Yanghua Wang

Professor

Imperial College London

United Kingdom

Research Interests

Explore related searches

Professors in United Kingdom

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Yanghua Wang is a Professor at Imperial College London, UK. His research areas encompass seismic characterization, waveform inversion techniques, and machine learning applications in geophysics. He has published extensively on topics such as seismic noise reduction, lithospheric seismic structures, and the evaluation of geological heterogeneities in reservoirs. His recent work includes innovative methodologies for data assimilation and analysis in seismic studies.

Articles (29)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Collaborators (3)

Chao Song

Imperial College London

UNITED KINGDOM

View details

Stephen Neethling

Imperial College London

UNITED KINGDOM

View details

Michael Warner

Imperial College London

UNITED KINGDOM

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Yanghua Wang

Research Interests

Explore related searches

Contact this professor

About

Articles (29)

Accelerating the convergence of physics-informed neural networks for seismic wave simulation

3D seismic characterization of magma plumbing components in the Tarim Large Igneous Province, north-central Tarim Basin, NW China

Seismic waveform inversion using envelope correlation with a learnable envelope power

Lithospheric Seismic Structure of the Anatolian Plate and Its Implications for Plateau Uplift: Evidence From Joint Inversion of Receiver Functions and Surface Waves

A strategy for preparing training data for machine learning for seismic noise reduction

Analytical Modeling of a Coil Sensor With a Ferrite Shell Encircling a Conductive Tube for Nondestructive Evaluation

Seismic full-waveform inversion regularized with a migration image

Screening Assessment of the Impact of Structural and Sedimentary Geological Heterogeneities on the Performance of an Ultra‐Deep Carbonate Reservoir, North‐Central Tarim Basin, Northwest China

AI-empowered Latent Four-dimensional Variational Data Assimilation for River Discharge Forecasting

Non-stationary inversion of seismic data for fracture compliances in azimuthally anisotropic mediag

The linear canonical W-transform

Synchrosqueezing voices through deep neural networks for horizon interpretation

Role of stress regime in azimuthal anisotropy of poroelastic media

A Hybrid Data‐Driven and Data Assimilation Method for Spatiotemporal Forecasting: PM2.5 Forecasting in China

A comparative study of a viscous froth lens in two and three dimensions

Seismic attribute-assisted seismic fault interpretation

Seismic reverse time migration based on biaxial wavefield decomposition

Seismic Full Waveform Inversion with Shot-encoding Using An improved L-BFGS Method

Seismic Reverse Time Migration With Random Boundary and Frequency Modulation

Weighted Envelope Correlation-Based Waveform Inversion Using Automatic Differentiation

Prediction of Permian karst reservoirs in the Yuanba gas field, northern Sichuan Basin, China

Nonstationary seismic–well tying with time-varying wavelets

The W transform with a chirp-modulated window

Prediction of permian karst reservoirs in the yuanba gas field, northern sichuan basin, China

Determination of the viscoelastic parameters for the generalized viscoelastic wave equation

Regularization of anisotropic full-waveform inversion with multiple parameters by adversarial neural networks

3-D Seismic Inversion by Model Parameterization With Fourier Coefficients

Simulating seismic multifrequency wavefields with the Fourier feature physics-informed neural network

Yield stress of foam flow in porous media: The effect of bubble trapping

Collaborators (3)

Chao Song

Stephen Neethling

Michael Warner

Make your next move.