Fornaro, G.,
Atzori, S.,
Calo, F.,
Reale, D.,
Salvi, S.,
Inversion of Wrapped Differential Interferometric SAR Data for Fault
Dislocation Modeling,
GeoRS(50), No. 6, June 2012, pp. 2175-2184.
IEEE DOI
1205
BibRef
Yang, S.,
Wang, J.,
Zhou, J.,
Zhu, T.,
Wang, H.,
An Efficient Algorithm of Both Frechet Derivative and Inversion of
MCIL Data in a Deviated Well in a Horizontally Layered TI Formation
Based on TLM Modeling,
GeoRS(52), No. 11, November 2014, pp. 6911-6923.
IEEE DOI
1407
Computational modeling
BibRef
Shin, Y.H.[Young Hong],
Shum, C.K.,
Braitenberg, C.[Carla],
Estimating the 3D fold structure of the crust-mantle boundary,
SPIE(Newsroom), November 23, 2015
DOI Link
1602
Deep-seated lithospheric folding can be revealed using a method that
combines gravity inversion calculations and isostatic analyses.
BibRef
Gao, Z.,
Pan, Z.,
Gao, J.,
Multimutation Differential Evolution Algorithm and Its Application to
Seismic Inversion,
GeoRS(54), No. 6, June 2016, pp. 3626-3636.
IEEE DOI
1606
evolutionary computation
BibRef
Gao, Z.,
Pan, Z.,
Gao, J.,
Wu, R.,
Frequency Controllable Envelope Operator and Its Application in
Multiscale Full-Waveform Inversion,
GeoRS(57), No. 2, February 2019, pp. 683-699.
IEEE DOI
1901
Frequency control, Computational modeling, Data models,
Optimization methods, Estimation, Inverse problems, Cycle skipping,
multiscale scheme
BibRef
Yu, Z.,
Zhou, J.,
Fang, Y.,
Hu, Y.,
Liu, Q.H.,
Through-Casing Hydraulic Fracture Evaluation by Induction Logging II:
The Inversion Algorithm and Experimental Validations,
GeoRS(55), No. 2, February 2017, pp. 1189-1198.
IEEE DOI
1702
fast Fourier transforms
BibRef
Al-Battal, A.F.,
Mousa, W.A.,
The Design of 2-D Explicit Depth Extrapolators Using the Cauchy Norm,
GeoRS(55), No. 5, May 2017, pp. 3029-3036.
IEEE DOI
1705
hydrocarbon reservoirs, 2-D explicit depth extrapolators,
Cauchy norm, Marmousi model data set, SEG/EAGE salt model,
adaptive damping, coefficients yielding, depth migration,
filter coefficients, paper, extrapolators,
poststack depth migrations, recursive migration process,
wavefield extrapolations, Design methodology, Extrapolation,
Finite impulse response filters, Frequency-domain analysis,
Imaging, Inverse problems, Passband, Cauchy norm,
finite impulse response (FIR) filters,
regularized least square (RLS), seismic imaging, wavefield, extrapolation
BibRef
Bordignon, F.L.,
de Figueiredo, L.P.,
Azevedo, L.,
Soares, A.,
Roisenberg, M.,
Neto, G.S.,
Hybrid Global Stochastic and Bayesian Linearized Acoustic Seismic
Inversion Methodology,
GeoRS(55), No. 8, August 2017, pp. 4457-4464.
IEEE DOI
1708
Bayes methods, Computational modeling, Correlation,
Covariance matrices, Data models, Stochastic processes,
Uncertainty, Bayesian inversion, geostatistics,
linearized inversion, seismic inversion, stochastic inversion,
uncertainty, modeling
BibRef
Lan, T.,
Liu, H.,
Liu, N.,
Li, J.,
Han, F.,
Liu, Q.H.,
Joint Inversion of Electromagnetic and Seismic Data Based on
Structural Constraints Using Variational Born Iteration Method,
GeoRS(56), No. 1, January 2018, pp. 436-445.
IEEE DOI
1801
Green's function methods, fast Fourier transforms,
finite difference methods, geophysical signal processing,
variational Born iteration method (VBIM)
BibRef
Guo, Q.,
Zhang, H.,
Han, F.,
Shang, Z.,
Prestack Seismic Inversion Based on Anisotropic Markov Random Field,
GeoRS(56), No. 2, February 2018, pp. 1069-1079.
IEEE DOI
1802
Anisotropic magnetoresistance, Bayes methods, Data models, Geology,
Linear programming, Markov processes, Standards, Anisotropic,
seismic inverse problems
BibRef
Guo, Q.,
Zhang, H.,
Cao, H.,
Xiao, W.,
Han, F.,
Hybrid Seismic Inversion Based on Multi-Order Anisotropic Markov
Random Field,
GeoRS(58), No. 1, January 2020, pp. 407-420.
IEEE DOI
2001
Geology, Data models, Impedance, Reliability, Mathematical model,
Acoustics, Markov processes,
multi-order neighborhoods
BibRef
Dagnino, D.[Daniel],
Sallarès, V.[Valentí],
Ranero, C.R.[César R.],
Waveform-Preserving Processing Flow of Multichannel Seismic
Reflection Data for Adjoint-State Full-Waveform Inversion of Ocean
Thermohaline Structure,
GeoRS(56), No. 3, March 2018, pp. 1615-1625.
IEEE DOI
1804
Butterworth filters, geophysical signal processing, oceanography,
seafloor phenomena, seismic waves, seismology, BF processing,
underwater acoustic propagation
BibRef
Zong, Z.,
Wang, Y.,
Li, K.,
Yin, X.,
Broadband Seismic Inversion for Low-Frequency Component of the Model
Parameter,
GeoRS(56), No. 9, September 2018, pp. 5177-5184.
IEEE DOI
1809
Frequency-domain analysis, Broadband communication, Data models,
Frequency estimation, Damping, Estimation, Bayes methods,
seismic inversion
BibRef
Li, H.,
Wang, L.,
Fast Modeling and Practical Inversion of Laterolog-Type Downhole
Resistivity Measurements,
GeoRS(57), No. 1, January 2019, pp. 120-127.
IEEE DOI
1901
Electrodes, Conductivity, Focusing, Tools, Velocity measurement,
Current measurement, Electric potential,
levenberg-marquardt (LM) method
BibRef
Lan, T.,
Liu, N.,
Han, F.,
Liu, Q.H.,
Joint Petrophysical and Structural Inversion of Electromagnetic and
Seismic Data Based on Volume Integral Equation Method,
GeoRS(57), No. 4, April 2019, pp. 2075-2086.
IEEE DOI
1904
electric field integral equations,
electromagnetic wave scattering, fast Fourier transforms,
variational Born iteration method (VBIM)
BibRef
Rodriguez, I.A.V.[I. A. Vera],
A Heuristic-Learning Optimizer for Elastodynamic Waveform Inversion
in Passive Seismics,
GeoRS(57), No. 4, April 2019, pp. 2234-2248.
IEEE DOI
1904
geophysical signal processing, geophysical techniques,
inverse problems, iterative methods, particle swarm optimisation,
waveform inversion
BibRef
Qiu, C.,
Liang, B.,
Han, F.,
Liu, H.,
Zhu, C.,
Liu, N.,
Liu, F.,
Fang, G.,
Liu, Q.H.,
Multifrequency 3-D Inversion of GREATEM Data by BCGS-FFT-BIM,
GeoRS(57), No. 4, April 2019, pp. 2439-2448.
IEEE DOI
1904
conjugate gradient methods, fast Fourier transforms, geology,
geophysical techniques, integral equations, inverse problems,
volume integral equation (VIE)
BibRef
Gao, Z.,
Pan, Z.,
Zuo, C.,
Gao, J.,
Xu, Z.,
An Optimized Deep Network Representation of Multimutation
Differential Evolution and its Application in Seismic Inversion,
GeoRS(57), No. 7, July 2019, pp. 4720-4734.
IEEE DOI
1907
Optimization methods, Data models, Mathematical model, Training,
Convergence, Deep learning, Deep learning,
seismic inversion
BibRef
Hu, Y.[Yong],
Wu, R.S.[Ru-Shan],
Han, L.G.[Li-Guo],
Zhang, P.[Pan],
Joint Multiscale Direct Envelope Inversion of Phase and Amplitude in
the Time-Frequency Domain,
GeoRS(57), No. 7, July 2019, pp. 5108-5120.
