Research
Research Projects
-
Natural Gas Hydrate FWP: Development, Testing, and Validation of the DEM-Based Particle Transport Code (NETL, DOE-FECM)
PIs: Dr. George Moridis, Dr. Thomas Blasingame -
Gas Storage Optimization: Evaluation of Feasibility and Operating Conditions for Maximization of Gas Storage and Early Recovery of Residual Hydrocarbon in Depleted Reservoirs (Crisman Institute, TAMU)
PIs: Dr. George Moridis, Dr. Thomas Blasingame -
Coupled Processes in Argillite: Investigation of Coupled Processes in Argillite Rock (LBNL, DOE-NE)
PIs: Dr. Jonny Rutqvist -
CyclicGeoH2: Cyclic Injection for Commercial Seismic-Safe Geologic H2 Production (LBNL, DOE-ARPA-E)
PIs: Dr. Mengsu Hu, Dr. Jonny Rutqvist
Technical Skills
-
Programming & High-Performance Computing
- Languages: Modern Fortran (Advanced), C/C++, Python, MATLAB
- Parallel Computing: MPI, OpenMP, CUDA (GPU Programming)
- HPC Environments: Large-scale Linux clusters, Slurm Workload Manager
-
Simulation Software
- TOUGH Suite: TOUGH+RealGasBrine, TOUGH+Hydrate, TOUGHREACT, TOUGH-FLAC
- Geomechanics: FLAC3D, TOUGH-FLAC (coupled THM)
- Custom Development: Independent developer of parallelized Discrete Element Method (DEM) codes
-
Numerical Methods
- Coupled Processes: THMC (Thermal-Hydraulic-Mechanical-Chemical) modeling
- Discretization: Finite Volume Method (FVM), Discrete Element Method (DEM), Discrete Fracture Network (DFN), Embedded Discrete Fracture Model (EDFM)
- Thermodynamics: High-fidelity compositional simulation; flash calculations (Rachford-Rice, Gibbs minimization)
-
Libraries & Tools
- Solvers & Meshing: PETSc, METIS, Gmsh, LaGriT, dfnWorks
- Visualization: Tecplot, ParaView
Modeling Enhanced Geothermal Systems (EGS)
I simulate coupled Thermal-Hydraulic-Mechanical-Chemical (THMC) processes to optimize heat extraction and system longevity in Enhanced Geothermal Systems. By using the Embedded Discrete Fracture Model (EDFM) and Discrete Fracture Network (DFN), I resolve complex fracture networks at field scale to address critical flow assurance challenges.
- Field-scale EGS simulation using EDFM for accurate fracture representation.
- Predicting mineral precipitation and scaling risks in fracture scale.
- Local and global sensitivity analysis of reactive transport in fractured geothermal reservoirs.
High-Fidelity Compositional Simulation
I am developing a robust compositional simulator designed to enhance predictive accuracy for complex recovery processes. My work focuses on algorithmic optimization to ensure stability and speed in highly compositional flows.
- Flash calculation Optimization: Improving robustness by enforcing equal-fugacity and material-balance constraints, and minimizing mixture Gibbs free energy.
- Algorithmic efficiency: Accelerating the solution of the Rachford-Rice equation.
High-Performance Computing & Parallelization
I specialize in developing massively parallel simulators using MPI and OpenMP within a Fortran framework. My research leverages advanced clusters to solve computationally intensive problems, such as tracking millions of particles and high-resolution simulations, by optimizing algorithms for scalability and speed.
- Parallelization: Integrated METIS and PETSc libraries into TOUGH+RealGasBrine to enable large-scale parallel processes.
- Code development: Developed and parallelized a custom particle transport code (10,000+ lines) for high-resolution simulation.
Particle Transport in Porous Media
To address sand production challenges in hydrate-bearing sediments, I independently developed a parallelized Discrete Element Method (DEM) code. This application functions as both a standalone tool and a module for reservoir simulators, capturing complex particle-fluid interactions.
- Architecture design: Engineered the full code structure, including core modules and physics subroutines.
- Scalability: Implemented MPI parallelization to simulate systems involving millions of distinct particles.
- Physics capture: Modeled critical mechanisms including sand detachment, inter-particle collision, clogging, and migration.
Subsurface Multiphase Flow: Hydrogen & Carbon Storage
I use the TOUGH+RealGasBrine simulator to model multiphase flow for energy transition applications. My work evaluates the feasibility and safety of Underground Hydrogen Storage (UHS), Carbon Capture and Sequestration (CCS), and geological hydrogen in complex geological formations.
- Feasibility analysis: Assessing underground hydrogen storage potential in saline aquifers and depleted gas reservoirs.
- Optimization: Evaluating the impact of cushion gas, relative permeability hysteresis, and formation heterogeneity on H2 recovery.
- Long-term safety: Modeling the 100-year implications of CO2 sequestration.
- Geological hydrogen: Modeling cyclic injection for geologic H2 production.
Geological Nuclear Waste Disposal
Safe disposal of high-level radioactive waste requires rigorous assessment of geological repositories over geological time scales. I employ TOUGH+FLAC3D to model coupled THM responses, ensuring the long-term integrity of disposal sites.
- 3D coupled modeling: Developed 3D THM-coupled models with high fidelity mesh Discretization to predict gas migration pathways in repository sites.
- Performance assessment: Simulating the impact of heat generation and gas release from waste canisters on rock stability over a 10,000-year period.
Additional Technical Competencies
-
Advanced Mesh Generation
Proficient in Gmsh, dfnWorks, and other opensource mesh generators for creating specialized meshes structures, such as discrete fracture networks. -
Natural Gas Hydrate
Extensive experience with TOUGH+Hydrate for modeling phase behavior in hydrate-bearing sediments, with a focus on large-scale CO2 sequestration feasibility. -
Machine Learning for Science
Leveraging my expertise on numerical methods and HPC, I can create sufficient high-fidelity simulations data, which can be used to train machine learning models for surrogate modeling, inversion problems and uncertainty quantification. I am currently exploring this area to enhance simulation efficiency and predictive capabilities.