Seismic Wavefield

Seismic wavefield analysis focuses on understanding and manipulating the propagation of seismic waves through the Earth, primarily to image subsurface structures and identify resources like hydrocarbons or monitor geological processes such as carbon storage. Current research emphasizes the application of machine learning, particularly deep neural networks (including convolutional neural networks, physics-informed neural networks, and Fourier neural operators), to improve data processing tasks such as denoising, deblending, interpolation, and inversion. These advancements aim to enhance the accuracy, efficiency, and robustness of seismic imaging and interpretation, leading to better subsurface models and improved decision-making in various geoscience applications.

Papers

September 13, 2024

Using Convolutional Neural Networks for Denoising and Deblending of Marine Seismic Data
Sigmund Slang, Jing Sun, Thomas Elboth, Steven McDonald, Leiv-J. Gelius
Convolutional Neural Network Denoising Process Seismic Data Seismic Wavefield

January 23, 2024

Gas trap prediction from 3D seismic and well test data using machine learning
Dmitry Ivlev
Machine Learning Test Data Reservoir Pressure Well Data Seismic Wavefield 3D Seismic Gas Reservoir

August 10, 2023

GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks
Xinquan Huang, Tariq Alkhalifah
Neural Network Physic Informed Neural Network Network Programming Gabor Filter Full Waveform Inversion Wavefield Solution Seismic Wavefield

July 18, 2023

Solving multiphysics-based inverse problems with learned surrogates and constraints
Ziyi Yin, Rafael Orozco, Mathias Louboutin, Felix J. Herrmann
Participation Constraint Surrogate Assisted Version Geological Carbon Storage Seismic Wavefield

May 25, 2023

PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks
Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah
Neural Network Theoretical Physic Seismic Data Reg PINNs Wavefield Solution Seismic Wavefield

April 6, 2023

Generalization with Reverse-Calibration of Well and Seismic Data Using Machine Learning Methods for Complex Reservoirs Predicting During Early-Stage Geological Exploration Oil Field
Dmitry Ivlev
Machine Learning Strong Generalization Human Prediction Self Calibration Geophysical Data Seismic Wavefield Gas Reservoir

December 27, 2022

S2S-WTV: Seismic Data Noise Attenuation Using Weighted Total Variation Regularized Self-Supervised Learning
Zitai Xu, Yisi Luo, Bangyu Wu, Deyu Meng
Neural Network Self Supervised Seismic Wavefield

September 25, 2022

Solving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator
Bian Li, Hanchen Wang, Shihang Feng, Xiu Yang, Youzuo Lin
Fourier Neural Operator Wave Equation Seismic Wave Seismic Wavefield

July 20, 2022

Deep Preconditioners and their application to seismic wavefield processing
Matteo Ravasi
Application Proficiency Inverse Problem Seismic Data Neural Preconditioners Seismic Wavefield Sparsifying Transform Physic Based Inverse Problem

Seismic Wavefield

Papers

Using Convolutional Neural Networks for Denoising and Deblending of Marine Seismic Data

Gas trap prediction from 3D seismic and well test data using machine learning

GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks

Solving multiphysics-based inverse problems with learned surrogates and constraints

PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks

Generalization with Reverse-Calibration of Well and Seismic Data Using Machine Learning Methods for Complex Reservoirs Predicting During Early-Stage Geological Exploration Oil Field

S2S-WTV: Seismic Data Noise Attenuation Using Weighted Total Variation Regularized Self-Supervised Learning

Solving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator

Deep Preconditioners and their application to seismic wavefield processing