IEEE DOI
1907
Separate hase and amplitude.
Data models, Scattering, Imaging, Frequency-domain analysis,
Transforms, Optimization, Numerical models,
waveform-phase
BibRef
Li, G.,
Cai, H.,
Li, C.,
Alternating Joint Inversion of Controlled-Source Electromagnetic and
Seismic Data Using the Joint Total Variation Constraint,
GeoRS(57), No. 8, August 2019, pp. 5914-5922.
IEEE DOI
1908
geophysical prospecting, geophysical techniques,
hydrocarbon reservoirs, seismic waves, seismology,
structural constraint
BibRef
Huang, G.T.[Guang-Tan],
Chen, X.H.[Xiao-Hong],
Luo, C.[Cong],
Li, X.,
Prestack Waveform Inversion by Using an Optimized Linear Inversion
Scheme,
GeoRS(57), No. 8, August 2019, pp. 5716-5728.
IEEE DOI
1908
geophysical techniques, seismic waves, seismology,
adaptively determined regularization weight,
prestack waveform inversion (PWI)
BibRef
Huang, G.T.[Guang-Tan],
Chen, X.H.[Xiao-Hong],
Luo, C.[Cong],
Chen, Y.K.[Yang-Kang],
Mesoscopic Wave-Induced Fluid Flow Effect Extraction by Using
Frequency-Dependent Prestack Waveform Inversion,
GeoRS(59), No. 8, August 2021, pp. 6510-6524.
IEEE DOI
2108
Dispersion, Rocks, Time-frequency analysis, Attenuation, Reservoirs,
Oils, Inversion spectral decomposition,
white model
BibRef
Wang, L.,
Li, H.,
Fan, Y.,
Bayesian Inversion of Logging-While-Drilling Extra-Deep Directional
Resistivity Measurements Using Parallel Tempering Markov Chain Monte
Carlo Sampling,
GeoRS(57), No. 10, October 2019, pp. 8026-8036.
IEEE DOI
1910
approximation theory, Bayes methods, drilling (geotechnical),
inverse problems, Markov processes, Monte Carlo methods,
parallel tempering (PT)
BibRef
Huang, W.,
Liu, J.,
Robust Seismic Image Interpolation With Mathematical Morphological
Constraint,
IP(29), No. 1, 2020, pp. 819-829.
IEEE DOI
1910
Interpolation, Mathematical model, Transforms,
Morphological operations, Morphology, Spatial databases, Shape,
inversion problems
BibRef
Li, S.,
Liu, B.,
Ren, Y.,
Chen, Y.,
Yang, S.,
Wang, Y.,
Jiang, P.,
Deep-Learning Inversion of Seismic Data,
GeoRS(58), No. 3, March 2020, pp. 2135-2149.
IEEE DOI
2003
Deep neural networks (DNNs), seismic inversion
BibRef
Liu, Q.C.[Qian-Cheng],
Lu, Y.M.[Yong-Ming],
Zhang, H.[Hao],
Fast Single-Step Least-Squares Reverse-Time Imaging via Adaptive
Matching Filters in Beams,
GeoRS(58), No. 3, March 2020, pp. 1913-1919.
IEEE DOI
2003
LSRTM.
Adaptive matching filter, fast inversion
BibRef
Zhang, Q.C.[Qing-Chen],
Mao, W.J.[Wei-Jian],
Fang, J.W.[Jin-Wei],
Elastic Full Waveform Inversion With Source-Independent
Crosstalk-Free Source-Encoding Algorithm,
GeoRS(58), No. 4, April 2020, pp. 2915-2927.
IEEE DOI
2004
Crosstalk, elastic full waveform inversion (FWI),
source-encoding, source-independent
BibRef
Valerio, E.[Emanuela],
Manzo, M.[Mariarosaria],
Casu, F.[Francesco],
Convertito, V.[Vincenzo],
de Luca, C.[Claudio],
Manunta, M.[Michele],
Monterroso, F.[Fernando],
Lanari, R.[Riccardo],
de Novellis, V.[Vincenzo],
Seismogenic Source Model of the 2019, Mw 5.9, East-Azerbaijan
Earthquake (NW Iran) through the Inversion of Sentinel-1 DInSAR
Measurements,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Sun, B.,
Alkhalifah, T.A.,
Joint Minimization of the Mean and Information Entropy of the
Matching Filter Distribution for a Robust Misfit Function in
Full-Waveform Inversion,
GeoRS(58), No. 7, July 2020, pp. 4704-4720.
IEEE DOI
2006
Computational modeling, Focusing, Data models, Mathematical model,
Optimization, Predictive models, Current measurement,
nonlinear inversion
BibRef
Fediuk, A.[Annika],
Wilken, D.[Dennis],
Thorwart, M.[Martin],
Wunderlich, T.[Tina],
Erkul, E.[Ercan],
Rabbel, W.[Wolfgang],
The Applicability of an Inverse Schlumberger Array for Near-Surface
Targets in Shallow Water Environments,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Wang, Y.,
Ge, Q.,
Lu, W.,
Yan, X.,
Well-Logging Constrained Seismic Inversion Based on Closed-Loop
Convolutional Neural Network,
GeoRS(58), No. 8, August 2020, pp. 5564-5574.
IEEE DOI
2007
Impedance, Convolution, Data models, Encoding, Kernel,
Convolutional neural networks, Deep learning,
seismic inversion
BibRef
Song, C.[Chao],
Alkhalifah, T.A.[Tariq A.],
Efficient Wavefield Inversion With Outer Iterations and Total
Variation Constraint,
GeoRS(58), No. 8, August 2020, pp. 5836-5846.
IEEE DOI
2007
Perturbation methods, Mathematical model, TV, Linear programming,
Computational modeling, Propagation, Data models, Cycle skipping,
wavefield reconstruction
BibRef
Zong, J.,
Wo, Y.,
Zhou, H.,
Dyaur, N.,
Inversion for Salt Flank Geometry Using Transmitted P- and S-Wave
Travel Times,
GeoRS(58), No. 9, September 2020, pp. 6504-6511.
IEEE DOI
2008
Geometry, Tomography, Data models, Mathematical model, Receivers,
Numerical models, Geology, Joint inversion, seismic tomography, vertical seismic profiling (VSP)
BibRef
Chen, G.,
Yang, W.,
Chen, S.,
Liu, Y.,
Gu, Z.,
Application of Envelope in Salt Structure Velocity Building:
From Objective Function Construction to the Full-Band Seismic Data
Reconstruction,
GeoRS(58), No. 9, September 2020, pp. 6594-6608.
IEEE DOI
2008
Linear programming, Data models, Image reconstruction, Buildings,
Reconstruction algorithms, Inverse problems, Scattering,
velocity building
BibRef
Sun, M.[Minao],
Jin, S.G.[Shuang-Gen],
Multiparameter Elastic Full Waveform Inversion of Ocean Bottom
Seismic Four-Component Data Based on A Modified Acoustic-Elastic
Coupled Equation,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Sun, M.[Minao],
Jin, S.G.[Shuang-Gen],
Yu, P.F.[Peng-Fei],
Elastic Least-Squares Reverse-Time Migration Based on a Modified
Acoustic-Elastic Coupled Equation for OBS Four-Component Data,
GeoRS(59), No. 11, November 2021, pp. 9772-9782.
IEEE DOI
2111
Mathematical model, Perturbation methods, Imaging, Propagation,
Impedance, Data models, Sun, Least-squares migration (LSM),
reverse-time migration
BibRef
Wu, G.L.[Guo-Li],
Dong, H.F.[He-Feng],
Ke, G.P.[Gan-Pan],
Song, J.Q.A.[Jun-Qi-Ang],
Shear-Wave Tomography Using Ocean Ambient Noise with Interference,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Zhang, Z.,
Lin, Y.,
Data-Driven Seismic Waveform Inversion:
A Study on the Robustness and Generalization,
GeoRS(58), No. 10, October 2020, pp. 6900-6913.
