Subsurface Flow and Transport

Team Leader

Dan O'Malley

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Bailian Chen

• Oil/gas production forecasting and optimization
• Geologic CO₂ storage
• Machine learning and reduced-order modeling
• Data assimilation and uncertainty quantification
• Value of information assessment

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Shaoping Chu

• Subsurface flow and transport model development and simulation
• System level model development, application and uncertainty analysis
• CO₂ sequestration and risk analysis
• Performance assessment modeling and analysis
• Marine biogeochemistry, interactions between atmosphere-ocean-land

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Jeffrey Hyman

• Subsurface flow and transport modeling
• Discrete Fracture Network generation and analysis (dfnWorks)
• Stochastic pore-scale generation
• Graph theoretical approaches for system reduction, reduced order models
• Particle based transport analysis, numerical analysis
• Stochastic hydrology, computational mesh generation

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Qinjun Kang

• Pore-scale and multiscale modeling of transport and interfacial phenomena in porous media
• Hydrocarbon exploration and production
• Geologic storage of carbon dioxide and nuclear waste
• Coupled mass transport and electrochemical processes in fuel cells and batteries

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Nataliia Makedonska

• Subsurface flow and transport simulation in fractured media
• Modeling & analysis of contaminant transport, reservoir-scale DFN natural gas production prediction, CO₂ sequestration, and geothermal reservoir flow.
• Software development (dfnWorks): particle tracking capability, development and implementation of fracture aperture variability
• Meshing algorithms for discrete fracture network mesh production
• Subsurface flow and transport modeling using PFLOTRAN & FEHM

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Daniel O'Malley

• Subsurface flow and transport
• Inverse analysis, data assimilation, and uncertainty quantification
• Quantum computing
• Machine learning

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Rajesh Pawar

• Numerical simulation and development of coupled thermal, hydrologic, mechanical, and chemical processes in complex porous media with applications to:
  • CO₂ sequestration
  • Conventional oil & gas production
  • Unconventional oil & gas production
  • Enhanced oil recovery
  • Nuclear waste disposal
  • Groundwater contamination

• Risk Assessment and System Modeling
  • Machine Learning & Reduced Order Model development
  • Uncertainty quantification

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Philip Stauffer

• Hydrogeology, focused on coupled thermal, hydrological, and chemical (THC) simulations and addition of mechanical impacts (THMC)
• FEHM developer including multiphase transport, isotopic fractionation, water thermodynamics, precipitation/dissolution, relative humidity boundaries, and salt functions
• Salt Repository Work Package Manager for the Spent Fuel and Waste Disposition program
• LANL lead for the US-China Clean Energy Research Center, Advanced Coal Technology Consortium
• Developer for Carbon Capture and Storage risk analysis tools (CO2PENS, NRAP IAM).

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Matthew Sweeney

• Computational fluid dynamics, geological and geophysical flows
• Eulerian-Eulerian multiphase models
• Discrete fracture network, discrete fracture matrix modeling
• Computational geometry
• Volcanology

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Monty Vesselinov

• Machine learning, blind source separation, feature extraction, data compression, high-performance and quantum computing
• Model inversion, parameter estimation, uncertainty, sensitivity and risk analysis, performance assessment, decision support (MADS)
• Experimental and remediation design
• Simulation of multiphase flow, transport and biogeochemical reactions in porous/fractured media (CHROTRAN)
• Hydrogeology and biogeochemistry, reservoir modeling
• Characterization of heterogeneity of subsurface flow and transport medium, high-resolution stochastic imaging, stochastic inversion

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Hari Viswanathan

• HPC Simulation of flow, reactive transport in porous and fractured media: hydraulic fracturing (DOE FE Oil and Gas, LDRD, DOE BES, Chevron); CO₂ sequestration (Southwest Regional Partnership for Carbon Sequestration); nuclear waste disposal (Spent Fuel Waste Disposition); nuclear nonproliferation
• Integrating simulation and experiment from the pore to reservoir scale: Lattice Boltzmann simulation and microfluidics experiments; fracture propagation simulation and triaxial coreflood experiments; discrete fracture network simulation of flow through reservoir scale fracture networks
• Uncertainty quantification: development of reduced order models of HPC simulation for use in uncertainty quantification studies; utilizing machine learning and graph theory to develop reduced order models of computational physics simulations

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Terry Miller

• Mesh Generation and model setup: regional flow and transport, nuclear waste disposal, CO₂ sequestration, watershed management, permafrost
• Advancing next generation meshing, model integration, geologic data, and software practices
• Software development, maintenance, and QA (e.g., LaGriT and FEHM)

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Bulbul Ahmmed

• Geothermal resource characterization using machine learning
• Subsurface reactive transport modeling in porous and fractured media
• Feature extraction from multi-variable and multi-scale data
• Inverse analysis, parameter estimation, and uncertainty quantification
• Novel machine learning tool development for subsurface characterization

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Mohamed Mehana

• Subsurface phenomena and fluid flow in porous media
• Molecular simulation and computational geochemistry
• Numerical modeling and reservoir simulation
• Deep learning and applied machine learning
• Salinity impact on water dynamics in porous media and interfaces

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Adam Rupe

• Data-driven approaches for nonlinear dynamical systems
• Transfer operators
• Spontaneous self-organization, pattern formation, and coherent structures
• Geophysical fluid flows

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Min Liu

• Reactive transport simulation in porous and fractured media
• Geologic storage of carbon dioxide and spent nuclear waste modelling
• Hydrocarbon exploration and production

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Hao Wu

• Hydrothermal fluid systems
• Fracture network characterization
• Carbon sequestration
• Numerical simulation
• Machine learning

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Bicheng Yan

• Numerical reservoir simulation of multiphase and compositional flow in porous media with applications in hydrocarbon recovery and geological storage of CO2
• Fractured reservoir modeling
• Machine/deep learning development and application into subsurface modeling