| A comparison of classification techniques for seismic facies recognition T Zhao, V Jayaram, A Roy, KJ Marfurt Interpretation 3 (4), SAE29-SAE58, 2015 | 203* | 2015 |
| Seismic facies classification using different deep convolutional neural networks T Zhao SEG Technical Program Expanded Abstracts 2018, 2046-2050, 2018 | 91 | 2018 |
| Semisupervised multiattribute seismic facies analysis J Qi, T Lin, T Zhao, F Li, K Marfurt Interpretation 4 (1), SB91-SB106, 2016 | 80* | 2016 |
| Characterizing a turbidite system in Canterbury Basin, New Zealand, using seismic attributes and distance-preserving self-organizing maps T Zhao, J Zhang, F Li, KJ Marfurt Interpretation 4 (1), SB79-SB89, 2016 | 62* | 2016 |
| A fault detection workflow using deep learning and image processing T Zhao, P Mukhopadhyay SEG Technical Program Expanded Abstracts 2018, 1966-1970, 2018 | 60 | 2018 |
| Constraining self-organizing map facies analysis with stratigraphy: An approach to increase the credibility in automatic seismic facies classification T Zhao, F Li, KJ Marfurt Interpretation 5 (2), T163-T171, 2017 | 48 | 2017 |
| Brittleness evaluation of resource plays by integrating petrophysical and seismic data analysis B Zhang, T Zhao, X Jin, KJ Marfurt Interpretation 3 (2), T81-T92, 2015 | 46 | 2015 |
| Estimation of total organic carbon and brittleness volume S Verma, T Zhao, KJ Marfurt, D Devegowda Interpretation 4 (3), T373-T385, 2016 | 40 | 2016 |
| Lithofacies classification in Barnett Shale using proximal support vector machines T Zhao*, V Jayaram, KJ Marfurt, H Zhou SEG Technical Program Expanded Abstracts 2014, 1491-1495, 2014 | 40* | 2014 |
| Seismic attribute selection for unsupervised seismic facies analysis using user-guided data-adaptive weights T Zhao, F Li, KJ Marfurt Geophysics 83 (2), O31-O44, 2018 | 34 | 2018 |
| Seismic attenuation attributes with applications on conventional and unconventional reservoirs F Li, S Verma, H Zhou, T Zhao, KJ Marfurt Interpretation 4 (1), SB63-SB77, 2016 | 27* | 2016 |
| TOC estimation in the Barnett Shale from triple combo logs using support vector machine T Zhao*, S Verma, D Devegowda, V Jayaram SEG Technical Program Expanded Abstracts 2015, 791-795, 2015 | 22 | 2015 |
| UNCONVENTIONAL, RESERVOIR CHARACTERIZATION BASED (ON SPECTRALLY CORRECTED SEISMIC E LI, H Zhou, T Zhao, KJ Marfurt Journal of Seismic Exploration 25, 447-461, 2016 | 18 | 2016 |
| Supervised and unsupervised learning: How machines can assist quantitative seismic interpretation T Zhao, S Verma, J Qi, KJ Marfurt 2015 SEG Annual Meeting, 2015 | 15 | 2015 |
| Multispectral coherence: Which decomposition should we use? B Lyu, J Qi, F Li, Y Hu, T Zhao, S Verma, KJ Marfurt Interpretation 8 (1), T115-T129, 2020 | 13 | 2020 |
| Horizon-based semiautomated nonhyperbolic velocity analysis B Zhang, T Zhao, J Qi, KJ Marfurt Geophysics 79 (6), U15-U23, 2014 | 12 | 2014 |
| 3D convolutional neural networks for efficient fault detection and orientation estimation T Zhao SEG Technical Program Expanded Abstracts 2019, 2418-2422, 2019 | 11 | 2019 |
| Enrich the interpretation of seismic image segmentation by estimating epistemic uncertainty T Zhao, X Chen SEG Technical Program Expanded Abstracts 2020, 1444-1448, 2020 | 10 | 2020 |
| Facies analysis by integrating 3D seismic attributes and well logs for prospect identification and evaluation—A case study from Northwest China X Wang, B Zhang, T Zhao, J Hang, H Wu, Z Yong Interpretation 5 (2), SE61-SE74, 2017 | 10 | 2017 |
| Highlighting discontinuities with variational mode decomposition based coherence B Lyu, F Li, J Qi, T Zhao, KJ Marfurt 2018 SEG International Exposition and Annual Meeting, 2018 | 9 | 2018 |
Fangyu Li (李方昱)Professor, Beijing University of TechnologyVerified email at bjut.edu.cn
