Sanjay Srinivasan | Penn State Department of Energy and Mineral Engineering

About:

Sanjay Srinivasan is a professor of petroleum and natural gas engineering at Penn State University and holds the John and Willie Leone Family chair in Energy and Mineral Engineering. He currently serves as the director of the Energy Institute within the college of earth and mineral sciences.

Srinivasan received his B.Tech degree in Petroleum Engineering from the Indian School of Mines, a M.S. degree in Petroleum Engineering from the University of Southern California and a Ph.D. degree in Petroleum Engineering from Stanford University. Prior to coming to Penn State, he was a professor in the department of petroleum and geosystems engineering at the University of Texas at Austin. He has also served on the faculty of the Chemical and Petroleum Engineering department at the University of Calgary.

Srinivasan’s primary research focus is in the area of petroleum reservoir characterization and improved management of reservoir recovery processes. Some of the algorithms and methods that he has pioneered have been applied for early appraisal of ultra-deepwater plays in the Gulf of Mexico and for characterizing natural fracture networks in conventional as well as unconventional reservoirs. He has also partnered with geophysicists and geo-modelers to develop novel schemes for integrating seismic data in reservoir models.

He served on the Technical Advisory board for the Alberta Ingenuity Center for In Situ Energy at the University of Calgary. He was until recently, a task leader in the Center for Frontiers of Subsurface Energy Security at UT Austin where he directed research focused on field scale characterization of geological CO2 sequestration.

He is the Penn State site director for CO2-SMART – an NSF funded Industry University Collaborative Research Center (IUCRC). He serves as the associate editor of the Journal of Mathematical Geosciences and is a member of the editorial committee for the Society of Petroleum Engineering Journal.

Srinivasan's research group, Penn State Initiative for Geostatistics and GeoModeling Applications can be found here.

Recent Activities

Organizer, Energy Innovations research showcase, The Energy Institute, Penn State University, April 2025.
Panelist, Petroleum Engineering Department Heads Association (PEDHA) – Society of Petroleum Engineers (SPE) symposium on the Future of Petroleum Engineering Education, Houston, August 2024.
Organizer, Annual Conference of the International Association of Mathematical Geosciences, Penn State University, September 2019.
Organizer, Frontiers in Subsurface Energy Security, Center for Petroleum and Geosystems Engineering Symposium, University of Texas at Austin, March 2015.
Organizer, CPGE Research Showcase, Center for Petroleum and Geosystems Engineering Symposium, University of Texas at Austin, November 2014.
Member, Organizing Committee – 10th International Geostatistics Congress, 2016, Valencia, Spain.
Member, International Scientific Committee – 16th IAMG Annual Meeting, New Delhi, India, October 2014.
Member, Consultative Committee – 9th International Geostatistics Congress, Oslo, 2012, Norway.
Member, Organizing Committee – SPE Forum: Novel Techniques for Reservoir Modeling, Santa Fe, New Mexico, November, 2012.
Vice-Chair, Organizing Committee – 12th IAMG Annual Meeting, 2009, Stanford University.
Member, Distinguished Lecturer Selection Committee, International Association of Mathematical Geology (IAMG), Sept. 2009 – Current.
Associate Editor, Mathematical Geosciences.
Member of the Editorial Review Board of Society of Petroleum Engineering Reservoir Evaluations Journal (SPERE).