IEEE DOI
2009
Inverse problems, Computational modeling, Mathematical model,
Generative adversarial networks, Neural networks,
transfer learning
BibRef
He, B.,
Liu, Y.,
Lu, H.,
Zhang, Z.,
Correlative Full-Intensity Waveform Inversion,
GeoRS(58), No. 10, October 2020, pp. 6983-6994.
IEEE DOI
2009
Data models, Linear programming, Frequency-domain analysis,
Bandwidth, Scattering, Geology, Geophysics, Cycle-skipping,
source-independent
BibRef
Long, Z.,
Cai, H.,
Hu, X.,
Li, G.,
Shao, O.,
Parallelized 3-D CSEM Inversion With Secondary Field Formulation and
Hexahedral Mesh,
GeoRS(58), No. 10, October 2020, pp. 6812-6822.
IEEE DOI
2009
Computational modeling, Finite element analysis,
Mathematical model, Numerical models, Solid modeling, Data models,
secondary field formulation
BibRef
Jia, Z.A.[Zhu-Ang],
Lu, W.K.[Wen-Kai],
Blind Separation of Ground-Roll Using Interband Morphological
Similarity and Pattern Coding,
GeoRS(58), No. 10, October 2020, pp. 7166-7177.
IEEE DOI
2009
Task analysis, Frequency-domain analysis, Encoding,
Wavelet transforms, Dictionaries, Signal to noise ratio,
self-similarity
BibRef
Roger, M.[Marine],
Li, Z.H.[Zhen-Hong],
Clarke, P.[Peter],
Song, C.[Chuang],
Hu, J.C.[Jyr-Ching],
Feng, W.P.[Wan-Peng],
Yi, L.[Lei],
Joint Inversion of Geodetic Observations and Relative Weighting: The
1999 Mw 7.6 Chi-Chi Earthquake Revisited,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Feng, D.,
Wang, X.,
Wang, X.,
New Dynamic Stochastic Source Encoding Combined With a Minmax-Concave
Total Variation Regularization Strategy for Full Waveform Inversion,
GeoRS(58), No. 11, November 2020, pp. 7753-7771.
IEEE DOI
2011
Encoding, Mathematical model, TV, Stochastic processes, Data models,
Linear programming, Crosstalk,
variable-density acoustic equation
BibRef
Zhang, Y.,
Zhao, Z.,
Nie, Z.,
Liu, Q.H.,
Approach on Joint Inversion of Electromagnetic and Acoustic Data
Based on Structural Constraints,
GeoRS(58), No. 11, November 2020, pp. 7672-7681.
IEEE DOI
2011
Acoustics, Scattering, Mathematical model, Image reconstruction,
Inverse problems, Electromagnetics, Permittivity, Joint inversion,
subspace-based optimization method (SOM)
BibRef
Liu, B.,
Li, H.,
Mohandes, M.,
Al-Shaikhi, A.,
Zhao, L.,
A Robust Scheme for Sparse Reflectivity Recovering From Uniformly
Quantized Seismic Data,
GeoRS(58), No. 12, December 2020, pp. 8665-8673.
IEEE DOI
2012
Quantization (signal), Matching pursuit algorithms, Uncertainty,
Estimation, Deconvolution, Robustness, Petroleum,
seismic data quantization
BibRef
Zhang, X.T.[Xiao-Tian],
Jia, Z.[Zhe],
Ross, Z.E.[Zachary E.],
Clayton, R.W.[Robert W.],
Extracting Dispersion Curves From Ambient Noise Correlations Using
Deep Learning,
GeoRS(58), No. 12, December 2020, pp. 8932-8939.
IEEE DOI
2012
Dispersion, Correlation, Training, Surface waves, Machine learning,
Data models, Surface treatment, Convolutional networks,
surface waves
BibRef
Jiang, B.,
Lu, W.,
Adaptive Multiple Subtraction Based on an Accelerating Iterative
Curvelet Thresholding Method,
IP(30), 2021, pp. 806-821.
IEEE DOI
2012
Curvelet transform, geophysical signal processing, sparsity,
iterative thresholding, signal separation
BibRef
Luo, J.,
Wang, B.,
Wu, R.S.,
Gao, J.,
Elastic Full Waveform Inversion With Angle Decomposition and
Wavefield Decoupling,
GeoRS(59), No. 1, January 2021, pp. 871-883.
IEEE DOI
2012
Scattering, Frequency-domain analysis, Perturbation methods,
Acoustics, Time-domain analysis, Analytical models,
wave mode decoupling
BibRef
Jiang, B.,
Lu, W.,
Primal-Dual Optimization Strategy With Total Variation Regularization
for Prestack Seismic Image Deblurring,
GeoRS(59), No. 1, January 2021, pp. 884-893.
IEEE DOI
2012
TV, Mathematical model, Imaging, Convolution, Lighting, Deconvolution,
Data models, Deconvolution, nonstationary,
total variation (TV)
BibRef
Qian, F.,
Zhang, C.,
Feng, L.,
Lu, C.,
Zhang, G.,
Hu, G.,
Tubal-Sampling: Bridging Tensor and Matrix Completion in 3-D Seismic
Data Reconstruction,
GeoRS(59), No. 1, January 2021, pp. 854-870.
IEEE DOI
2012
Tensors, Matrix decomposition, Periodic structures,
Mathematical model, Bridges, Signal to noise ratio, Convolution,
tubal sampling
BibRef
Grathwohl, C.[Christine],
Kunstmann, P.C.[Peer Christian],
Quinto, E.T.[Eric Todd],
Rieder, A.[Andreas],
Imaging with the Elliptic Radon Transform in Three Dimensions from an
Analytical and Numerical Perspective,
SIIMS(13), No. 4, 2020, pp. 2250-2280.
DOI Link
2012
A linear model in seismic imaging.
BibRef
Wang, D.,
Gao, J.,
Liu, N.,
Jiang, X.,
Structure-Oriented DTGV Regularization for Random Noise Attenuation
in Seismic Data,
GeoRS(59), No. 2, February 2021, pp. 1757-1771.
IEEE DOI
2101
TV, Attenuation, Transforms, Oils, Geology, Data models,
Signal to noise ratio, Gradient structure tensor (GST),
variational regularization
BibRef
Yuan, Y.,
Li, Y.,
Zhou, S.,
Multichannel Statistical Broadband Wavelet Deconvolution for
Improving Resolution of Seismic Signals,
GeoRS(59), No. 2, February 2021, pp. 1772-1783.
IEEE DOI
2101
Deconvolution, Correlation, Receivers, Surface treatment,
Signal resolution, Convolution, Surface waves, Broadband wavelet,
resolution
BibRef
Liu, X.,
Chen, X.,
Li, J.,
Chen, Y.,
Nonlocal Weighted Robust Principal Component Analysis for Seismic
Noise Attenuation,
GeoRS(59), No. 2, February 2021, pp. 1745-1756.
IEEE DOI
2101
Noise reduction, Principal component analysis, Attenuation,
Image reconstruction, Matrix decomposition, Linear programming,
seismic data
BibRef
Gao, Z.,
Li, C.,
Liu, N.,
Pan, Z.,
Gao, J.,
Xu, Z.,
Large-Dimensional Seismic Inversion Using Global Optimization With
Autoencoder-Based Model Dimensionality Reduction,
GeoRS(59), No. 2, February 2021, pp. 1718-1732.
IEEE DOI
2101
Optimization methods, Dimensionality reduction, Decoding,
Data models, Impedance, Numerical models, Autoencoder, seismic inversion
BibRef
Xu, S.,
Su, W.,
Yang, D.,
Li, Z.,
A Application of adaptive generalized S transform in formation Q
value extraction,
CVIDL20(688-692)
IEEE DOI
2102
geophysical signal processing, geophysical techniques,
optimisation, seismic waves, time-frequency analysis,
Teager-Kaiser energy
BibRef
Adler, A.,
Araya-Polo, M.,
Poggio, T.,
Deep Learning for Seismic Inverse Problems: Toward the Acceleration
of Geophysical Analysis Workflows,
SPMag(38), No. 2, March 2021, pp. 89-119.
