Bio

I am currently a postdoctoral scholar working with Tapan Mukerji on digital rock physics at Stanford University. My research focuses on geophysics inverse problems, seismic reservoir characterization, history matching, digital rock physics, data assimilation and deep learning. I completed my PhD degree in geophysics from the University of Wyoming in 2021 under the supervision of Dario Grana, and earned the bachelor and master degree from China University of Geosciences (Wuhan) in 2013 and 2016, respectively.

Honors & Awards

  • Research Scholarship, International Association for Mathematical Geosciences (2021)
  • Outstanding Ph.D. Student, University of Wyoming (2021)
  • James L. Allen Scholarship, Society of Exploration Geophysicists (2019)
  • Technical Program Travel Grant, Society of Exploration Geophysicists (2019)

Professional Education

  • Bachelor of Science, China Univ Of Geosciences (2013)
  • Master of Engineering, China Univ Of Geosciences (2016)
  • Doctor of Philosophy, University of Wyoming (2021)

Stanford Advisors

Contact

  • Academic
    University - Scholar Department: Department of Energy Science and Engineering Position: Postdoctoral Scholar

Additional Info

Links

All Publications

  • Hierarchical Homogenization With Deep-Learning-Based Surrogate Model for Rapid Estimation of Effective Permeability From Digital Rocks JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH Liu, M., Ahmad, R., Cai, W., Mukerji, T. 2023; 128 (2)

    View details for DOI 10.1029/2022JB025378

    View details for Web of Science ID 000936298000001

  • Joint Inversion of Geophysical Data for Geologic Carbon Sequestration Monitoring: A Differentiable Physics-Informed Deep Learning Model Journal of Geophysical Research: Solid Earth Liu, M., Vashisth, D., Grana, D., Mukerji, T. 2023; 128 (3)

    View details for DOI 10.1029/2022JB025372

  • Multiscale Fusion of Digital Rock Images Based on Deep Generative Adversarial Networks GEOPHYSICAL RESEARCH LETTERS Liu, M., Mukerji, T. 2022; 49 (9)

    View details for DOI 10.1029/2022GL098342

    View details for Web of Science ID 000795770000001

  • Uncertainty quantification in stochastic inversion with dimensionality reduction using variational autoencoder GEOPHYSICS Liu, M., Grana, D., de Figueiredo, L. P. 2022; 87 (2): M43-M58

    View details for DOI 10.1190/geo2021-0138.1

  • Stochastic nonlinear inversion of seismic data for the estimation of petroelastic properties using the ensemble smoother and data reparameterization GEOPHYSICS Liu, M., Grana, D. 2018; 83 (3): M25–M39

    View details for DOI 10.1190/GEO2017-0713.1

    View details for Web of Science ID 000443596300068

  • Randomized Tensor Decomposition for Large-Scale Data Assimilation Problems for Carbon Dioxide Sequestration MATHEMATICAL GEOSCIENCES Liu, M., Grana, D., Mukerji, T. 2022

    View details for DOI 10.1007/s11004-022-10005-1

    View details for Web of Science ID 000802314500001

  • Prediction of CO2 Saturation Spatial Distribution Using Geostatistical Inversion of Time-Lapse Geophysical Data IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Grana, D., Liu, M., Ayani, M. 2021; 59 (5): 3846-3856

    View details for DOI 10.1109/TGRS.2020.3018910

    View details for Web of Science ID 000642096400017

  • Stochastic inversion method of time-lapse controlled source electromagnetic data for CO2 plume monitoring INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL Ayani, M., Grana, D., Liu, M. 2020; 100

    View details for DOI 10.1016/j.ijggc.2020.103098

    View details for Web of Science ID 000567840400002

  • Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder ADVANCES IN WATER RESOURCES Liu, M., Grana, D. 2020; 142

    View details for DOI 10.1016/j.advwatres.2020.103634

    View details for Web of Science ID 000550807600004

  • A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data GEOPHYSICS Grana, D., Azevedo, L., Liu, M. 2020; 85 (4): WA41–WA52

    View details for DOI 10.1190/GEO2019-0405.1

    View details for Web of Science ID 000583755100064

  • Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks GEOPHYSICS Liu, M., Jervis, M., Li, W., Nivlet, P. 2020; 85 (4): O47–O58

    View details for DOI 10.1190/GEO2019-0627.1

    View details for Web of Science ID 000583755100035

  • Time-lapse seismic history matching with an iterative ensemble smoother and deep convolutional autoencoder GEOPHYSICS Liu, M., Grana, D. 2020; 85 (1): M15–M31

    View details for DOI 10.1190/GEO2019-0019.1

    View details for Web of Science ID 000506219100026

  • Generation and evolution of overpressure caused by hydrocarban generation in the Jurassic source rocks of the central Junggar Basin, northwestern China AAPG BULLETIN Guo, X., He, S., Liu, K., Yang, Z., Yuan, S., Liu, M. 2019; 103 (7): 1553–74

    View details for DOI 10.1306/1213181614017139

    View details for Web of Science ID 000475472700002

  • Accelerating geostatistical seismic inversion using TensorFlow: A heterogeneous distributed deep learning framework COMPUTERS & GEOSCIENCES Liu, M., Grana, D. 2019; 124: 37–45

    View details for DOI 10.1016/j.cageo.2018.12.007

    View details for Web of Science ID 000458938800004

  • Recycling of oceanic crust from a stagnant slab in the mantle transition zone: Evidence from Cenozoic continental basalts in Zhejiang Province, SE China LITHOS Li, Y., Ma, C., Robinson, P. T., Zhou, Q., Liu, M. 2015; 230: 146–65

    View details for DOI 10.1016/j.lithos.2015.05.021

    View details for Web of Science ID 000357839000011

https://orcid.org/0000-0002-5783-4490