Accelerating geostatistical seismic inversion using TensorFlow: A heterogeneous distributed deep learning framework M Liu, D Grana Computers & Geosciences 124, 37-45, 2019 | 40 | 2019 |
Recycling of oceanic crust from a stagnant slab in the mantle transition zone: Evidence from Cenozoic continental basalts in Zhejiang Province, SE China YQ Li, CQ Ma, PT Robinson, Q Zhou, ML Liu Lithos 230, 146-165, 2015 | 40 | 2015 |
Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks M Liu, M Jervis, W Li, P Nivlet Geophysics 85 (4), O47-O58, 2020 | 38 | 2020 |
A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data D Grana, L Azevedo, M Liu Geophysics 85 (4), WA41-WA52, 2020 | 33 | 2020 |
Stochastic nonlinear inversion of seismic data for the estimation of petroelastic properties using the ensemble smoother and data reparameterization M Liu, D Grana Geophysics 83 (3), M25-M39, 2018 | 33 | 2018 |
Time-lapse seismic history matching with an iterative ensemble smoother and deep convolutional autoencoder M Liu, D Grana Geophysics 85 (1), M15-M31, 2020 | 32 | 2020 |
Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder M Liu, D Grana Advances in Water Resources 142, 103634, 2020 | 17 | 2020 |
Ensemble-based seismic history matching with data reparameterization using convolutional autoencoder M Liu, D Grana SEG Technical Program Expanded Abstracts 2018, 3156-3160, 2018 | 14 | 2018 |
3D seismic facies classification using convolutional neural network and semi-supervised generative adversarial network M Liu, W Li, M Jervis, P Nivlet SEG Technical Program Expanded Abstracts 2019, 4995-4999, 2019 | 11 | 2019 |
Stochastic inversion method of time-lapse controlled source electromagnetic data for CO2 plume monitoring M Ayani, D Grana, M Liu International Journal of Greenhouse Gas Control 100, 103098, 2020 | 8 | 2020 |
Prediction of CO₂ Saturation Spatial Distribution Using Geostatistical Inversion of Time-Lapse Geophysical Data D Grana, M Liu, M Ayani IEEE Transactions on Geoscience and Remote Sensing 59 (5), 3846-3856, 2020 | 7 | 2020 |
Generation and evolution of overpressure caused by hydrocarbon generation in the Jurassic source rocks of the central Junggar Basin, northwestern China X Guo, S He, K Liu, Z Yang, S Yuan, M Liu AAPG Bulletin 103 (7), 1553-1574, 2019 | 7 | 2019 |
Data driven machine learning models for shale gas adsorption estimation L Wang, M Liu, A Altazhanov, B Syzdykov, J Yan, X Meng, K Jin SPE Europec, 2020 | 6 | 2020 |
Ensemble-based joint inversion of PP and PS seismic data using full Zoeppritz equations M Liu, D Grana 2018 SEG International Exposition and Annual Meeting, 2018 | 4 | 2018 |
Uncertainty quantification in stochastic inversion with dimensionality reduction using variational autoencoder M Liu, D Grana, LP de Figueiredo Geophysics 87 (2), M43-M58, 2022 | 3 | 2022 |
Machine-learning based prediction of phase velocities and phase angles from group velocities and group angles in an anisotropic elastic medium—A feasibility study S Mallick, P Rath, M Liu, SA Darhower, CD Minh Ha, AM Moraes, ... SEG Technical Program Expanded Abstracts 2019, 2443-2447, 2019 | 2 | 2019 |
Deep learning applied to seismic facies classification M Jervis, M Liu, P Nivlet 2019 New Advances in Seismic Interpretation Workshop, 2018 | 2 | 2018 |
Deep learning network optimization and hyperparameter tuning for seismic lithofacies classification M Jervis, M Liu, R Smith The Leading Edge 40 (7), 514-523, 2021 | 1 | 2021 |
Deep learning network optimization and hyper-parameter tuning M Jervis, M Liu, W Li, R Smith SEG International Exposition and Annual Meeting, 2019 | 1 | 2019 |
Seismic history matching in the low-dimensional model and data space using deep convolutional auto-encoder M Liu, D Grana SEG Technical Program Expanded Abstracts 2019, 3324-3328, 2019 | 1 | 2019 |