Publications

Geostatistics for Reservoir Modeling

Baran, Y.C. and Srinivasan, S., 2025, “Application of Reinforcement Learning in Geostatistical Modeling Workflows,” Math Geosciences. https://doi.org/10.1007/s11004-025-10180-x.
Ren, Z. and Srinivasan, S., 2024, “Using Physics Informed Generative Adversarial Networks to Model 3D porous media,” arXiv preprint arXiv:2409.11541.
Chandna, A. and Srinivasan, S., 2023, “Probabilistic Integration of Geomechanical and Geostatistical Inferences for Mapping Natural Fracture Networks,” Mathematical Geosciences, 1-27.
Chandna, A. and Srinivasan, S., 2023, “Probabilistic Integration of Geomechanical and Geostatistical Inferences for Mapping Natural Fracture Networks”, In Springer Proceedings in Earth and Environmental Sciences (pp. 63-79). Springer Nature. https://doi.org/10.1007/978-3-031-19845-8_11.
Dawuda, I., & Srinivasan, S. (2023). Geometric and Geostatistical Modeling of Point Bars. In Springer Proceedings in Earth and Environmental Sciences (pp. 63-79). Springer Nature. https://doi.org/10.1007/978-3-031-19845-8_6.
Dawar, K., Srinivasan, S. and Webster, M., 2023. Application of Reinforcement Learning for Well Location Optimization, In Springer Proceedings in Earth and Environmental Sciences (pp. 81-110). Springer Nature. https://doi.org/10.1007/978-3-031-19845-8_7.
Chandna,A. and Srinivasan, S., 2022, “Mapping natural fracture networks using geomechanical inferences from machine learning approaches,” Computational Geosciences, 26 (3), 651-676.
Dawuda, I. and Srinivasan, S., 2022, “A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations,” Computers & Geosciences, 164, 105-127.
Joon, S., Dawuda, I., Morgan, E. and Srinivasan,S., 2022, “Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage,” SPE Journal, 27 (04), 2510-2524.
Al-Mudhafar, W.J, Rao, D.N., Srinivasan, S., Vo Thanh, H. and Al Lawe, E.M., 2022 “Rapid evaluation and optimization of carbon dioxide-enhanced oil recovery using reduced-physics proxy models,” Energy Science & Engineering, 10 (10), 4112-4135.
Singh, M. and Srinivasan, S., 2020, “Development of Proxy Model for Hydraulic Fracturing and Seismic Wave Propagation Processes, Mathematical Geosciences, Volume 52, pages 81–110, 2020.
Kumar, D. and Srinivasan, S. 2020, “Indicator-based data assimilation with multiple-point statistics for updating an ensemble of models with non-Gaussian parameter distributions,” Advances in Water Resources Research, Volume 141, July 2020, https://doi.org/10.1016/j.advwatres.2020.103611.
Chandna, A. and Srinivasan, S., 2019, “Modeling natural fracture networks using improved geostatistical inferences,” Energy Procedia, DOI: https://doi.org/10.1016/j.egypro.2019.01.508, Volume 158, Pages 6073-6078, February.
Udegbe, E., Morgan, E., Srinivasan, S., 2019, “Big data analytics for seismic fracture identification using amplitude-based statistics,” Computational Geosciences, Volume 23, pages1277–1291.
Kumar, D. and Srinivasan, S. 2019, “Ensemble-Based Assimilation of Nonlinearly Related Dynamic Data in Reservoir Models Exhibiting Non-Gaussian Characteristics,” Mathematical Geosciences, Volume 51, Issue 1, pp 75–107, January 2019.
Udegbe, E., Morgan, E., Srinivasan, S., 2019, “Big-Data Analytics for Production-Data Classification Using Feature Detection: Application to Restimulation - Candidate Selection,” SPE Reservoir Evaluation & Engineering, Preprint, DOI: https://doi.org/10.2118/187328-PA, January 2019.
Li, Liangping, Srinivasan, S., Zhou, H., and Hernandez, Jaime, “Two-point or multiple-point statistics? A comparison between the ensemble Kalman filtering and the ensemble pattern matching inverse methods,” Advances in Water Resources, Volume 86, Part B, December 2015, Pages 297–310.
Li, Liangping, Srinivasan, S. and Hernandez, Jaime, (2015) “A Local-Global Pattern Matching Method for Subsurface Stochastic Inverse Modeling,” Environmental Modeling & Software, Volume 70, Pages 55-64, August 2015.
Li, Liangping, Srinivasan, S., Zhou, H. and Gomez-Hernandez, J., “Simultaneous estimation of both geologic and reservoir state variables within an ensemble-based multiple-point statistic framework,” Mathematical Geosciences, Vol. 46, pages 597-623, July 2014.
Srinivasan, S. and Barrera, A.E., “Multi-scale reservoir characterization and history matching within a probabilistic framework,” in CLOSING THE GAP Advances in Applied Geomodeling for Hydrocarbon Reservoirs Edited by David Garner, Damien Thenin and Clayton V. Deutsch, September 2013.
Huang, Yu-Chun and Srinivasan, S., “GrowthSim - Efficient Conditional Simulation of Spatial Patterns Using a Pattern-Growth Algorithm,” – Proceedings of the Ninth International Geostatistics Congress: Springer-Verlag Quantitative Geology and Geostatistics Series Vol. 17, Abrahamsen, Petter; Hauge, Ragnar; Kolbjørnsen, Odd (Eds.), pp 209-220, ISBN: 978-94-007-4152-2, 2012.
Srinivasan, S. and Anupam, A., “Multiscale Modeling of Fracture Network in a Carbonate Reservoir,” – Proceedings of the Ninth International Geostatistics Congress: Springer-Verlag Quantitative Geology and Geostatistics Series Vol. 17, Abrahamsen, Petter; Hauge, Ragnar; Kolbjørnsen, Odd (Eds.), pp 185-196, ISBN: 978-94-007-4152-2, 2012.
Erzeybek, S., Srinivasan, S. and Janson, X., “Multiple-point statistics in a non-gridded domain: Application to karst/fracture network modeling,” – Proceedings of the Ninth International Geostatistics Congress: Springer-Verlag Quantitative Geology and Geostatistics Series Vol. 17, Abrahamsen, Petter; Hauge, Ragnar; Kolbjørnsen, Odd (Eds.), pp 221-238, ISBN: 978-94-007-4152-2, 2012.
Eskandari, K. and Srinivasan, S., “Reservoir Modeling of Complex Geological Systems- A Multiple Point Perspective,” Journal of Canadian Petroleum Technology, Volume 49, No. 8, August 2010, pp. 59-68.
Sil, S. and Srinivasan, S., “Stochastic simulation of fracture strikes using seismic anisotropy induced velocity anomalies,” Exploration Geophysics, Volume 40, Number 3, November 2009.

