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Modeling Fluid Flow and Transport in Porous Media by Physics-driven Simulation Approaches

Project

Project Details

Program
Energy Resources and Petroleum Engineering
Field of Study
Subsurface Modeling
Division
Physical Sciences and Engineering
Faculty Lab Link
https://www.kaust.edu.sa/en/study/faculty/bicheng-yan
Center Affiliation
Ali I. Al-Naimi Petroleum Engineering Research Center

Project Description

The Digital Subsurface Flow & Transport Lab (DSFT-Lab) is a cross-discipline team led by Prof. Bicheng Yan KAUST. Currently DSFT focuses on physics-driven and data-driven (deep learning mainly) model development that can simulate multiphase flow in porous media at reservoir scale and pore scale. The goal is to explore the fundamental physics that governs the complex and coupled physics related flow and transport in porous media, and investigate its impact on subsurface fluid flow such as hydrocarbon recovery, geologic carbon sequestration, hydrogen storage and geothermal recovery etc. DSFT seeks for self-motivated, dedicated and creative STEM-majored students who wants to address challenging energy and environmental related engineering problems.

About the Researcher

Bicheng Yan
Assistant Professor, Energy Resources and Petroleum Engineering
Physical Science and Engineering Division

Affiliations

Education Profile

  • Postdoctoral Research Associate, Los Alamos National Lab, 2020-2021
  • Ph.D. Petroleum Engineering, Texas A&M University, 2017
  • M.S. Petroleum Engineering, Texas A&M University, 2013
  • B.S. Petroleum Engineering, China University of Petroleum (Beijing), 2009

Research Interests

Professor Yan's current research interests are physics-driven modeling and data-driven modeling for complex subsurface processes related to energy and environmental domains. He has worked in areas including reservoir simulation, multi-porosity modeling for flow and transport in heterogeneous porous media (mainly shale), integrating physics with data analytics in unconventional field and carbon storage management, history matching and stochastic optimization.

Selected Publications

  • Yan, B., Mi, L., Chai, Z., Wang, Y. et al. 2018. An Enhanced Discrete Fracture Network Model for Multiphase Flow in Fractured Reservoirs. Journal of Petroleum Science and Engineering, Vol 161: 667-682.
  • Yan, B., Mi, L., Wang, Y., Tang, H. etl al. 2018. Multi-Porosity Multi-Physics Compositional Simulation for Gas Storage and Transport in Highly Heterogeneous Shales. Journal of Petroleum Science and Engineering, Vol 160: 498-509.
  • Yan, B., Wang, Y., Killough, J. 2017. A Fully Compositional Model Considering the Effect of Nanopores in Tight Oil Reservoirs. Journal of Petroleum Science and Engineering, Vol 152: 675-682.
  • Yan, B., Alfi, M., An, C., Cao, Y., Wang, Y., Killough, J.E. 2016. General Multi-Porosity Simulation for Fractured Reservoir Modeling. Journal of Natural Gas Science and Engineering, Vol 33: 777-791.
  • Yan, B., Wang, Y., and Killough, J.E. 2015. Beyond Dual-Porosity Modeling for the Simulation of Complex Flow Mechanisms in Shale Reservoirs. Computational Geosciences, Vol 20 (1): 69-91.

Desired Project Deliverables

* Subsurface modeling workflow/software for reservoir or pore scale modeling; * 1 to 2 publications based on the scientific findings.

Recommended Student Background

Petroleum Engineering
Applied Mathematics
Civil Engineering
Data Analytics
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3-6 months
Internship period
100+
Research Projects
3.5/4
Cumulative GPA
310
Interns a Year