Yangkang Chen

Publications

• Porosity and permeability prediction using a transformer and periodic long short-term network
• Domain knowledge-guided data-driven prestack seismic inversion using deep learning
• Denoising of distributed acoustic sensing data using supervised deep learning
• 3D true-amplitude elastic wave-vector decomposition in heterogeneous anisotropic media
• Imaging point diffractors using a low-rank approximation method
• Pyekfmm: A Python Package for 3D Fast-Marching-Based Travel-Time Calculation and its Applications in Seismology
• Denoising distributed acoustic sensing data using unsupervised deep learning
• Joint deblending and source time inversion
• Retrieving useful signals from highly corrupted erratic noise using robust residual dictionary learning
• Enhancing earthquake detection from distributed acoustic sensing data by coherency measure and moving-rank-reduction filtering
• Joint Reconstruction and Multiple Attenuation Using One-Step Randomized-Order Damped Rank Reduction Method
• Unsupervised deep-learning framework for 5D seismic denoising and interpolation
• Unsupervised deep learning for 3D interpolation of highly incomplete data
• Deep-learning missing well-log prediction via long short-term memory network with attention-period mechanism
• Pyseistr: A Python Package for Structural Denoising and Interpolation of Multichannel Seismic Data
• High-Fidelity Permeability and Porosity Prediction Using Deep Learning With the Self-Attention Mechanism
• Self-Attention Fully Convolutional DenseNets for Automatic Salt Segmentation
• Interpretable Unsupervised Learning Framework for Multidimensional Erratic and Random Noise Attenuation
• SLKNet: An attention-based deep-learning framework for downhole distributed acoustic sensing data denoising
• DRR: An open-source multi-platform package for the damped rank-reduction method and its applications in seismology
• EQCCT: A Production-Ready Earthquake Detection and Phase-Picking Method Using the Compact Convolutional Transformer
• Unsupervised Learning With Waveform Multibranch Attention Mechanism for Erratic Noise Attenuation
• Dictionary Learning for Single-Channel Passive Seismic Denoising
• Deep Nonlocal Regularizer: A Self-Supervised Learning Method for 3-D Seismic Denoising
• Deep Learning for P-Wave First-Motion Polarity Determination and Its Application in Focal Mechanism Inversion
• Revisiting two notable methods for improving the deblending performance of marine towed-streamer acquisition
• Streaming seismic attributes
• Deep learning with soft attention mechanism for small-scale ground roll attenuation
• A Reference Model of Crustal Thickness and Vp/Vs of Western Canada
• Deep Learning Peak Ground Acceleration Prediction Using Single-Station Waveforms
• Salt3DNet: A Self-Supervised Learning Framework for 3-D Salt Segmentation
• Capsule Neural Network Guided by Compact Convolutional Transformer for Discriminating Earthquakes from Quarry Blasts
• Protecting the weak signals in distributed acoustic sensing data processing using local orthogonalization: The FORGE data example
• Subsurface Natural Fracture Identification Using an Integrated Ensemble Learning Method
• DAS Vehicle Signal Extraction Using Machine Learning in Urban Traffic Monitoring
• Nonstationary adaptive S-wave leakage suppression of ocean-bottom node data
• TXED: The Texas Earthquake Dataset for AI
• SigRecover: Recovering Signal from Noise in Distributed Acoustic Sensing Data Processing
• Thousands of Induced Earthquakes per Month in West Texas Detected Using EQCCT
• SelfMixed: Self-supervised mixed noise attenuation for distributed acoustic sensing data
• High‐Resolution Mantle Transition Zone Imaging Using Multi‐Dimensional Reconstruction of SS Precursors
• One-Dimensional Dictionary Learning With Variational Sparse Representation for Single-Channel Seismic Denoising
• Transfer Learning for Seismic Phase Picking With Significantly Higher Precision in Faraway Seismic Stations
• Warped-Mapping-Based Multigather Joint Prestack Q Estimation
• Ground-truth-free deep learning for 3D seismic denoising and reconstruction with channel attention mechanism
• Near Real‐Time Earthquake Monitoring in Texas Using the Highly Precise Deep Learning Phase Picker
• Robust blind Q-compensated denoising for seismic data with adaptive structural regularization
• Deep Learning for Seismic Data Compression in Distributed Acoustic Sensing
• Unsupervised Deep Learning for DAS-VSP Denoising Using Attention-Based Deep Image Prior
• Closed-Loop Bayesian Generative Adversarial Network for Probabilistic Acoustic Impedance Inversion