IEEE DOI
2103
Seismic measurements, Inverse problems, Earthquakes, Deep learning,
Hydrocarbons, Hazards, Earth, Analytical models, Geophysical measurements
BibRef
Yang, C.S.[Cheng-Sheng],
Wang, T.[Ting],
Zhu, S.[Sainan],
Han, B.Q.[Bing-Quan],
Dong, J.H.[Ji-Hong],
Zhao, C.Y.[Chao-Ying],
Co-Seismic Inversion and Post-Seismic Deformation Mechanism Analysis
of 2019 California Earthquake,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Wu, B.[Bangyu],
Meng, D.[Delin],
Zhao, H.X.[Hai-Xia],
Semi-Supervised Learning for Seismic Impedance Inversion Using
Generative Adversarial Networks,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Zhong, T.,
Cheng, M.,
Dong, X.,
Li, Y.,
Seismic Random Noise Suppression by Using Adaptive Fractal
Conservation Law Method Based on Stationarity Testing,
GeoRS(59), No. 4, April 2021, pp. 3588-3600.
IEEE DOI
2104
Noise reduction, Attenuation, Signal processing algorithms,
Testing, Transforms, Signal to noise ratio, Data processing,
stationarity testing
BibRef
Wang, H.,
Huang, G.,
Chen, W.,
Chen, Y.,
Q-Compensated Denoising of Seismic Data,
GeoRS(59), No. 4, April 2021, pp. 3580-3587.
IEEE DOI
2104
Noise reduction, Attenuation, Convolution, Data models,
Mathematical model, Noise measurement, Estimation, Denoising,
Q-compensation
BibRef
Liu, Y.T.[Yang-Ting],
Zhong, Y.[Yu],
Machine Learning-Based Seafloor Seismic Prestack Inversion,
GeoRS(59), No. 5, May 2021, pp. 4471-4480.
IEEE DOI
2104
Training, Data models, Neurons, Mathematical model,
Computational modeling, Biological neural networks,
seafloor properties
BibRef
Ferreira, R.S.[Rodrigo S.],
Oliveira, D.A.B.[Dário A. B.],
Semin, D.G.[Daniil G.],
Zaytsev, S.[Semen],
Automatic Velocity Analysis Using a Hybrid Regression Approach With
Convolutional Neural Networks,
GeoRS(59), No. 5, May 2021, pp. 4464-4470.
IEEE DOI
2104
Training, MOS devices, Convolution,
Splines (mathematics), Stacking, Geophysics,
regression analysis
BibRef
Wang, S.N.[Sheng-Nan],
Li, Y.[Yue],
Wu, N.[Ning],
Zhao, Y.X.[Yu-Xing],
Yao, H.Y.[Hai-Yang],
Attribute-Based Double Constraint Denoising Network for Seismic Data,
GeoRS(59), No. 6, June 2021, pp. 5304-5316.
IEEE DOI
2106
Noise reduction, Training, Noise measurement, Task analysis,
Data mining, Generative adversarial networks,
seismic data
BibRef
Cyz, M.[Marta],
Azevedo, L.[Leonardo],
Direct Geostatistical Seismic Amplitude Versus Angle Inversion for
Shale Rock Properties,
GeoRS(59), No. 6, June 2021, pp. 5335-5344.
IEEE DOI
2106
Rocks, Data models, Computational modeling, Physics,
Predictive models, Stochastic processes, Reservoirs, Geostatistics,
stochastic inversion
BibRef
Huang, G.T.[Guang-Tan],
Chen, X.H.[Xiao-Hong],
Chen, Y.K.[Yang-Kang],
P-P and Dynamic Time Warped P-SV Wave AVA Joint-Inversion With l1-2
Regularization,
GeoRS(59), No. 7, July 2021, pp. 5535-5548.
IEEE DOI
2106
Reservoirs, Heuristic algorithms, Correlation, Reliability,
Data mining, Data models, Rocks, l1-2-norm penalty,
prestack joint inversion
BibRef
Liu, C.Y.[Chun-Yy],
Yang, H.F.[Hong-Feng],
Wang, B.S.[Bao-Shan],
Yang, J.[Jun],
Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal
Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Cheng, J.W.[Jing-Wang],
Chen, W.[Wei],
Zhou, L.[Li],
Yang, L.Q.[Liu-Qing],
Liu, Q.M.[Qi-Min],
Zhang, X.[Xiang],
Deblending of Simultaneous-Source Seismic Data Using Bregman
Iterative Shaping,
GeoRS(59), No. 7, July 2021, pp. 6208-6217.
IEEE DOI
2106
Transforms, Crosstalk, Iterative algorithms, Imaging,
Mathematical model, Data models, Bregman iterative shaping (BIS),
simultaneous-source
BibRef
Ha, W.[Wansoo],
Shin, C.S.[Chang-Soo],
Handling Negative Values for the Logarithmic Objective Function in
Acoustic Laplace-Domain Full-Waveform Inversion Using Real Variables,
GeoRS(59), No. 7, July 2021, pp. 6218-6224.
IEEE DOI
2106
Linear programming, Damping, Data models, Numerical models,
Laplace equations, Optimization methods,
logarithmic objective function
BibRef
Liu, H.[Hong],
Yang, K.[Kunde],
Yang, Q.L.[Qiu-Long],
Sequential Parameter Estimation of Modal Dispersion Curves with an
Adaptive Particle Filter in Shallow Water: Experimental Results,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
Geoacoustic analysis in shallow water.
BibRef
Shi, H.Y.[Hui-Yan],
Li, T.L.[Tong-Lin],
Sun, R.[Rui],
Zhang, G.B.[Gong-Bo],
Zhang, R.Z.[Rong-Zhe],
Kang, X.Z.[Xin-Ze],
Insights from the P Wave Travel Time Tomography in the Upper Mantle
Beneath the Central Philippines,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Fokker, E.[Eldert],
Ruigrok, E.[Elmer],
Hawkins, R.[Rhys],
Trampert, J.[Jeannot],
Physics-Based Relationship for Pore Pressure and Vertical Stress
Monitoring Using Seismic Velocity Variations,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Ayala-Garcia, D.[Daniella],
Curtis, A.[Andrew],
Branicki, M.[Michal],
Seismic Interferometry from Correlated Noise Sources,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Wang, H.Z.[Hong-Zhou],
Li, Y.[Yue],
Dong, X.T.[Xin-Tong],
Generative Adversarial Network for Desert Seismic Data Denoising,
GeoRS(59), No. 8, August 2021, pp. 7062-7075.
IEEE DOI
2108
Noise reduction, Generators, Generative adversarial networks,
Convolution, Signal to noise ratio, Training,
low signal-to-noise ratios (SNRs)
BibRef
Dong, X.T.[Xin-Tong],
Li, Y.[Yue],
Denoising the Optical Fiber Seismic Data by Using Convolutional
Adversarial Network Based on Loss Balance,
GeoRS(59), No. 12, December 2021, pp. 10544-10554.
IEEE DOI
2112
Noise reduction, Signal to noise ratio, Noise measurement,
Generative adversarial networks, Optical scattering,
low signal-to-noise ratio (SNR)
BibRef
Zhu, H.Y.[Hui-Yu],
Sun, M.Y.[Meng-Yao],
Fu, H.H.[Hao-Huan],
Du, N.[Nianmao],
Zhang, J.[Jie],
Training a Seismogram Discriminator Based on ResNet,
GeoRS(59), No. 8, August 2021, pp. 7076-7085.
IEEE DOI
2108
Earthquakes, Task analysis, Neural networks,
Geophysics, Training, Image recognition, Machine learning,
seismological observations
BibRef
Wang, H.[Hang],
Chen, W.[Wei],
Zhang, Q.[Quan],
Liu, X.Y.[Xing-Ye],
Zu, S.[Shaohuan],
Chen, Y.K.[Yang-Kang],
Fast Dictionary Learning for High-Dimensional Seismic Reconstruction,
GeoRS(59), No. 8, August 2021, pp. 7098-7108.
