Geological Carbon Sequestration

Peer-Reviewed Journals:

• Alqahtani A, He X, Yan B, Hoteit H. Uncertainty Analysis of CO₂ Storage in Deep Saline Aquifers Using Machine Learning and Bayesian Optimization. Energies. 2023; 16(4):1684. https://doi.org/10.3390/en16041684 
• Tariq, Z., Gudala, M., Yan, B., Sun, S., Mahmoud, M. 2023. Spatial–temporal prediction of minerals dissolution and precipitation using deep learning techniques: An implication to Geological Carbon Sequestration, Fuel. 341: 127677. 
• Z Tariq, B Yan, S Sun, M Gudala, MS Aljawad, M Murtaza, M Mahmoud. 2022. Machine Learning-Based Accelerated Approaches to Infer Breakdown Pressure of Several Unconventional Rock Types. ACS omega 7 (45), 41314-41330
• Z Tariq, M Gudala, B Yan, S Sun, M Mahmoud, A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques, Geoenergy Science and Engineering, 211333.
• Yan, B., Harp, D., Chen, B., Pawar, R.J. 2022. Improving deep learning performance for predicting large-scale geological CO2 sequestration modeling through feature coarsening. Scientific Reports, 20667.
• Yan, B., Harp, D., Chen, B., Hoteit, H., Pawar, R.J. 2022. A gradient-based deep neural network model for simulating multiphase flow in porous media. Journal of Computational Physics.
• Yan, B., Chen, B., Harp, D.R., Pawar, R.J. 2022. A robust deep learning workflow to predict multiphase flow behavior during geological CO2 sequestration injection and Post-Injection periods. Journal of Hydrology, Vol. 607: 127542.
• Yan, B., Harp, D.R., Chen, B., Pawar R.J. 2021. A physics-constrained deep learning model for simulating multiphase flow in 3D heterogeneous porous media. Fuel, 2021: 122693.

Conference Papers:

• Z Tariq, B Yan, S Sun, 2023, Application of Image Processing Techniques in Deep-Learning Workflow to Predict CO2 Storage in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network …. Paper presented at the Middle East Oil, Gas and Geosciences Show, Manama, Bahrain. https://doi.org/10.2118/213359-MS
• Z Tariq, M Ali, B Yan, S Sun, M Khan, N Yekeen, H Hoteit, 2023, Data-Driven Machine Learning Modeling of Mineral/CO2/Brine Wettability Prediction: Implications for CO2 Geo-Storage. Paper presented at the Middle East Oil, Gas and Geosciences Show, Manama, Bahrain, February 2023. https://doi.org/10.2118/213346-MS
• Z Tariq, B Yan, S Sun, 2023, An Intelligent Safe Well Bottom-Hole Pressure Monitoring of CO2 Injection Well into Deep Saline: A coupled Hydro-Mechanical Approach. Paper presented at the Middle East Oil, Gas and Geosciences Show, Manama, Bahrain, February 2023. https://doi.org/10.2118/213315-MS
• Z Tariq, Z Xu, M Gudala, B Yan, S Sun, 2023, Deep-Learning-Based Surrogate Model to Predict CO2 Saturation Front in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach, SPE Reservoir Characterization and Simulation Conference and Exhibition
• Z Tariq, B Yan, S Sun, 2023,Physics Informed Surrogate Model Development in Predicting Dynamic Temporal and Spatial Variations During CO2 Injection into Deep Saline Aquifers, SPE Reservoir Characterization and Simulation Conference and Exhibition.
• Z Tariq, EU Yildirim, B Yan, S Sun, 2023, Deep Learning Models for the Prediction of Mineral Dissolution and Precipitation During Geological Carbon Sequestration, SPE Reservoir Characterization and Simulation Conference and Exhibition.
• Z Tariq, B Yan, S Sun, M Gudala, M Mahmoud, 2022, A Machine Learning Based Accelerated Approach to Infer the Breakdown Pressure of the Tight Rocks, ADIPEC.
• Z Tariq, M Gudala, Z Xu, B Yan, S Sun, M Mahmoud, 2022, An Effective Method of Estimating Nuclear Magnetic Resonance Based Porosity Using Deep Learning Approach, ADIPEC.
• Chen, B., Yan, B., Kang, Q., Pawar, R. 2022. Deep Learning Accelerated History Matching and Forecasting for Geologic CO2 Sequestration. 14^th International Society for Porous Media Annual Meeting (InterPore2022).
• Zhang, J., Yan, B., Wang, Y.. 2022. Image-based physics-constraint workflow for multi-phase flow simulation in heterogeneous media. 14^th International Society for Porous Media Annual Meeting (InterPore2022).
• Yan, B., Chen, B., Harp, D.R., Pawar, R.J. 2021.  Development and Evaluation of Deep Learning to Predict Multiphase Flow Behavior during Geological CO2 Sequestration Injection and Post-Injection Periods. AGU Fall Meeting 2021, Dec 13 to 17, 2021, New Orleans, Louisiana, U.S.