Publications

You can also find my publications on my Google Scholar profile.

Journal Papers

Guo, Q., He, Y., Liu, M., Zhao, Y., Liu, Y., & Luo, J. (2024), Reduced Geostatistical Approach With a Fourier Neural Operator Surrogate Model for Inverse Modeling of Hydraulic Tomography, Water Resources Research, 60(6), e2023WR034939, doi: https://doi.org/10.1029/2023WR034939.
[paper] [code]

Guo, Q., Liu, M., & Luo, J. (2023), Predictive Deep Learning for High-Dimensional Inverse Modeling of Hydraulic Tomography in Gaussian and Non-Gaussian Fields, Water Resources Research, 59(10), e2023WR035408, doi: https://doi.org/10.1029/2023WR035408.
[paper] [code]

Guo, Q., Zhao, Y., Lu, C., & Luo, J. (2023). High-dimensional inverse modeling of hydraulic tomography by physics informed neural network (HT-PINN). Journal of Hydrology, 616, 128828, doi: https://doi.org/10.1016/j.jhydrol.2022.128828.
[paper] [code]

Liu, Y., He, Y., Guo, Q., Kim, M., Rathore, S., & Luo, J. (2024), Impact of Boundary Conditions on Modeling Seawater Intrusion in Stratified Coastal Aquifers Under Sea Level Rise, doi: http://dx.doi.org/10.2139/ssrn.4912526.

Zhao, Y., Guo, Q., Lu, C., & Luo, J. (2022). High‐dimensional groundwater flow inverse modeling by upscaled effective model on principal components. Water Resources Research, 58(7), e2022WR032610. doi: https://doi.org/10.1029/2022WR032610. [paper] [code]

He, Y., Guo, Q., Liu, Y., Huang, H., Hou, D., & Luo, J. (2024). Multiphysics Modeling Investigation of Wellbore Storage Effect and Non-Darcy Flow. Water Resources Research, 60(1), e2023WR035453. doi: https://doi.org/10.1029/2023WR035453. [paper] [data]

Conference Proceedings

Chen, B., Ma, Z., Ahmmed, B., Guo, Q., Li, W., Mehana, M., Meng, M., & Pawar, R. (2024), Unified SimCCS Platform for Decision-Making in Carbon Capture, Transport, and Storage Infrastructure, paper presented at Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17), 20-24 October 2024, doi: http://dx.doi.org/10.2139/ssrn.5030859.

Ma, Z., Guo, Q., Viswanathan, H., Pawar, R., & Chen, B. (2024), Deep Learning Assisted History Matching and Forecasting: Applied to the Illinois Basin – Decatur Project (IBDP), paper presented at Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17), 20-24 October 2024, doi: http://dx.doi.org/10.2139/ssrn.5019810.

Conference and Workshop Presentations

[Poster] An Innovative Method to Evaluate Cost of CO2 Shipping** In: CCUS 2025, Houston, TX, March 2025

[Poster] Unified SimCCS Platform for Decision-Making in Carbon Capture, Transport, and Storage** In: CESAM 2024, Socorro, NM, November 2024

[Presentation] Large-scale Inverse Modeling of Hydraulic Tomography by Physics Informed Neural Network**
In: AGU Fall Meeting, Chicago, IL, December 2022
[abstract]

Invited Talks & Seminars

Physics informed neural network in groundwater inverse modeling In: Georgia Tech Water Resource Engineering Seminar, Atlanta, GA, March 2022.

Scalable high-dimensional inverse modeling of hydraulic tomography by physics informed neural network (HT-PINN)
In: National Environmental Conference for Doctoral Students, Beijing, China, January 2023