IEEE DOI
2108
Dictionaries, Sparse matrices, Encoding, Mathematical model,
Transforms, Singular value decomposition, Image reconstruction,
signal processing
BibRef
Qu, Y.M.[Ying-Ming],
Huang, C.P.[Chong-Peng],
Liu, C.[Chang],
Li, Z.C.[Zhen-Chun],
Full-Path Compensated Least-Squares Reverse Time Migration of Joint
Primaries and Different-Order Multiples for Deep-Marine Environment,
GeoRS(59), No. 8, August 2021, pp. 7109-7121.
IEEE DOI
2108
Attenuation, Imaging, Mathematical model, Linear programming,
Seismic waves, Media, Acoustics, Deep-marine environment,
viscoacoustic
BibRef
Guo, Q.[Qiang],
Ba, J.[Jing],
Luo, C.[Cong],
Prestack Seismic Inversion With Data-Driven MRF-Based Regularization,
GeoRS(59), No. 8, August 2021, pp. 7122-7136.
IEEE DOI
2108
Maximum likelihood estimation, Uncertainty, Inverse problems,
Geology, Simulated annealing, Linear programming,
prestack seismic inversion
BibRef
Chen, H.M.[Han-Ming],
Zhou, H.[Hui],
Rao, Y.[Ying],
Source Wavefield Reconstruction in Fractional Laplacian Viscoacoustic
Wave Equation-Based Full Waveform Inversion,
GeoRS(59), No. 8, August 2021, pp. 6496-6509.
IEEE DOI
2108
Propagation, Laplace equations, Time-domain analysis, Receivers,
Mathematical model, Correlation, Graphics processing units,
wavefield reconstruction
BibRef
Oliveira, D.A.B.[Dário A. B.],
Semin, D.G.[Daniil G.],
Zaytsev, S.[Semen],
Self-Supervised Ground-Roll Noise Attenuation Using Self-Labeling and
Paired Data Synthesis,
GeoRS(59), No. 8, August 2021, pp. 7147-7159.
IEEE DOI
2108
Training, Attenuation, Noise reduction, Pipelines, Noise measurement,
Data models, Geology, Deep learning, geophysical image processing,
self-supervised learning
BibRef
Ao, Y.[Yile],
Lu, W.K.[Wen-Kai],
Jiang, B.[Bowu],
Monkam, P.[Patrice],
Seismic Structural Curvature Volume Extraction With Convolutional
Neural Networks,
GeoRS(59), No. 9, September 2021, pp. 7370-7384.
IEEE DOI
2109
Feature extraction, Estimation, Deformable models,
Surface topography, Surface impedance, Strain,
structural curvature
BibRef
Yang, L.Q.[Liu-Qing],
Chen, W.[Wei],
Wang, H.[Hang],
Chen, Y.K.[Yang-Kang],
Deep Learning Seismic Random Noise Attenuation via Improved Residual
Convolutional Neural Network,
GeoRS(59), No. 9, September 2021, pp. 7968-7981.
IEEE DOI
2109
Attenuation, Transforms, Training, Task analysis, Noise reduction,
Signal to noise ratio, Convolution, transfer learning
BibRef
Guo, R.[Rui],
Yao, H.M.[He Ming],
Li, M.[Maokun],
Ng, M.K.P.[Michael Kwok Po],
Jiang, L.J.[Li-Jun],
Abubakar, A.[Aria],
Joint Inversion of Audio-Magnetotelluric and Seismic Travel Time Data
With Deep Learning Constraint,
GeoRS(59), No. 9, September 2021, pp. 7982-7995.
IEEE DOI
2109
Training, Deep learning, Knowledge engineering, Conductivity,
Data models, Numerical models, Space exploration, velocity
BibRef
Zhou, Y.X.[Yan-Xin],
Wang, R.[Runqiu],
Huang, W.[Weilin],
Surface Diffraction Noise Attenuation for Marine Seismic Data
Processing With Mathematical Morphological Filtering,
GeoRS(59), No. 9, September 2021, pp. 8007-8021.
IEEE DOI
2109
Surface morphology, Trajectory, Diffraction, Data processing,
Petroleum, Surface treatment, Attenuation,
surface diffraction noise (SDN)
BibRef
Li, Y.S.[Yin-Shuo],
Song, J.Y.[Jian-Yong],
Lu, W.K.[Wen-Kai],
Monkam, P.[Patrice],
Ao, Y.[Yile],
Multitask Learning for Super-Resolution of Seismic Velocity Model,
GeoRS(59), No. 9, September 2021, pp. 8022-8033.
IEEE DOI
2109
Task analysis, Image edge detection, Computational modeling,
Deep learning, Convolution, Correlation, Deep learning, edge image,
super-resolution (SR)
BibRef
Fang, Z.L.[Zhi-Long],
Demanet, L.[Laurent],
Lift and Relax for PDE-Constrained Inverse Problems in Seismic
Imaging,
GeoRS(59), No. 9, September 2021, pp. 8034-8039.
IEEE DOI
2109
Optimization, Linear programming, Mathematical model,
Numerical models, Data models, Atmospheric modeling, Receivers,
surface and subsurface properties
BibRef
Meyers, P.M.[Patrick M.],
Prestegard, T.[Tanner],
Mandic, V.[Vuk],
Tsai, V.C.[Victor C.],
Bowden, D.C.[Daniel C.],
Matas, A.[Andrew],
Pavlis, G.[Gary],
Caton, R.[Ross],
A Linear Inversion Approach to Measuring the Composition and
Directionality of the Seismic Noise Field,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Zhang, W.[Wei],
Gao, J.H.[Jing-Huai],
Gao, Z.Q.[Zhao-Qi],
Chen, H.L.[Hong-Ling],
Adjoint-Driven Deep-Learning Seismic Full-Waveform Inversion,
GeoRS(59), No. 10, October 2021, pp. 8913-8932.
IEEE DOI
2109
Inverse problems, Linear programming, Image reconstruction,
Data models, Mathematical model, Training, Reliability,
inverse problem
BibRef
Zhang, W.[Wei],
Gao, J.H.[Jing-Huai],
Deep-Learning Full-Waveform Inversion Using Seismic Migration Images,
GeoRS(60), 2022, pp. 1-18.
IEEE DOI
2112
Image reconstruction, Data models, Neural networks,
Iterative methods, Inverse problems, Tools, Electronics packaging,
reverse time migration
BibRef
Wang, B.F.[Ben-Feng],
Li, J.K.[Jia-Kuo],
Luo, J.R.[Jing-Rui],
Wang, Y.Y.[Ying-Ying],
Geng, J.H.[Jian-Hua],
Intelligent Deblending of Seismic Data Based on U-Net and Transfer
Learning,
GeoRS(59), No. 10, October 2021, pp. 8885-8894.
IEEE DOI
2109
Feature extraction, Transforms, Training data, Training, Data mining,
Deep learning, Volume measurement, Deblending, deep learning,
U-net
BibRef
Li, Q.[Qin],
Wang, W.[Wei],
AVO Inversion in Orthotropic Media Based on SA-PSO,
GeoRS(59), No. 10, October 2021, pp. 8903-8912.
IEEE DOI
2109
Seismic inversion.
amplitude variation with offset.
Media, Optimization, Reservoirs, Prediction algorithms,
Temperature distribution, Rocks, Particle swarm optimization,
orthotropic medium
BibRef
Feng, J.[Jie],
Zhao, J.H.[Jian-Hu],
Zheng, G.[Gen],
Li, S.B.[Shao-Bo],
Horizon Picking from SBP Images Using Physicals-Combined Deep
Learning,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
Seismic related, marine bottom layers.
BibRef
Vargas, D.[David],
Vasconcelos, I.[Ivan],
Ravasi, M.[Matteo],
Luiken, N.[Nick],
Time-Domain Multidimensional Deconvolution:
A Physically Reliable and Stable Preconditioned Implementation,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Li, Z.X.[Zhong-Xiao],
Sun, N.[Ningna],
Gao, H.T.[Hao-Tian],
Qin, N.[Ning],
Li, Z.C.[Zhen-Chun],
Adaptive Subtraction Based on U-Net for Removing Seismic Multiples,
GeoRS(59), No. 11, November 2021, pp. 9796-9812.
