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publications
Coupled Flow and Geomechanics in Reservoirs with Complex Fractures Using Embedded Meshes
Published in SPE Annual Technical Conference and Exhibition, 2022
Conference paper on coupled flow and geomechanics in fractured reservoirs using embedded meshes.
Chen, Jungang, Wu, Kan, & Killough, John. (2022). Coupled Flow and Geomechanics in Reservoirs with Complex Fractures Using Embedded Meshes. SPE Annual Technical Conference and Exhibition.
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Generating subsurface earth models using discrete representation learning and deep autoregressive network
Published in Computational Geosciences, 2023
Journal paper on generating subsurface earth models with discrete representation learning and deep autoregressive networks.
Recommended citation: Chen, Jungang, Misra, Siddharth, Huang, Chung-Kan, & Delgado, Jose F. (2023). Generating subsurface earth models using discrete representation learning and deep autoregressive network. Computational Geosciences, 27, 955–974. Springer Nature.
-->Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
Published in Mathematics, 2023
Journal paper on transfer learning-based physics-informed CNNs for porous media flow with dynamic controls.
Recommended citation: Chen, Jungang, Gildin, Eduardo, & Killough, John E. (2023). Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls. Mathematics, 12(20), 3281.
-->Massive geomodel compression and rapid geomodel generation using advanced autoencoders and autoregressive neural networks
Published in SPE Europec featured at EAGE Conference and Exhibition, 2023
Conference paper on geomodel compression and generation using autoencoders and autoregressive neural networks.
Recommended citation: Misra, Siddharth, Chen, Jungang, Falola, Yusuf, Churilova, Polina, Huang, Chung-Kan, & Delgado, Jose. (2023). Massive geomodel compression and rapid geomodel generation using advanced autoencoders and autoregressive neural networks. SPE Europec at EAGE Conference and Exhibition.
-->Physics-informed convolutional recurrent surrogate model for reservoir simulation with well controls
Published in arXiv preprint, 2023
Preprint introducing a physics-informed convolutional recurrent surrogate model for reservoir simulation with well controls.
Chen, Jungang, Gildin, Eduardo, & Killough, John E. (2023). Physics-informed convolutional recurrent surrogate model for reservoir simulation with well controls. arXiv preprint arXiv:2305.09056.
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Advancing Proxy Modeling in Reservoir Simulation: A Multi-Step Embed to Control Approach
Published in SPE Annual Technical Conference and Exhibition, 2024
Conference paper on advancing proxy modeling in reservoir simulation with a multi-step embed to control approach.
Recommended citation: Chen, Jungang, Gildin, Eduardo, & Killough, John. (2024). Advancing Proxy Modeling in Reservoir Simulation: A Multi-Step Embed to Control Approach. SPE Annual Technical Conference and Exhibition.
-->Optimization of pressure management strategies for geological CO2 storage using surrogate model-based reinforcement learning
Published in International Journal of Greenhouse Gas Control, 2024
Journal paper on optimizing CO₂ storage pressure management strategies with surrogate model-based reinforcement learning.
Recommended citation: Chen, Jungang, Gildin, Eduardo, & Kompantsev, Georgy. (2024). Optimization of pressure management strategies for geological CO₂ storage using surrogate model-based reinforcement learning. International Journal of Greenhouse Gas Control, 138, 104262. Elsevier.
-->Assessing risk in long-term CO2 storage under uncertainty via survival analysis-based surrogates
Published in SPE Annual Technical Conference and Exhibition, 2024
Conference paper on assessing CO₂ storage risk using survival analysis-based surrogates.
Recommended citation: Gurwicz, A., Chen, J., Gutman, D. H., & Gildin, E. (2024). Assessing risk in long-term CO₂ storage under uncertainty via survival analysis-based surrogates. SPE Annual Technical Conference and Exhibition.
-->Generative Artificial Intelligence for Geomodeling
Published in International Petroleum Technology Conference, 2024
Conference paper on generative AI for geomodeling.
Recommended citation: Misra, Siddharth, Chen, Jungang, Churilova, Polina, & Falola, Yusuf. (2024). Generative Artificial Intelligence for Geomodeling. International Petroleum Technology Conference.
-->Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation
Published in arXiv preprint, 2024
Preprint on a deep learning-based approach for surrogate modelling in reservoir simulation.
Chen, Jungang, Gildin, Eduardo, & Killough, John. (2024). Multi-Step Embed to Control: A Novel Deep Learning-based Approach for Surrogate Modelling in Reservoir Simulation. arXiv preprint arXiv:2409.09920.
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Assessing Risk in Long-Term CO2 Storage Under Uncertainty via Survival Analysis-Based Surrogates
Published in SPE Journal, 2025
Journal article on long-term CO₂ storage risk assessment using survival analysis-based surrogates.
Recommended citation: Gurwicz, Allan, Chen, Jungang, Gutman, David H., & Gildin, Eduardo. (2025). Assessing Risk in Long-Term CO₂ Storage Under Uncertainty via Survival Analysis-Based Surrogates. SPE Journal, 30(05), 2837–2854. Society of Petroleum Engineers.
-->Optimal CO2 storage management considering safety constraints in multi-stakeholder multi-site CCS projects: a game theoretic perspective
Published in arXiv preprint, 2025
Preprint introducing a game-theoretic perspective on optimal CO₂ storage management with safety constraints across multiple stakeholders.
Chen, Jungang, & Hosseini, Seyyed A. (2025). Optimal CO₂ storage management considering safety constraints in multi-stakeholder multi-site CCS projects: a game theoretic perspective. arXiv preprint arXiv:2508.11618.
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talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
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teaching
PETE 419-Petroleum Data Analytics & Machine Learning
Course, Texas A&M University, Petroleum Engineering Department, 2022
- Collaborated with professor in delivering lectures, preparing and conducting examinations, and managing various academic projects
- Guided and supported over 30 students during office hours, providing personalized tutoring and assistance with coursework, enhancing their understanding and performance in the subject matter.
GeoFORCE Texas - Jackson School of Geosciences
High-schooler outreach program, University of Texas at Austin, Bureau of Economic Geology, 2025
- GeoFORCE is a free youth education outreach program for high school students across Texas.
- Delivered STEM outreach instruction to 10+ high school students using the EASiTool web app.
- Simplified complex technical concepts for diverse learners with no prior background.