19.6.3.11.2 Seismic Inversion

Chapter Contents (Back)
Seismic Processing. Seismology. Application, Seismic.

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], Sallarčs, 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., Chen, X., Luo, C., 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

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.[Shuanggen],
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

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

Bai, P.[Peng], Vignoli, G.[Giulio], Viezzoli, A.[Andrea], Nevalainen, J.[Jouni], Vacca, G.[Giuseppina],
(Quasi-)Real-Time Inversion of Airborne Time-Domain Electromagnetic Data via Artificial Neural Network,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
EM data, for mineral exploration. 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

Di, Q., Li, H., Xue, G., Zhang, L.,
Pseudo-2-D Transdimensional Bayesian Inversion of the Full Waveform TEM Response From PRBS Source,
GeoRS(58), No. 11, November 2020, pp. 7602-7610.
IEEE DOI 2011
Bayes methods, Data models, Markov processes, Electromagnetics, Earth, Signal resolution, Conductivity, transient electromagnetic method (TEM) 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), Computer architecture, 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


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 .


Last update:Jun 9, 2021 at 21:04:26