IEEE DOI
2111
Adaptation models, Data models, Training, Mathematical model, Kernel,
Computational modeling, Minimization, Adaptive subtraction, U-net
BibRef
Yu, H.[Han],
Chen, Y.Q.[Yu-Qing],
Hanafy, S.M.[Sherif M.],
Schuster, G.T.[Gerard T.],
Skeletonized Wave-Equation Refraction Inversion With Autoencoded
Waveforms,
GeoRS(59), No. 10, October 2021, pp. 8210-8227.
IEEE DOI
2109
Training, Neural networks, Feature extraction, Decoding, Data models,
Telecommunications, Tools, Autoencoder, refractions, skeletonization,
waveform inversion
BibRef
Chen, G.X.[Guo-Xin],
Yang, W.[Wencai],
Liu, Y.[Yanan],
Luo, J.R.[Jing-Rui],
Jing, H.[Hao],
Envelope-Based Sparse-Constrained Deconvolution for Velocity Model
Building,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Deconvolution, Data models, Buildings, Seismic waves, Optimization,
Numerical models, Linear programming, Envelope,
velocity model building
BibRef
Ao, Y.[Yile],
Lu, W.K.[Wen-Kai],
Xu, P.C.[Peng-Cheng],
Jiang, B.[Bowu],
Seismic Dip Estimation With a Domain Knowledge Constrained Transfer
Learning Approach,
GeoRS(60), 2022, pp. 1-16.
IEEE DOI
2112
Estimation, Transfer learning, Task analysis, Robustness,
Deep learning, Azimuth, Tensors, Convolutional neural network,
transfer learning
BibRef
Zhang, C.[Chao],
van der Baan, M.[Mirko],
Seismic Signal Matching and Complex Noise Suppression by Zernike
Moments and Trilateral Weighted Sparse Coding,
GeoRS(60), 2022, pp. 1-10.
IEEE DOI
2112
Noise reduction, Encoding, Sparse matrices, Euclidean distance,
Signal to noise ratio, Correlation, Noise measurement,
Zernike moments
BibRef
Zhao, Y.X.[Yu-Xing],
Li, Y.[Yue],
Wu, N.[Ning],
Distributed Acoustic Sensing Vertical Seismic Profile Data Denoiser
Based on Convolutional Neural Network,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI
2112
Noise reduction, Training, Optical noise, Convolution, Interference,
Optical coupling, Fading channels, Borehole seismic survey,
vertical seismic profile (VSP)
BibRef
Tian, X.Y.[Xing-Yu],
Lu, W.K.[Wen-Kai],
Li, Y.[Yanda],
Improved Anomalous Amplitude Attenuation Method Based on Deep Neural
Networks,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI
2112
Deep learning, Convolutional neural networks, Task analysis,
Noise reduction, Noise measurement, Attenuation,
seismic denoising
BibRef
Othman, A.[Abdullah],
Iqbal, N.[Naveed],
Hanafy, S.M.[Sherif M.],
Waheed, U.B.[Umair Bin],
Automated Event Detection and Denoising Method for Passive Seismic
Data Using Residual Deep Convolutional Neural Networks,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI
2112
Noise reduction, Neural networks, Noise measurement,
Feature extraction, Event detection, Data mining,
machine learning
BibRef
Ma, H.T.[Hai-Tao],
Wang, Y.Z.[Yu-Zhuo],
Li, Y.[Yue],
Zhao, Y.X.[Yu-Xing],
Desert Seismic Low-Frequency Noise Attenuation Using Low-Rank
Decomposition-Based Denoising Convolutional Neural Network,
GeoRS(60), 2022, pp. 1-9.
IEEE DOI
2112
Convolution, Attenuation, Neural networks, Training,
Signal to noise ratio, Noise reduction, Noise measurement,
low-rank decomposition
BibRef
Lin, Y.[Yi],
Zhang, J.H.[Jin-Hai],
A Multispectral Denoising Framework for Seismic Random Noise
Attenuation,
GeoRS(60), 2022, pp. 1-17.
IEEE DOI
2112
Tensors, Noise measurement, Noise reduction, Transforms, Attenuation,
Time-frequency analysis, Matrix decomposition, 3-D tensor,
seismic data processing
BibRef
Li, J.T.[Jin-Tao],
Wu, X.M.[Xin-Ming],
Hu, Z.X.[Zhan-Xuan],
Deep Learning for Simultaneous Seismic Image Super-Resolution and
Denoising,
GeoRS(60), 2022, pp. 1-11.
IEEE DOI
2112
Image resolution, Superresolution, Training data, Training,
Noise reduction, Convolution, Computational modeling,
super-resolution
BibRef
Giannakis, I.[Iraklis],
Giannopoulos, A.[Antonios],
Warren, C.[Craig],
Sofroniou, A.[Anastasia],
Fractal-Constrained Crosshole/Borehole-to-Surface Full-Waveform
Inversion for Hydrogeological Applications Using Ground-Penetrating
Radar,
GeoRS(60), 2022, pp. 1-10.
IEEE DOI
2112
Permittivity, Soil, Fractals, Computational modeling, Transmitters,
Time-domain analysis, Finite difference methods,
principal component analysis (PCA)
BibRef
Liu, N.H.[Nai-Hao],
Li, F.Y.[Fang-Yu],
Wang, D.H.[De-Hua],
Gao, J.H.[Jing-Huai],
Xu, Z.B.[Zong-Ben],
Ground-Roll Separation and Attenuation Using Curvelet-Based
Multichannel Variational Mode Decomposition,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI
2112
Transforms, Attenuation, Signal resolution, Wavelet transforms,
Signal to noise ratio, Robustness, Optimization,
variational mode decomposition (VMD)
BibRef
Bai, Y.[Yang],
Tan, M.[Maojin],
Shi, Y.J.[Yu-Jiang],
Zhang, H.T.[Hai-Tao],
Li, G.[Gaoren],
Regression Committee Machine and Petrophysical Model Jointly Driven
Parameters Prediction From Wireline Logs in Tight Sandstone
Reservoirs,
GeoRS(60), 2022, pp. 1-9.
IEEE DOI
2112
Reservoirs, Training, Predictive models, Permeability,
Mathematical model, Data models, Acoustics, Petrophysical models,
wireline logs
BibRef
Zhou, Y.T.[Ya-Tong],
Yang, J.[Jian],
Wang, H.[Hang],
Huang, G.T.[Guang-Tan],
Chen, Y.K.[Yang-Kang],
Statistics-Guided Dictionary Learning for Automatic Coherent Noise
Suppression,
GeoRS(60), 2022, pp. 1-17.
IEEE DOI
2112
Dictionaries, Transforms, Noise reduction, Measurement,
Atomic measurements, Training, Signal processing algorithms,
statistics
BibRef
Huang, G.T.[Guang-Tan],
Zhang, D.[Dong],
Chen, W.[Wei],
Chen, Y.K.[Yang-Kang],
Accelerated Signal-and-Noise Orthogonalization,
GeoRS(60), 2022, pp. 1-9.
IEEE DOI
2112
Noise reduction, Acceleration, Imaging, Inverse problems,
Smoothing methods, Oils, Mathematical model, Denoising,
seismic data processing
BibRef
Yang, J.D.[Ji-Dong],
Huang, J.P.[Jian-Ping],
Li, Z.C.[Zhen-Chun],
Zhu, H.[Hejun],
McMechan, G.A.[George A.],
Luo, X.[Xin],
Approximating the Gauss-Newton Hessian Using a Space-Wavenumber
Filter and its Applications in Least-Squares Seismic Imaging,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Mathematical model, Imaging, Computational modeling, Receivers,
Data models, Media, Geometry, Gauss-Newton Hessian (GNH),
seismic imaging
BibRef
Luo, C.[Cong],
Huang, G.T.[Guang-Tan],
Chen, X.H.[Xiao-Hong],
Chen, Y.K.[Yang-Kang],
Registration-Free Multicomponent Joint AVA Inversion Using Optimal
Transport,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Earth, Mathematical model, Convex functions, Transforms,
Signal to noise ratio, Media, Linear approximation,
registration-free
BibRef
Liu, B.[Bo],
Mohandes, M.[Mohamed],
Nuha, H.[Hilal],
Deriche, M.[Mohamed],
Fekri, F.[Faramarz],
McClellan, J.H.[James H.],
A Multitone Model-Based Seismic Data Compression,
SMCS(52), No. 2, February 2022, pp. 1030-1040.
