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Journal Articles

Dynamic Physics-Guided Deep Learning for Long-Term Production Forecasting in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 29 (10): 5151–5169.
Paper Number: SPE-221474-PA
https://doi.org/10.2118/221474-PA
Published: 09 October 2024
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View article titled, Dynamic Physics-Guided Deep Learning for Long-Term Production Forecasting in Unconventional Reservoirs
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Includes: Supplementary Content
Proceedings Papers

Production Enhancement by Microproppants: Concept Proof Using Laboratory Experiment and Numerical Modeling

Yanhui Han, Feng Liang, Hui-Hai Liu
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0055
https://doi.org/10.56952/ARMA-2024-0055
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View Paper titled, Production Enhancement by Microproppants: Concept Proof Using Laboratory Experiment and Numerical Modeling
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Proceedings Papers

Research on Mechanical Properties of Natural Fracture and Fracture Prediction Model Based on Sliding Window

Yesong Li, Hui Li, Yi Li, Hai Liu, Yunyi Zhang, Libo Zhou, Guoying Zhao, Yongcheng Peng, Fujian Zhou, Ben Li
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043943-MS
https://doi.org/10.15530/urtec-2024-4043943
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View Paper titled, Research on Mechanical Properties of Natural Fracture and Fracture Prediction Model Based on Sliding Window
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Proceedings Papers

An Analytical Solution to Pressure Build-Up for CO 2 Injection into a Saline Aquifer: The Impact of Stress-Dependency of Permeability

Hui-Hai Liu, Yanhui Han, Khalid M. AlRuwaili, Murtadha J. AlTammar
Paper presented at the International Petroleum Technology Conference, February 12, 2024
Paper Number: IPTC-23869-EA
https://doi.org/10.2523/IPTC-23869-EA
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View Paper titled, An Analytical Solution to Pressure Build-Up for CO 2 Injection into a Saline Aquifer: The Impact of Stress-Dependency of Permeability
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Journal Articles

Transfer Learning with Prior Data-Driven Models from Multiple Unconventional Fields

Jodel Cornelio, Syamil Mohd Razak, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 28 (05): 2385–2414.
Paper Number: SPE-214312-PA
https://doi.org/10.2118/214312-PA
Published: 11 October 2023
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View article titled, Transfer Learning with Prior Data-Driven Models from Multiple Unconventional Fields
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Journal Articles

Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 28 (05): 2425–2447.
Paper Number: SPE-214663-PA
https://doi.org/10.2118/214663-PA
Published: 11 October 2023
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View article titled, Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs
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Proceedings Papers

Optimization of Slurry Operation Parameters Through the Application of Dynamic Proppant Conductivity Apparatus

Hai Liu, Xiwu Yang, Jian Zhang, Yuanxiang Xiao, Hongxing Xu, Yesong Li, Libo Zhou, Yanxin Tan, Hui Li, Ben Li
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0231
https://doi.org/10.56952/ARMA-2023-0231
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View Paper titled, Optimization of Slurry Operation Parameters Through the Application of Dynamic Proppant Conductivity Apparatus
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Proceedings Papers

Dynamic Physics-Guided Deep Learning for Production Forecasting in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Paper presented at the SPE Western Regional Meeting, May 22–25, 2023
Paper Number: SPE-212962-MS
https://doi.org/10.2118/212962-MS
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View Paper titled, Dynamic Physics-Guided Deep Learning for Production Forecasting in Unconventional Reservoirs
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Proceedings Papers

Neural Network-Assisted Clustering for Improved Production Predictions in Unconventional Reservoirs

Jodel Cornelio, Syamil Mohd Razak, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Paper presented at the SPE Western Regional Meeting, May 22–25, 2023
Paper Number: SPE-212953-MS
https://doi.org/10.2118/212953-MS
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View Paper titled, Neural Network-Assisted Clustering for Improved Production Predictions in Unconventional Reservoirs
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Proceedings Papers

An Innovative Machine Learning Method for Predicting Well Performance in Unconventional Reservoirs with a Relatively Small Data Set

Hui-Hai Liu, Jilin Zhang, Cenk Temizel, Moemen Abdelrahman
Paper presented at the Middle East Oil, Gas and Geosciences Show, February 19–21, 2023
Paper Number: SPE-213288-MS
https://doi.org/10.2118/213288-MS
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View Paper titled, An Innovative Machine Learning Method for Predicting Well Performance in Unconventional Reservoirs with a Relatively Small Data Set
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Proceedings Papers

A Dynamic Residual Learning Approach to Improve Physics-Constrained Neural Network Predictions in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Paper presented at the Middle East Oil, Gas and Geosciences Show, February 19–21, 2023
Paper Number: SPE-213289-MS
https://doi.org/10.2118/213289-MS
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View Paper titled, A Dynamic Residual Learning Approach to Improve Physics-Constrained Neural Network Predictions in Unconventional Reservoirs
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Proceedings Papers

Identifying and Ranking Multiple Source Models for Transfer Learning in Unconventional Reservoirs.