• Uncovering the microseismic signals from noisy data for high-fidelity 3D source-location imaging using deep learning
• Nonstationary local slope estimation via forward-backward space derivative calculation
• Iterative Gaussian mixture model and multi‐channel attributes for arrival picking in extremely noisy environments
• Nonstationary predictive filtering for seismic random noise suppression — A tutorial
• Bandwidth-insensitive extended centroid frequency-shift method for near-surface Q estimation
• Geologic forward prospecting using improved tunnel-seismic-while-drilling method: A case study of the water supply project at Songhua River, Jilin, China
• An explicit stabilization scheme for Q-compensated reverse time migration
• Mesoscopic Wave-Induced Fluid Flow Effect Extraction by Using Frequency-Dependent Prestack Waveform Inversion
• Time-Lapse Seismic Difference-and-Joint Prestack AVA Inversion
• Building Complex Seismic Velocity Models for Deep Learning Inversion
• Dynamic Characterization of Reservoirs Constrained by Time-Lapse Prestack Seismic Inversion
• Retrieving the leaked signals from noise using a fast dictionary-learning method
• Robust damped rank-reduction method for simultaneous denoising and reconstruction of 5D seismic data
• Erratic and random noise attenuation using adaptive local orthogonalization
• Erratic noise suppression using iterative structure‐oriented space‐varying median filtering with sparsity constraint
• A fully unsupervised and highly generalized deep learning approach for random noise suppression
• Relative time seislet transform
• Prestack reverse time imaging in tunnels based on the decoupled nonconversion elastic-wave equation
• Dictionary learning with convolutional structure for seismic data denoising and interpolation
• Urban DAS Data Processing and Its Preliminary Application to City Traffic Monitoring
• Frequency-Independent Centroid Frequency Shift Method for Signal Attenuation Estimation
• Nonstationary local signal-and-noise orthogonalization
• A MATLAB code package for 2D/3D local slope estimation and structural filtering
• Deep-learning seismic full-waveform inversion for realistic structural models
• Robust local slope estimation by deep learning
• Spatiotemporal Variations in Earthquake Triggering Mechanisms During Multistage Hydraulic Fracturing in Western Canada
• 3D Microseismic Monitoring Using Machine Learning
• Seismic signal enhancement based on the low‐rank methods
• Pre‐stack seismic inversion based on ‐norm regularized logarithmic absolute misfit function
• EQConvMixer: A Deep Learning Approach for Earthquake Location From Single-Station Waveforms
• SCALODEEP: A Highly Generalized Deep Learning Framework for Real‐Time Earthquake Detection
• Real‐Time Earthquake Detection and Magnitude Estimation Using Vision Transformer
• Nonlocal Weighted Robust Principal Component Analysis for Seismic Noise Attenuation
• Convolutional neural networks for microseismic waveform classification and arrival picking
• Deep learning reservoir porosity prediction based on multilayer long short-term memory network
• Iterative deblending for simultaneous source data using the deep neural network
• Incoherent Noise Suppression of Seismic Data Based on Robust Low-Rank Approximation
• Deep denoising autoencoder for seismic random noise attenuation
• Self-training and learning the waveform features of microseismic data using an adaptive dictionary
• Automatic waveform-based source-location imaging using deep learning extracted microseismic signals
• Separation and imaging of seismic diffractions using a localized rank-reduction method with adaptively selected ranks
• Adaptive frequency-domain nonlocal means for seismic random noise attenuation
• Accelerated Signal-and-Noise Orthogonalization
• Time-lapse image registration by high-resolution time-shift scan
• Nonstationary local time-frequency transform
• Training deep networks with only synthetic data: Deep-learning-based near-offset reconstruction for (closed-loop) surface-related multiple estimation on shallow-water field data
• Fast local primary-and-multiple orthogonalization for surface-related multiple leakage estimation and extraction
• 5D dealiased seismic data interpolation using nonstationary prediction-error filter
• Enhanced low-rank matrix estimation for simultaneous denoising and reconstruction of 5D seismic data
• Improving receiver function imaging with high-resolution Radon transform
• Seismic imaging of simultaneous-source data using constrained least-squares reverse time migration
• An efficient and effective common reflection surface stacking approach using local similarity and plane-wave flattening