IEEE DOI
2201
Data models, Parameter estimation, Transforms, Encoding,
Analytical models, Redundancy, Optimization, Data compression,
sinusoidal waves
BibRef
Zhao, H.X.[Hai-Xia],
Bai, T.T.[Ting-Ting],
Wang, Z.Q.[Zhi-Qiang],
A Natural Images Pre-Trained Deep Learning Method for Seismic Random
Noise Attenuation,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Han, Z.[Zhi],
Yu, S.Q.[Si-Quan],
Lin, S.B.[Shao-Bo],
Zhou, D.X.[Ding-Xuan],
Depth Selection for Deep ReLU Nets in Feature Extraction and
Generalization,
PAMI(44), No. 4, April 2022, pp. 1853-1868.
IEEE DOI
2203
Applied to earthquake seismic intensity prediction.
Feature extraction, Data mining, Deep learning, Task analysis,
Optimization, Machine learning algorithms, Deep nets, learning theory
BibRef
Fang, P.[Peng],
Zhang, J.H.[Jin-Hai],
Recursive Enhancement of Weak Subsurface Boundaries and Its
Application to SHARAD Data,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Han, J.G.[Jian-Guang],
Gu, B.L.[Bing-Luo],
Zhu, G.H.[Guang-Hui],
Liu, Z.W.[Zhi-Wei],
High-Precision Depth Domain Migration Method in Imaging of 3D Seismic
Data in Coalfield,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Zhang, X.[Xin],
Qian, Y.[Yinping],
Shen, X.[Xuzhang],
Huang, H.[He],
Chai, H.B.[Hai-Bin],
Shallow Crustal Structure of S-Wave Velocities in the Coastal Area of
South China Constrained by Receiver Function Amplitudes,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Li, F.D.[Fang-Da],
Guo, Z.W.[Zhen-Wei],
Pan, X.P.[Xin-Peng],
Liu, J.X.[Jian-Xin],
Wang, Y.Y.[Yan-Yi],
Gao, D.W.[Da-Wei],
Deep Learning with Adaptive Attention for Seismic Velocity Inversion,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Wang, N.[Ning],
Shi, Y.[Ying],
Zhou, H.[Hui],
Accurately Stable Q-Compensated Reverse-Time Migration Scheme for
Heterogeneous Viscoelastic Media,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Li, W.[Wenda],
Wu, T.Q.[Tian-Qi],
Liu, H.[Hong],
Structure-Preserving Random Noise Attenuation Method for Seismic Data
Based on a Flexible Attention CNN,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Guo, Z.Q.[Zhi-Qi],
Zhao, D.Y.[Dan-Yu],
Liu, C.[Cai],
A New Seismic Inversion Scheme Using Fluid Dispersion Attribute for
Direct Gas Identification in Tight Sandstone Reservoirs,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Zhao, B.H.[Bing-Hui],
Han, L.G.[Li-Guo],
Zhang, P.[Pan],
Yin, Y.C.[Yu-Chen],
Weak Signal Enhancement for Passive Seismic Data Reconstruction Based
on Deep Learning,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Zhu, G.[Guang],
Chen, X.H.[Xiao-Hong],
Li, J.Y.[Jing-Ye],
Guo, K.K.[Kang-Kang],
Data-Driven Seismic Impedance Inversion Based on Multi-Scale Strategy,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Ouyang, Z.Y.[Zhi-Yuan],
Zhang, L.Q.[Li-Qi],
Wang, H.Z.[Hua-Zhong],
Yang, K.[Kai],
High-Dimensional Seismic Data Reconstruction Based on Linear Radon
Transform-Constrained Tensor CANDECOM/PARAFAC Decomposition,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Zhang, Z.[Zheng],
Yan, Z.[Zhe],
Jing, J.K.[Jian-Kun],
Gu, H.[Hanming],
Li, H.Y.[Hai-Ying],
Generating Paired Seismic Training Data with Cycle-Consistent
Adversarial Networks,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Lin, Y.[Youzuo],
Theiler, J.[James],
Wohlberg, B.[Brendt],
Physics-Guided Data-Driven Seismic Inversion: Recent progress and
future opportunities in full-waveform inversion,
SPMag(40), No. 1, January 2023, pp. 115-133.
IEEE DOI
2301
Seismic measurements, Uncertainty, Surface waves,
Surface contamination, Measurement uncertainty, Earthquakes, Predictive models
BibRef
Yin, Y.C.[Yu-Chen],
Han, L.G.[Li-Guo],
Zhang, P.[Pan],
Lu, Z.W.[Zhan-Wu],
Shang, X.[Xujia],
First-Break Picking of Large-Offset Seismic Data Based on CNNs with
Weighted Data,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Zeng, J.W.[Jing-Wen],
Han, L.G.[Li-Guo],
Sparse Inversion for the Iterative Marchenko Scheme of Irregularly
Sampled Data,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Su, Y.Z.[Yi-Zhe],
Wang, D.L.[De-Li],
Hu, B.[Bin],
Gong, X.B.[Xiang-Bo],
Zhang, J.M.[Jun-Ming],
Supervirtual Refraction Interferometry in the Radon Domain,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
seismic first arrivals.
BibRef
Deng, W.[Wubing],
Cao, Q.S.[Qing-Song],
Morozov, I.B.[Igor B.],
Fu, L.Y.[Li-Yun],
Seismic-Q Compensation by Iterative Time-Domain Deconvolution,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Wu, C.L.[Cheng-Liang],
Feng, B.[Bo],
Song, X.N.[Xiao-Nan],
Wang, H.Z.[Hua-Zhong],
Xu, R.W.[Rong-Wei],
Sheng, S.[Shen],
Automatic Horizon Picking Using Multiple Seismic Attributes and
Markov Decision Process,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Zhang, P.[Pan],
Wu, R.S.[Ru-Shan],
Han, L.G.[Li-Guo],
Zhou, Y.X.[Yi-Xiu],
Strong-Scattering Multiparameter Reconstruction Based on Elastic
Direct Envelope Inversion and Full-Waveform Inversion with
Anisotropic Total Variation Constraint,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Borcea, L.[Liliana],
Garnier, J.[Josselin],
Mamonov, A.V.[Alexander V.],
Zimmerling, J.[Jorn],
Waveform Inversion with a Data Driven Estimate of the Internal Wave,
SIIMS(16), No. 1, 2023, pp. 280-312.
DOI Link
2302
BibRef
Gu, Z.Y.[Zhi-Yuan],
Chai, X.[Xintao],
Yang, T.[Taihui],
Deep-Learning-Based Low-Frequency Reconstruction in Full-Waveform
Inversion,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Lv, Q.Z.[Qing-Zhou],
Liu, W.[Wanzeng],
Li, R.[Ran],
Yang, H.[Hui],
Tao, Y.[Yuan],
Wang, M.J.[Meng-Jiao],
Classification of Seismaesthesia Information and Seismic Intensity
Assessment by Multi-Model Coupling,
IJGI(12), No. 2, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Tao, L.R.[Liu-Rong],
Ren, H.R.[Hao-Ran],
Gu, Z.W.[Zhi-Wei],
Acoustic Impedance Inversion from Seismic Imaging Profiles Using Self
Attention U-Net,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Luo, C.[Cong],
Ba, J.[Jing],
Guo, Q.[Qiang],
Sequential Seismic Anisotropic Inversion for VTI Media with Simulated
Annealing Algorithm Aided by Adaptive Setting of Optimization
Parameters,
RS(15), No. 7, 2023, pp. 1891.
DOI Link
2304
BibRef
Yan, D.[Dong],
Tian, Y.[You],
Li, Z.Q.[Zhi-Qiang],
Li, H.L.[Hong-Li],
Upper Mantle Velocity Structure Beneath the Yarlung-Tsangpo Suture
Revealed by Teleseismic P-Wave Tomography,
RS(15), No. 11, 2023, pp. 2724.
DOI Link
2306
BibRef
Parasyris, A.[Apostolos],
Stankovic, L.[Lina],
Stankovic, V.[Vladimir],
Synthetic Data Generation for Deep Learning-Based Inversion for
Velocity Model Building,
RS(15), No. 11, 2023, pp. 2901.