Jodel Cornelio, Syamil Mohd Razak, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Paper presented at the Middle East Oil, Gas and Geosciences Show, February 19–21, 2023
Paper Number: SPE-213349-MS
https://doi.org/10.2118/213349-MS
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View Paper titled, Identifying and Ranking Multiple Source Models for Transfer Learning in Unconventional Reservoirs.
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Journal Articles

Residual Learning to Integrate Neural Network and Physics-Based Models for Improved Production Prediction in Unconventional Reservoirs

Jodel Cornelio, Syamil Mohd Razak, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 27 (06): 3328–3350.
Paper Number: SPE-210559-PA
https://doi.org/10.2118/210559-PA
Published: 20 December 2022
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View article titled, Residual Learning to Integrate Neural Network and Physics-Based Models for Improved Production Prediction in Unconventional Reservoirs
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Journal Articles

An Efficient Laboratory Method to Measure Stress-Dependent Tight Rock Permeability With the Steady-State Flow Method

Jilin Jay Zhang, Hui-Hai Liu, Jewel Duncan
Journal: Petrophysics - The SPWLA Journal of Formation Evaluation and Reservoir Description
Publisher: Society of Petrophysicists and Well-Log Analysts
Petrophysics 63 (05): 604–613.
Paper Number: SPWLA-2022-v63n5a3
https://doi.org/10.30632/PJV63N5-2022a3
Published: 01 October 2022
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View article titled, An Efficient Laboratory Method to Measure Stress-Dependent Tight Rock Permeability With the Steady-State Flow Method
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Journal Articles

Transfer Learning with Recurrent Neural Networks for Long-Term Production Forecasting in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 27 (04): 2425–2442.
Paper Number: SPE-209594-PA
https://doi.org/10.2118/209594-PA
Published: 11 August 2022
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View article titled, Transfer Learning with Recurrent Neural Networks for Long-Term Production Forecasting in Unconventional Reservoirs
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Proceedings Papers

Embedding Physical Flow Functions into Deep Learning Predictive Models for Improved Production Forecasting

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 20–22, 2022
Paper Number: URTEC-3702606-MS
https://doi.org/10.15530/urtec-2022-3702606
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View Paper titled, Embedding Physical Flow Functions into Deep Learning Predictive Models for Improved Production Forecasting
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Proceedings Papers

Aramco Nano Permeameter ANP: A New Laboratory Technology for Accurate and Efficient Measurements of Stress-Dependent Source Rock Permeability

Hui-Hai Liu, Jilin Zhang, Mohammed Boudjatit
Paper presented at the International Petroleum Technology Conference, February 21–23, 2022
Paper Number: IPTC-22185-EA
https://doi.org/10.2523/IPTC-22185-EA
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View Paper titled, Aramco Nano Permeameter ANP: A New Laboratory Technology for Accurate and Efficient Measurements of Stress-Dependent Source Rock Permeability
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Proceedings Papers

Integrating Deep Learning and Physics-Based Models for Improved Production Prediction in Unconventional Reservoirs

Syamil Mohd Razak, Jodel Cornelio, Atefeh Jahandideh, Behnam Jafarpour, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya
Paper presented at the SPE Middle East Oil & Gas Show and Conference, November 28–December 1, 2021
Paper Number: SPE-204864-MS
https://doi.org/10.2118/204864-MS
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View Paper titled, Integrating Deep Learning and Physics-Based Models for Improved Production Prediction in Unconventional Reservoirs
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Proceedings Papers

Investigating Transfer Learning for Characterization and Performance Prediction in Unconventional Reservoirs

Jodel Cornelio, Syamil Mohd Razak, Atefeh Jahandideh, Behnam Jafarpour, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya
Paper presented at the SPE Middle East Oil & Gas Show and Conference, November 28–December 1, 2021
Paper Number: SPE-204563-MS
https://doi.org/10.2118/204563-MS
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View Paper titled, Investigating Transfer Learning for Characterization and Performance Prediction in Unconventional Reservoirs
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Journal Articles

Incorporation of Physics into Machine Learning for Production Prediction from Unconventional Reservoirs: A Brief Review of the Gray-Box Approach

Hui-Hai Liu, Jilin Zhang, Feng Liang, Cenk Temizel, Mustafa A. Basri, Rabah Mesdour
Journal: SPE Reservoir Evaluation & Engineering
Publisher: Society of Petroleum Engineers (SPE)
SPE Res Eval & Eng 24 (04): 847–858.
Paper Number: SPE-205520-PA
https://doi.org/10.2118/205520-PA
Published: 10 November 2021
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View article titled, Incorporation of Physics into Machine Learning for Production Prediction from Unconventional Reservoirs: A Brief Review of the Gray-Box Approach
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