Papers Seismic Imaging
“Seismic Imaging” 태그가 달린 논문 44편 · 필터 해제
Diffusion prior as a direct regularization term for FWI
Diffusion models have recently shown promise as powerful generative priors for inverse problems. However, conventional applications require solving the full reverse diffusion process and operating on noisy intermediate s…
DenoisingSeismic ImagingGood Things Come in Pairs: Paired Autoencoders for Inverse Problems
In this book chapter, we discuss recent advances in data-driven approaches for inverse problems. In particular, we focus on the \emph{paired autoencoder} framework, which has proven to be a powerful tool for solving inve…
Seismic ImagingNoisier2Inverse: Self-Supervised Learning for Image Reconstruction with Correlated Noise
We propose Noisier2Inverse, a correction-free self-supervised deep learning approach for general inverse prob- lems. The proposed method learns a reconstruction function without the need for ground truth samples and is a…
Image ReconstructionSeismic ImagingSelf-Supervised LearningData-Driven and Theory-Guided Pseudo-Spectral Seismic Imaging Using Deep Neural Network Architectures
Full Waveform Inversion (FWI) reconstructs high-resolution subsurface models via multi-variate optimization but faces challenges with solver selection and data availability. Deep Learning (DL) offers a promising alternat…
Seismic ImagingSynergizing Deep Learning and Full-Waveform Inversion: Bridging Data-Driven and Theory-Guided Approaches for Enhanced Seismic Imaging
This review explores the integration of deep learning (DL) with full-waveform inversion (FWI) for enhanced seismic imaging and subsurface characterization. It covers FWI and DL fundamentals, geophysical applications (vel…
GeophysicsSeismic ImagingEnhancing Robustness Of Digital Shadow For CO2 Storage Monitoring With Augmented Rock Physics Modeling
To meet climate targets, the IPCC underscores the necessity of technologies capable of removing gigatonnes of CO2 annually, with Geological Carbon Storage (GCS) playing a central role. GCS involves capturing CO2 and inje…
Seismic ImagingAdvancing Geological Carbon Storage Monitoring With 3d Digital Shadow Technology
Geological Carbon Storage (GCS) is a key technology for achieving global climate goals by capturing and storing CO2 in deep geological formations. Its effectiveness and safety rely on accurate monitoring of subsurface CO…
Decision MakingSeismic ImagingProbabilistic Joint Recovery Method for CO$_2$ Plume Monitoring
Reducing CO$_2$ emissions is crucial to mitigating climate change. Carbon Capture and Storage (CCS) is one of the few technologies capable of achieving net-negative CO$_2$ emissions. However, predicting fluid flow patter…
Seismic ImagingUncertainty QuantificationA Novel Diffusion Model for Pairwise Geoscience Data Generation with Unbalanced Training Dataset
Recently, the advent of generative AI technologies has made transformational impacts on our daily lives, yet its application in scientific applications remains in its early stages. Data scarcity is a major, well-known ba…
GeophysicsSeismic ImagingFully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data
The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for (sub-) surface data segmentation. Recently developed fully reversible…
Dimensionality ReductionSeismic ImagingStochastic full waveform inversion with deep generative prior for uncertainty quantification
To obtain high-resolution images of subsurface structures from seismic data, seismic imaging techniques such as Full Waveform Inversion (FWI) serve as crucial tools. However, FWI involves solving a nonlinear and often no…
Bayesian InferenceSeismic ImagingUncertainty QuantificationVariational InferenceIntegrating Physics of the Problem into Data-Driven Methods to Enhance Elastic Full-Waveform Inversion with Uncertainty Quantification
Full-Waveform Inversion (FWI) is a nonlinear iterative seismic imaging technique that, by reducing the misfit between recorded and predicted seismic waveforms, can produce detailed estimates of subsurface geophysical pro…
Deep LearningProbabilistic Deep LearningSeismic ImagingUncertainty QuantificationInvertibleNetworks.jl: A Julia package for scalable normalizing flows
InvertibleNetworks.jl is a Julia package designed for the scalable implementation of normalizing flows, a method for density estimation and sampling in high-dimensional distributions. This package excels in memory effici…
Density EstimationSeismic ImagingIntraSeismic: a coordinate-based learning approach to seismic inversion
Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As such, it is widely utilized in the ener…
Data CompressionSeismic ImagingSeismic InversionUncertainty QuantificationAbsorption-Constrained Wavelet Power Spectrum Inversion for Robust Q Extraction From VSP Data
Extracting a reliable model of quality factor Q from the spectral information of seismic signals is a significantly important step for seismic imaging and reservoir characterization. However, the conventional Q estimatio…
GeophysicsSeismic ImagingThree-Dimensional Ultrasound Matrix Imaging
Matrix imaging paves the way towards a next revolution in wave physics. Based on the response matrix recorded between a set of sensors, it enables an optimized compensation of aberration phenomena and multiple scattering…
3D geometrySeismic ImagingAn Analysis of Physics-Informed Neural Networks
Whilst the partial differential equations that govern the dynamics of our world have been studied in great depth for centuries, solving them for complex, high-dimensional conditions and domains still presents an incredib…
Seismic ImagingDe-risking Carbon Capture and Sequestration with Explainable CO2 Leakage Detection in Time-lapse Seismic Monitoring Images
With the growing global deployment of carbon capture and sequestration technology to combat climate change, monitoring and detection of potential CO2 leakage through existing or storage induced faults are critical to the…
Binary ClassificationSeismic ImagingDe-risking geological carbon storage from high resolution time-lapse seismic to explainable leakage detection
Geological carbon storage represents one of the few truly scalable technologies capable of reducing the CO2 concentration in the atmosphere. While this technology has the potential to scale, its success hinges on our abi…
Seismic ImagingSolving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator
In the study of subsurface seismic imaging, solving the acoustic wave equation is a pivotal component in existing models. The advancement of deep learning enables solving partial differential equations, including wave eq…
Computational EfficiencyOperator learningSeismic Imaging