DOI Link
2306
BibRef
Nosov, M.A.[Mikhail A.],
Kolesov, S.V.[Sergey V.],
Sementsov, K.A.[Kirill A.],
Interpretation of Signals Recorded by Ocean-Bottom Pressure Gauges
during the Passage of Atmospheric Lamb Wave on 15 January 2022,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Li, J.[Jun],
Yin, C.C.[Chang-Chun],
Liu, Y.H.[Yun-He],
Wang, L.Y.[Lu-Yuan],
Ma, X.P.[Xin-Peng],
Simulation of Seismoelectric Waves Using Time-Domain Finite-Element
Method in 2D PSVTM Mode,
RS(15), No. 13, 2023, pp. 3321.
DOI Link
2307
BibRef
Deng, F.[Fei],
Hu, J.[Jian],
Wang, X.[Xuben],
Yu, S.[Siling],
Zhang, B.[Bohao],
Li, S.[Shuai],
Li, X.[Xue],
Magnetotelluric Deep Learning Forward Modeling and Its Application in
Inversion,
RS(15), No. 14, 2023, pp. 3667.
DOI Link
2307
BibRef
Han, J.G.[Jian-Guang],
Lü, Q.T.[Qing-Tian],
Gu, B.L.[Bing-Luo],
Yan, J.Y.[Jia-Yong],
Q-Compensated Gaussian Beam Migration under the Condition of
Irregular Surface,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Ding, J.Q.[Jia-Qi],
Zhao, X.F.[Xiao-Feng],
Yang, P.[Pinglv],
Fu, Y.[Yapeng],
A Multi-Objective Geoacoustic Inversion of Modal-Dispersion and
Waveform Envelope Data Based on Wasserstein Metric,
RS(15), No. 19, 2023, pp. 4893.
DOI Link
2310
BibRef
Zhang, X.B.[Xue-Bing],
Song, Z.C.[Zheng-Chun],
Li, B.[Bonan],
Feng, X.[Xuan],
Zhou, J.G.[Jian-Gang],
Yu, Y.P.[Yi-Peng],
Hu, X.[Xin],
The LPR Instantaneous Centroid Frequency Attribute Based on the 1D
Higher-Order Differential Energy Operator,
RS(15), No. 22, 2023, pp. 5305.
DOI Link
2311
BibRef
Liu, L.[Lei],
Sun, Y.[Yong],
Ji, M.[Min],
Wang, H.[Huimeng],
Liu, J.T.[Jian-Tao],
Efficient Construction of Voxel Models for Ore Bodies Using an
Improved Winding Number Algorithm and CUDA Parallel Computing,
IJGI(12), No. 12, 2023, pp. 473.
DOI Link
2312
BibRef
Galone, L.[Luciano],
d'Amico, S.[Sebastiano],
Colica, E.[Emanuele],
Iregbeyen, P.[Peter],
Galea, P.[Pauline],
Rivero, L.[Lluís],
Villani, F.[Fabio],
Assessing Shallow Soft Deposits through Near-Surface Geophysics and
UAV-SfM: Application in Pocket Beaches Environments,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
horizontal-to-vertical spectral ratio, seismic ambient noise, pocket beach,
Malta, near-surface geophysics, electrical resistivity tomography,
photogrammetry
BibRef
Ding, M.[Mu],
Zhou, Y.[Yatong],
Chi, Y.[Yue],
Self-Attention Generative Adversarial Network Interpolating and
Denoising Seismic Signals Simultaneously,
RS(16), No. 2, 2024, pp. 305.
DOI Link
2402
BibRef
Xia, M.M.[Mu-Ming],
Zhou, H.[Hui],
Jiang, C.[Chuntao],
Cui, J.M.[Jin-Ming],
Zeng, Y.[Yong],
Chen, H.[Hanming],
Comparative Study of 2D Lattice Boltzmann Models for Simulating
Seismic Waves,
RS(16), No. 2, 2024, pp. 285.
DOI Link
2402
BibRef
Druskin, V.[Vladimir],
Moskow, S.[Shari],
Zaslavsky, M.[Mikhail],
Reduced Order Modeling Inversion of Monostatic Data in a
Multi-scattering Environment,
SIIMS(17), No. 1, 2024, pp. 334-350.
DOI Link
2404
BibRef
Sun, H.[Hui],
Gao, F.[Fuliu],
Huang, X.G.[Xing-Guo],
Zhang, J.[Jian],
Li, M.[Meng],
Zhao, X.Y.[Xiao-Yan],
Time-Frequency Analysis Method of Seismic Data Based on Sparse
Constraints for Road Detection,
ITS(25), No. 3, March 2024, pp. 2748-2756.
IEEE DOI
2405
Time-frequency analysis, Roads, Transforms, Surveys, Geology,
Noise level, Mathematical models, Seismic data processing,
seismic exploration
BibRef
Bahia, B.[Breno],
JafarGandomi, A.[Arash],
Sacchi, M.D.[Mauricio D.],
Hypercomplex Processing of Vector Field Seismic Data: Toward
vector-valued signal processing,
SPMag(41), No. 2, March 2024, pp. 29-41.
IEEE DOI
2406
[Hypercomplex Signal and Image Processing]
Seismic measurements, Systematics, Source separation, Reviews,
Algebra, Quaternions, Seismology, Complexity theory, Vectors
BibRef
Zhang, J.M.[Jun-Ming],
Wang, D.L.[De-Li],
Hu, B.[Bin],
Gong, X.B.[Xiang-Bo],
Chen, Y.F.[Yi-Fei],
Zhang, Y.[Yang],
Multi-Shot Simultaneous Deghosting for Virtual-Shot Gathers via
Integrated Sparse and Nuclear Norm Constraint Inversion,
RS(16), No. 12, 2024, pp. 2075.
DOI Link
2406
BibRef
Zhang, H.[Hao],
Ma, J.W.[Jian-Wei],
Optimal Transport with a New Preprocessing for Deep-Learning Full
Waveform Inversion,
ICIP22(1446-1450)
IEEE DOI
2211
Deep learning, Seismic measurements, Recurrent neural networks,
Transforms, Geophysics, Probability density function,
integration affine transform
BibRef
Hernandez-Rojas, A.[Alejandra],
Arguello, H.[Henry],
3D Geometry Design via End-To-End Optimization for Land Seismic
Acquisition,
ICIP22(4053-4057)
IEEE DOI
2211
Geometry, Seismic measurements, Costs, Neural networks, Jitter,
Surfaces, Seismic Acquisition Geometry, End-to-End Optimization,
Undersampling Rate
BibRef
Picetti, F.[Francesco],
Lipari, V.[Vincenzo],
Bestagini, P.[Paolo],
Tubaro, S.[Stefano],
Anti-Aliasing Add-On for Deep Prior Seismic Data Interpolation,
ICIP21(1979-1983)
IEEE DOI
2201
Interpolation, Laplace equations, Neural networks,
Machine learning, Tools, Spatial databases, spatial aliasing,
convolutional neural network
BibRef
Lin, Y.,
Theiler, J.,
Wohlberg, B.,
Wu, Y.,
Zhang, Z.,
Data-driven Methods for Solving Large-scale Inverse Problems with
Applications to Subsurface Imaging,
SSIAI20(13-13)
IEEE DOI
2009
convolutional neural nets, geophysical image processing,
geophysical prospecting, geophysical techniques,
Convolutional neural networks
BibRef
Abbas, A.[Ahmed],
Swoboda, P.[Paul],
Bottleneck Potentials in Markov Random Fields,
ICCV19(3174-3183)
IEEE DOI
2004
combinatorial mathematics, graph theory, inverse problems,
Markov processes, minimisation, random processes,
Image segmentation
BibRef
Angulo Bustos, H.I.[Harold Ivan],
dos Santos Silva, M.P.[Marcelino Pereira],
A MAP algorithm for AVO seismic inversion based on the mixed (L2,
non-L2) norms to separate primary and multiple signals in slowness
space,
WACV09(1-6).
IEEE DOI
0912
BibRef
Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Geological Analysis, Rocks .