Personal information

Other IDs

Loop profile: 1672735

Activities

Collapse all

Works (19)

Bayesian neural network and Bayesian physics-informed neural network via variational inference for seismic petrophysical inversion

GEOPHYSICS
2024-11-01 | Journal article
DOI: 10.1190/geo2023-0737.1
Contributors: Peng Li; Dario Grana; Mingliang Liu
Source: check_circle
Crossref

GeosPIn: A MATLAB library for geostatistical petrophysical inversion

GEOPHYSICS
2024-09-01 | Journal article
DOI: 10.1190/geo2023-0467.1
Contributors: Dario Grana; Mingliang Liu; Leandro de Figueiredo
Source: check_circle
Crossref

Geostatistical Inversion for Subsurface Characterization Using Stein Variational Gradient Descent With Autoencoder Neural Network: An Application to Geologic Carbon Sequestration

Journal of Geophysical Research: Solid Earth
2024-07 | Journal article
DOI: 10.1029/2024JB029073
Contributors: Mingliang Liu; Dario Grana; Tapan Mukerji
Source: check_circle
Crossref

Geostatistical Inversion for Subsurface Characterization Using Stein Variational Gradient Descent with Autoencoder Neural Network: An Application to Geologic Carbon Sequestration

2024-03-21 | Preprint
DOI: 10.22541/essoar.171104220.03785450/v1
Contributors: Mingliang Liu; Dario Grana; Tapan Mukerji
Source: check_circle
Crossref

Probabilistic physics-informed neural network for seismic petrophysical inversion

GEOPHYSICS
2024-03-01 | Journal article
DOI: 10.1190/geo2023-0214.1
Contributors: Peng Li; Mingliang Liu; Motaz Alfarraj; Pejman Tahmasebi; Dario Grana
Source: check_circle
Crossref

Frequency-domain electromagnetic induction for the prediction of electrical conductivity and magnetic susceptibility using geostatistical inversion and randomized tensor decomposition

GEOPHYSICS
2023-11-01 | Journal article
DOI: 10.1190/geo2022-0443.1
Contributors: Mingliang Liu; João Narciso; Dario Grana; Ellen Van De Vijver; Leonardo Azevedo
Source: check_circle
Crossref

Computation of effective elastic moduli of rocks using hierarchical homogenization

Journal of the Mechanics and Physics of Solids
2023-05 | Journal article
DOI: 10.1016/j.jmps.2023.105268
Contributors: Rasool Ahmad; Mingliang Liu; Michael Ortiz; Tapan Mukerji; Wei Cai
Source: check_circle
Crossref

Joint Inversion of Geophysical Data for Geologic Carbon Sequestration Monitoring: A Differentiable Physics‐Informed Neural Network Model

Journal of Geophysical Research: Solid Earth
2023-03 | Journal article
DOI: 10.1029/2022JB025372
Contributors: Mingliang Liu; Divakar Vashisth; Dario Grana; Tapan Mukerji
Source: check_circle
Crossref

Hierarchical Homogenization With Deep‐Learning‐Based Surrogate Model for Rapid Estimation of Effective Permeability From Digital Rocks

Journal of Geophysical Research: Solid Earth
2023-02 | Journal article
DOI: 10.1029/2022JB025378
Contributors: Mingliang Liu; Rasool Ahmad; Wei Cai; Tapan Mukerji
Source: check_circle
Crossref

Randomized Tensor Decomposition for Large-Scale Data Assimilation Problems for Carbon Dioxide Sequestration

Mathematical Geosciences
2022-10 | Journal article
DOI: 10.1007/s11004-022-10005-1
Contributors: Mingliang Liu; Dario Grana; Tapan Mukerji
Source: check_circle
Crossref

Hierarchical homogenization with deep-learning-based surrogate model for rapid estimation of effective permeability from digital rocks

2022-08-13 | Preprint
DOI: 10.1002/essoar.10512161.1
Contributors: Mingliang Liu; Rasool Ahmad; Wei Cai; Tapan Mukerji
Source: check_circle
Crossref

Joint Inversion of Geophysical Data for Geologic Carbon Sequestration Monitoring: A Differentiable Physics-Informed Deep Learning Model

2022-08-13 | Preprint
DOI: 10.1002/essoar.10512162.1
Contributors: Mingliang Liu; Dario Grana; Tapan Mukerji
Source: check_circle
Crossref

Multiscale Fusion of Digital Rock Images Based on Deep Generative Adversarial Networks

Geophysical Research Letters
2022-05-16 | Journal article
DOI: 10.1029/2022GL098342
Contributors: Mingliang Liu; Tapan Mukerji
Source: check_circle
Crossref

Uncertainty quantification in stochastic inversion with dimensionality reduction using variational autoencoder

GEOPHYSICS
2022-03-01 | Journal article
DOI: 10.1190/geo2021-0138.1
Contributors: Mingliang Liu; Dario Grana; Leandro Passos de Figueiredo
Source: check_circle
Crossref

Multiscale fusion of digital rock images based on deep generative adversarial networks

2022-02-18 | Preprint
DOI: 10.1002/essoar.10510572.1
Contributors: Mingliang Liu; Tapan Mukerji
Source: check_circle
Crossref

A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data

GEOPHYSICS
2020-07-01 | Journal article
DOI: 10.1190/geo2019-0405.1
Contributors: Dario Grana; Leonardo Azevedo; Mingliang Liu
Source: check_circle
Crossref

Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks

GEOPHYSICS
2020-07-01 | Journal article
DOI: 10.1190/geo2019-0627.1
Contributors: Mingliang Liu; Michael Jervis; Weichang Li; Philippe Nivlet
Source: check_circle
Crossref

Time-lapse seismic history matching with an iterative ensemble smoother and deep convolutional autoencoder

GEOPHYSICS
2020-01-01 | Journal article
DOI: 10.1190/geo2019-0019.1
Contributors: Mingliang Liu; Dario Grana
Source: check_circle
Crossref

Stochastic nonlinear inversion of seismic data for the estimation of petroelastic properties using the ensemble smoother and data reparameterization

GEOPHYSICS
2018-05-01 | Journal article
DOI: 10.1190/geo2017-0713.1
Contributors: Mingliang Liu; Dario Grana
Source: check_circle
Crossref

Peer review (18 reviews for 9 publications/grants)

Review activity for Applied energy (2)
Review activity for Computational geosciences. (2)
Review activity for Computers & geosciences. (2)
Review activity for Geoenergy science and engineering. (4)
Review activity for Geophysical research letters. (1)
Review activity for Journal of petroleum exploration and production technology. (2)
Review activity for Mathematical geology. (3)
Review activity for Natural resources research. (1)
Review activity for Water resources research. (1)
How many people are using ORCID?