: can gradient-based optimizers solve cycle skipping in full waveform inversion given sufficient iterations?
by: Mu, Xinru, et al.
Published: (2025)
by: Mu, Xinru, et al.
Published: (2025)
Velocity model building from seismic images using a Convolutional Neural Operator
by: Ma, Xiao, et al.
Published: (2025)
by: Ma, Xiao, et al.
Published: (2025)
High-resolution velocity model estimation with neural operator and the time-shift imaging condition
by: Ma, Xiao, et al.
Published: (2025)
by: Ma, Xiao, et al.
Published: (2025)
Seismic inversion using hybrid quantum neural networks
by: Vashisth, Divakar, et al.
Published: (2025)
by: Vashisth, Divakar, et al.
Published: (2025)
Towards physics-informed neural networks for landslide prediction
by: Dahal, Ashok, et al.
Published: (2024)
by: Dahal, Ashok, et al.
Published: (2024)
Seismic wavefield solutions via physics-guided generative neural operator
by: Cheng, Shijun, et al.
Published: (2025)
by: Cheng, Shijun, et al.
Published: (2025)
Discovery of physically interpretable wave equations
by: Cheng, Shijun, et al.
Published: (2024)
by: Cheng, Shijun, et al.
Published: (2024)
Parameter-Efficient Transfer Learning for Microseismic Phase Picking Using a Neural Operator
by: Abdullin, Ayrat, et al.
Published: (2025)
by: Abdullin, Ayrat, et al.
Published: (2025)
Physics-informed conditional diffusion model for generalizable elastic wave-mode separation
by: Cheng, Shijun, et al.
Published: (2025)
by: Cheng, Shijun, et al.
Published: (2025)
Self-Flow-Matching assisted Full Waveform Inversion
by: Huang, Xinquan, et al.
Published: (2026)
by: Huang, Xinquan, et al.
Published: (2026)
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
by: Rice, Julian, et al.
Published: (2020)
by: Rice, Julian, et al.
Published: (2020)
Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
by: Zhu, Min, et al.
Published: (2023)
by: Zhu, Min, et al.
Published: (2023)
Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks
by: Chung, Jaehong, et al.
Published: (2023)
by: Chung, Jaehong, et al.
Published: (2023)
Velocity Model Building and Editing with Guided Denoising Diffusion Implicit Models
by: Brandolin, Francesco, et al.
Published: (2026)
by: Brandolin, Francesco, et al.
Published: (2026)
A Deep-Learning-Driven Optimization-Based Inverse Solver for Accelerating the Marchenko Method
by: Wang, Ning, et al.
Published: (2025)
by: Wang, Ning, et al.
Published: (2025)
Similar Items
-
GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks
by: Huang, Xinquan, et al.
Published: (2023) -
DiffPINN: Generative diffusion-initialized physics-informed neural networks for accelerating seismic wavefield representation
by: Cheng, Shijun, et al.
Published: (2025) -
Physics-informed waveform inversion using pretrained wavefield neural operators
by: Huang, Xinquan, et al.
Published: (2025) -
Physics-informed neural wavefields with Gabor basis functions
by: Alkhalifah, Tariq, et al.
Published: (2023) -
Efficient physics-informed neural networks using hash encoding
by: Huang, Xinquan, et al.
Published: (2023)