My research group is currently working on oil and gas reservoir simulation and experimental studies. We have developed machine learning based algorithms which can predict oil and gas well rates quickly and efficiently. These algorithms include predictions being made by purely field data as well as by physics-based machine learning. We are also investigating efficient workflows to test reservoir rock samples through experimental and simulation methods to determine suitability of an Enhanced Oil Recovery (EOR) technique for the corresponding reservoir. This includes conducting reservoir core testing and developing software tools to select most efficient Enhanced Oil Recovery (EOR) methodologies for a given reservoir. We are also doing research in petroleum reservoir production history matching to determine reservoir properties through inverse modelling.
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Application of machine learning in predicting oil rate decline for Bakken shale oil wells Bhattacharyya S., Vyas A. By Scientific Reports 12 - (2022)
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Rapid Compositional Simulation and History Matching of Shale Oil Reservoirs Using the Fast Marching Method Vyas A., Lino A. , Huang J. , Datta-gupta A. , Fujita Y. , Sankaran S. By SPE Unconventional Resources Technology Conference - (2017)
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Rapid Compositional Simulation and History Matching of Shale Oil Reservoirs Using the Fast Marching Method Vyas A., Lino A. , Huang J. , Datta-gupta A. , Fujita Y. , Sankaran S. By SPE Unconventional Resources Technology Conference - (2017)
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A novel methodology for fast reservoir simulation of single-phase gas reservoirs using machine learning Bhattacharyya S., Vyas A. By Heliyon 8 - (2022)
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Data-driven model-based rate decline prediction in unconventional eagle ford shale oil wells Bhattacharyya S., Vyas A. By Petroleum Science and Technology 40 401-422 (2022)
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Machine learning based rate decline prediction in unconventional reservoirs Bhattacharyya S., Vyas A. By Upstream Oil and Gas Technology 8 - (2022)
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Evaluating Precision of Annular Pressure Buildup (APB) Estimation Using Machine-Learning Tools Kulkarni S. D., Vyas A. , Gupta H. , Maiti S. By SPE Drilling and Completion 37 93-103 (2022)
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Investigation on viscosity behaviour of anionic polyacrylamide copolymer in brine solutions for slickwater fluids applications at high salinity and hardness conditions. Balaga D. K., Korlepara N. K., Vyas A. , Kulkarni S. D. By Journal of Energy Resources Technology 144 112104-112116 (2022)
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Modeling Early Time Rate Decline in Unconventional Reservoirs Using Machine Learning Techniques Vyas A., Datta-gupta A. , Mishra S. By Abu Dhabi International Petroleum Exhibition & Conference - (2017)
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Modeling Early Time Rate Decline in Unconventional Reservoirs Using Machine Learning Techniques Vyas A., Datta-gupta A. , Mishra S. By Abu Dhabi International Petroleum Exhibition & Conference - (2017)
- Co-Principal Investigator
Ph. D. Students
Akshay Chandan Dey
Area of Research: Reservoir Engineering
Atman Madhumaya
Area of Research: Reservoir Engineering
Shweta Rai
Area of Research: Reservoir Characterization