Reservoir Engineering and Recovery Processes

Ren, Z., Srinivasan, S. and Crandall, D., 2024, “Constrained Transformer-Based Porous Media Generation to Spatial Distribution of Rock Properties”, arXiv preprint arXiv:2410.21462.
Dawuda, I. and Srinivasan, S., 2022, “Geologic Modeling and Ensemble-Based History Matching for Evaluating CO2 Sequestration Potential in Point bar Reservoirs,” Frontiers in Energy Research, 10:867083. doi: 10.3389/fenrg.2022.867083.
Al-Mudhafar, W.J, Rao, D.N., Srinivasan, S., Vo Thanh, H. and Al Lawe, E.M., 2022, “Rapid evaluation and optimization of carbon dioxide-enhanced oil recovery using reduced-physics proxy models,” Energy Science & Engineering, 10 (10), 4112-4135.
Jeong, H. and Srinivasan, S., “Fast Assessment of Flow Characteristics of CO2 plumes Plume Characteristics in Heterogeneous Reservoirs Using a Connectivity Based Proxy,” International Journal for Greenhouse Gas Control, Volume 59, April 2017, Pages 40–57.
Azom, Nnamdi and Srinivasan, S., “Coupled multiphase flow and heat transfer at the steam chamber interface during the Steam Assisted Gravity Drainage Process,” Society of Petroleum Engineering Journal, October 2013.
Leung, J.Y. and Srinivasan, S., “Scale-Up of Mass Transfer and Recovery Performance in Heterogeneous Reservoirs, “Journal of Petroleum Science and Engineering, Volumes 86–87, Pages 71–86, May 2012.
Leung, J.Y. and Srinivasan, S., “Analysis of Uncertainty Introduced by Scaleup of Reservoir Attributes and Flow Response in Heterogeneous Reservoirs,” SPE Journal, Volume 16, No.3, September 2011.
Bhowmick, S., Mantilla, C.M. and Srinivasan, S., “Tracking CO2 Plume Migration during Geologic Sequestration using a Probabilistic History Matching Approach,” Stochastic Environmental Resource Risk Assessment (SERRA), Vol. 25, pp. 1085-1090, April 2011.
Mantilla, C.M., Srinivasan, S. and Nguyen, Q., “Updating Geologic Models using Ensemble Kalman Filter for Water Coning Control,” Engineering (Open Access), Vol.3 No.5, May 2011.
Wu, X., Pope, G.A., Shook, G.M. and Srinivasan, S. “Prediction of enthalpy from fractured geothermal reservoirs using partitioning tracers,” International Journal of Heat and Mass Transfer, Volume 51, March, 2008, pp. 1453-1466.
Kashib, T. and Srinivasan, S. “Iterative Updating of Reservoir Models Constrained to Dynamic Data,” Journal of Canadian Petroleum Technology, Volume 46, No. 11, November 2007.
Kashib, T. and Srinivasan, S.: “A Probabilistic Approach to Integrating Dynamic Data in Reservoir Models,” Journal of Petroleum Science and Engineering, Volume 50, Issues 3-4, pp. 241-257, March 2006.
Lake, L.W. and Srinivasan, S., “Statistical Scale-Up of Reservoir Properties: Concepts and Applications,” Journal of Petroleum Science and Engineering, Vol. 44, Issues 1-1, pp. 27-39, October 2004.
Srinivasan, S. and Mantilla, C., “Uncertainty quantification and feedback control using a model selection approach – application to a polymer flooding process,” – Proceedings of the Ninth International Geostatistics Congress: Springer-Verlag Quantitative Geology and Geostatistics Series Vol. 17, Abrahamsen, Petter; Hauge, Ragnar; Kolbjørnsen, Odd (Eds.), pp. 197-208, ISBN: 978-94-007-4152-2, 2012.
Ramachandran, H., Pope, G.A. and Srinivasan, S., "Effect of Thermodynamic Phase Changes on CO2 leakage," Energy Procedia, Volume 63, 2014, Pages 3735-3745, November, 2014.

Awards

Distinguished Member, Society of Petroleum Engineers, 2022.
Selected for Big Ten Academic Alliance Department Executive Officer Workshop Series, 2021.
John and Willie Leone Family Chair in Petroleum and Natural Gas Engineering, Energy and Mineral Engineering Department, Penn State University.
SPE Faculty Pipeline Award, September 2012.
Cox Visiting Faculty Fellowship – Stanford University, 2010.
SPE Southwest Region Reservoir Description and Dynamics Award, April, 2009.
Frank Jessen fellowship awarded by the College of Engineering, University of Texas at Austin, September 2007 – current.
SPE Award for outstanding technical editor, Society of Petroleum Engineering Reservoir Evaluation journal, 2006.
UT Austin Department of Petroleum and Geosystems Engineering Teaching Excellence award for 2005-2006.
Henry Ramey fellowship for outstanding academic achievement and contributions to the school of Earth Sciences at Stanford University, 1999.
Frank Miller fellowship for Best Graduate Student in the Petroleum Engineering Department at Stanford University, 1999.
Centennial Teaching Assistant award (Stanford University), 1999.