| Convolutional neural network for seismic impedance inversion V Das, A Pollack, U Wollner, T Mukerji Geophysics 84 (6), R869-R880, 2019 | 399 | 2019 |
| Prestack and poststack inversion using a physics-guided convolutional neural network R Biswas, MK Sen, V Das, T Mukerji Interpretation 7 (3), SE161-SE174, 2019 | 192 | 2019 |
| Petrophysical properties prediction from prestack seismic data using convolutional neural networks V Das, T Mukerji Geophysics 85 (5), N41-N55, 2020 | 90 | 2020 |
| Petrophysical properties prediction from pre-stack seismic data using convolutional neural networks V Das, T Mukerji SEG Technical Program Expanded Abstracts 2019, 2328-2332, 2019 | 90 | 2019 |
| Numerical simulation of coupled fluid-solid interaction at the pore scale: A digital rock-physics technology V Das, T Mukerji, G Mavko Geophysics 84 (4), WA71-WA81, 2019 | 28 | 2019 |
| Numerical simulation of coupled fluid-solid interaction at the pore scale: A digital rock-physics technology V Das, T Mukerji, G Mavko SEG Technical Program Expanded Abstracts 2018, 3673-3677, 2018 | 28 | 2018 |
| An Appraisal of the 2001 Bhuj Earthquake (Mw 7.7, India) Source Zone: Fractal Dimension and b Value Mapping of the Aftershock Sequence JR Kayal, V Das, U Ghosh Pure and Applied Geophysics 169, 2127-2138, 2012 | 28 | 2012 |
| Pre-stack inversion using a physics-guided convolutional neural network R Biswas, MK Sen, V Das, T Mukerji SEG international exposition and annual meeting, D043S152R007, 2019 | 21 | 2019 |
| Prestack and poststack inversion using a physics-guided convolutional neural network: Interpretation, 7 R Biswas, MK Sen, V Das, T Mukerji SE161–SE174, 2019 | 14 | 2019 |
| Compressibility predictions using digital thin-section images of rocks V Das, N Saxena, R Hofmann Computers & geosciences 139, 104482, 2020 | 11 | 2020 |
| Effect of rock physics modeling in impedance inversion from seismic data using convolutional neural network V Das, A Pollack, U Wollner, T Mukerji The 13th SEGJ International Symposium, Tokyo, Japan, 12-14 November 2018 …, 2019 | 10 | 2019 |
| Convolutional neural network for seismic impedance inversion. Geophysics, 84, R869–R880 V Das, A Pollack, U Wollner, T Mukerji Preprint not peer reviewed, 2019 | 10 | 2019 |
| Convolutional neural network for seismic impedance inversion: 88th Annual International Meeting, SEG, Expanded Abstracts, 2071–2075, doi: 10.1190/segam2018-2994378.1 V Das, A Pollack, U Wollner, T Mukerji Abstract, 2018 | 9 | 2018 |
| Scale effects of velocity dispersion and attenuation (Q−1) in layered viscoelastic medium V Das, T Mukerji, G Mavko Geophysics 84 (3), T147-T166, 2019 | 7 | 2019 |
| Traditional Feature Based vs Direct Machine Learning Based AVO Classification V Das, T Mukerji 81st EAGE Conference and Exhibition 2019, 2019 | 5 | 2019 |
| Estimation of Water Saturation in Shale Formation Using In Situ Multifrequency Dielectric Permittivity Y Cho, SS Dolan, N Saxena, V Das Geofluids 2022, 2022 | 3 | 2022 |
| Self potential data inversion using particle swarm optimization A Ghosal, V Das, S Srivastava, BB Bhattacharya 20th IAGA WG 1.2 Workshop on Electromagnetic induction in the Earth. Giza, Egypt, 2010 | 3 | 2010 |
| Prediction of coal-bed permeability using artificial neural network V Das, R Chatterjee 9th biennial international conference and exposition on petroleum geophysics …, 2012 | 2 | 2012 |
| A comparative analysis of particle swarm optimization (PSO) and very fast simulated annealing (VFSA) inversion techniques for self-potential (SP) anomalies V Das, A Ghosal, S Shalivahan, BB Bhattacharya SEG International Exposition and Annual Meeting, SEG-2010-1845, 2010 | 2 | 2010 |
| Finite element modeling of coupled fluid-solid interaction at the pore scale of digital rock samples V Das, T Mukerji, G Mavko The 13th SEGJ International Symposium, Tokyo, Japan, 12-14 November 2018 …, 2019 | 1 | 2019 |
Tapan MukerjiStanford UniversityDirección de correo verificada de stanford.edu
