Zhenxue Dai
Los Alamos National Laboratory, University of La Corunia
Research areas: Environmental Science · Environmental Engineering · Groundwater flow and contamination studies · CO2 Sequestration and Geologic Interactions · Reservoir Engineering and Simulation Methods
0000-0002-0805-7621
About
Zhenxue Dai
College of Construction Engineering, Jilin University
938 Ximinzhu Street, Changchun 130026, China
Email: [email protected]; [email protected]
Education
University of La Coruña, Spain, Civil Engineering, Ph.D. Cum Laude
Central Coal Mining Research Institute, China, Hydrogeology, M.S.
Changchun University of Geology, China, Hydrogeology, B.A.
Appointments
2017-present: College of Construction Engineering, Jilin University, Dean/Professor
2012-2017: Los Alamos National Laboratory, EES-16, Senior Scientist
2008-2012: Los Alamos National Laboratory, EES-16, Staff Scientist
2005-2008: Los Alamos National Laboratory, EES-6, Limited-term Scientist
2004-2005: Advanced Environmental Solutions, LLC, Research Hydrologist
2001-2004: Wright State University, Post-doc Research Associate
1997-2000: University of La Coruña, Spain, Research Assistant
2008-present: Florida State University, Adjunct Professor
2008-present: ChangAn University, China, Adjunct Professor
2013-present: Wright State University, Adjunct Professor
Honors and Awards
1. Superior performance and teamwork awards, Los Alamos National Lab, 2012.
2. A Fellow of the Geological Society of America, GSA Fellow, since 2010.
3. Excellent organizer of Brown Bag Seminar Series, Los Alamos Awards Program, 2009.
4. Outstanding Innovation and Technology Transfer Awards, Los Alamos National Lab, 2008.
5. Cum Laude distinction PhD, University of La Coruña, Spain, 2000.
Research and Teaching Interests
1. Uncertainty quantification and optimization for CO2-Enhanced Oil Recovery (EOR);
2. Coupled simulation of heat transfer, fluid flow (oil-gas-CO2-water) and geochemical reactions (multi-phase and multi-component transport modeling) in heterogeneous media;
3. Characterizations of multi-scale aquifer/reservoir systems with geological, geochemical and geophysical data using geostatistical methods;
4. Risk assessment for CO2 geologic sequestration in reservoirs;
5. Upscaling flow and reactive transport parameters in porous and fractured rocks (in aquifers and reservoirs);
6. Identification of geochemical reaction processes and reservoir heterogeneous structures;
7. Optimal design of injection/pumping wells in the oil reservoirs;
8. Stochastic modeling of flow and reactive solute transport in multimodal heterogeneous formations, including fractured rock and porous media; and
9. Inverse modeling of reactive transport in variably saturated heterogeneous media.
Employment
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Los Alamos National Laboratory Staff Scientist2005 - Present
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Los Alamos National Laboratory Staff Scientist2005 - Present
Education
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University of La Corunia PhD1997 - 2000
Projects & Funding
Projects & funding information is unavailable.
Publications (199)
- Caprock breakthrough pressure for geological CO2 sequestration: advances in characterization and controlling mechanisms Save
- Geometric confinement regulates shape-dependent microplastic migration across air–water interfaces in variably saturated porous media Save
- Quantum-classical estimation of physically scaled groundwater flow and solute transport from normalized quantum states Save
- A structure-constrained inverse distance weighting framework for stochastic simulation of multi-lithofacies sedimentary aquifer architecture Save
- Historical Groundwater Memory Predicts Site‐Specific Persistence Horizons Across Germany Save
- Artificial intelligence-driven monitoring network optimization under reservoir uncertainty for underground hydrogen storage Save
- Applications of artificial intelligence models in seawater intrusion: progress, challenges, and future directions Save
- U-shape convolutional neural network-based granite mineral facies characterization and sorption coefficient uncertainty quantification Save
- Transport and Attenuation of Human Viruses in Groundwater: Assessment of Adsorption-Induced Interfacial Inactivation and Evidence of Aggregation Save
- Machine Learning-Driven Insights into CO2-Driven CH4 Displacement: Impacts of Pore Structure and Flow Conditions Save
- Autonomous inverse modeling of complex groundwater systems via a physics-integrated large language model multi-agent framework Save
- Advances and challenges in machine learning-based identification of organic pollutant sources in heterogeneous aquifers Save
- Localization of Spatiotemporally Heterogeneous Subsurface Flows Using Autoencoder‐Based Deep Learning Framework for Time‐Lapse Self‐Potential Tomography Save
- Machine learning-guided reactive transport modeling of CO2-water-rock interactions in heterogeneous shale Save
- Analysis of the influence mechanisms of key operational parameters on underground hydrogen storage Save
- Data dependency in deep learning-based multi-scale fracture system characterization using hydrogeophysical data Save
- A multi-model framework for risk assessment of high-level radionuclide geological disposal Save
- Multiscale simulation and machine learning sensitivity analysis of pore-structure controls on solute transport in heterogeneous porous media Save
- CO2 Exsolution and Residual Trapping Influenced by Heterogeneity During Imbibition in Conglomerates: A Core‐Scale Multiphase Flow Save
- Combining hydrologic, chemical, and geophysical deep learning-based inversion for heterogeneous aquifer structure identification Save