• Sparse inversion for water bubble removal and spectral enhancement
• Dictionary learning based on dip patch selection training for random noise attenuation
• Mathematical morphological filtering for linear noise attenuation of seismic data
• Seismic Noise Attenuation Using Unsupervised Sparse Feature Learning
• Shot-domain deblending using least-squares inversion
• A Physics-Based Neural-Network Way to Perform Seismic Full Waveform Inversion
• Unsupervised Seismic Random Noise Attenuation Based on Deep Convolutional Neural Network
• Effects of Kerogen Content on Elastic Properties‐Based on Artificial Organic‐Rich Shale (AORS)
• Robust Nonstationary Local Slope Estimation
• Surface-related multiple leakage extraction using local primary-and-multiple orthogonalization
• Denoising controlled-source electromagnetic data using least-squares inversion
• Automatic velocity analysis using high-resolution hyperbolic Radon transform
• Deep-Learning Inversion of Seismic Data
• Geological structure guided well log interpolation for high-fidelity full waveform inversion
• The Interpolation of Sparse Geophysical Data
• Velocity analysis using similarity-weighted semblance
• Velocity analysis of simultaneous-source data using high-resolution semblance—coping with the strong noise
• Hybrid-domain simultaneous-source full waveform inversion without crosstalk noise
• Full-waveform inversion and joint migration inversion with an automatic directional total variation constraint
• Enhancing seismic reflections using empirical mode decomposition in the flattened domain
• Iterative deblending using shaping regularization with a combined PNMO-MF-FK coherency filter
• Automatic Waveform Classification and Arrival Picking Based on Convolutional Neural Network
• Obtaining free USArray data by multi-dimensional seismic reconstruction
• Weak signal detection using multiscale morphology in microseismic monitoring
• Least-Squares Gaussian Beam Transform for Seismic Noise Attenuation
• Iterative Double Laplacian-Scaled Low-Rank Optimization for Under-Sampled and Noisy Signal Recovery
• Least-Squares Gaussian Beam Transform for Deblending Distance-Separated Simultaneous Sources
• Earthquake Detection and P-Wave Arrival Time Picking Using Capsule Neural Network
• Fast and Robust Low-Rank Approximation for Five-Dimensional Seismic Data Reconstruction
• Fast Dictionary Learning for High-Dimensional Seismic Reconstruction
• Gaussian beam reconstruction of seismic data
• Three-parameter prestack seismic inversion based on L1-2 minimization
• Normalized shaping regularization for robust separation of blended data
• Substituting smoothing with low-rank decomposition — Applications to least-squares reverse time migration of simultaneous source and incomplete seismic data
• A matrix-transform numerical solver for fractional Laplacian viscoacoustic wave equation
• Q-compensated viscoelastic reverse time migration using mode-dependent adaptive stabilization scheme
• CuQ-RTM: A CUDA-based code package for stable and efficient Q-compensated reverse time migration
• Estimation of δ and C13 of organic-rich shale from laser ultrasonic technique measurement
• Adaptive stabilization for Q-compensated reverse time migration
• EMD-seislet transform
• Data-driven multitask sparse dictionary learning for noise attenuation of 3D seismic data
• Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data
• Preserving the discontinuities in least-squares reverse time migration of simultaneous-source data
• Signal extraction using randomized-order multichannel singular spectrum analysis
• A high-resolution weighted AB semblance for dealing with amplitude-variation-with-offset phenomenon
• Simultaneous denoising and reconstruction of 5-D seismic data via damped rank-reduction method
• Robust Bidirectional Q-Compensated Denoising for Seismic Data With Adaptive Structural Regularization
• Simultaneous off-the-grid deblending and data reconstruction via unsupervised deep learning
• Pyntfa: A Python Package for Nonstationary Time–Frequency Analysis
• Thank You to Our Peer Reviewers in 2024
• Least-squares migration imaging of receiver functions
• Efficient Unsupervised Deep Learning for Simultaneous Seismic Noise Attenuation and Interpolation
• Leveraging overfitting for good — A two-step deep image prior model for seismic denoising
• Unsupervised deep learning for off-the-grid seismic reconstruction and denoising
• QBTransNet: Deep Learning Earthquake Distinction from Quarry Blasts Using Dilated Convolutional Transformer
• FaultVitNet: An Vision Transformer Assisted Network for 3D Fault Segmentation