Sanjay Srinivasan

IEE Faculty Member
Titles and Affiliations
Department Head and Professor, John and Willie Leone Department of Energy & Mineral Engineering (EME)
John and Willie Leone Family Chair, John and Willie Leone Department of Energy & Mineral Engineering (EME)

Sanjay Srinivasan is a professor of petroleum and natural gas engineering, and he holds the John and Willie Leone Family chair in Energy and Mineral Engineering. His 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.

In the News

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Recent Publications

Bayesian averaging sensitivity analysis of reservoir heterogeneity and anisotropy of carbon dioxide assisted gravity drainage of a large clastic oil reservoir

Al-Mudhafar, W. J., Rao, D. N., Srinivasan, S. & Wood, D. A., Apr 1 2023, In: Fuel. 337, 127200.

Research output: Contribution to journalArticlepeer-review

Probabilistic Integration of Geomechanical and Geostatistical Inferences for Mapping Natural Fracture Networks

Chandna, A. & Srinivasan, S., Jul 2023, In: Mathematical Geosciences. 55, 5, p. 645-671 27 p.

Research output: Contribution to journalArticlepeer-review

Rapid evaluation and optimization of carbon dioxide-enhanced oil recovery using reduced-physics proxy models

Al-Mudhafar, W. J., Rao, D. N., Srinivasan, S., Vo Thanh, H. & Al Lawe, E. M., Oct 2022, In: Energy Science and Engineering. 10, 10, p. 4112-4135 24 p.

Research output: Contribution to journalArticlepeer-review

Mapping natural fracture networks using geomechanical inferences from machine learning approaches

Chandna, A. & Srinivasan, S., Jun 2022, In: Computational Geosciences. 26, 3, p. 651-676 26 p.

Research output: Contribution to journalArticlepeer-review

A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations

Dawuda, I. & Srinivasan, S., Jul 2022, In: Computers and Geosciences. 164, 105127.

Research output: Contribution to journalArticlepeer-review

Geologic Modeling and Ensemble-Based History Matching for Evaluating CO2 Sequestration Potential in Point bar Reservoirs

Dawuda, I. & Srinivasan, S., May 10 2022, In: Frontiers in Energy Research. 10, 867083.

Research output: Contribution to journalArticlepeer-review

Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during Geological Carbon Storage

Joon, S., Dawuda, I., Morgan, E. C. & Srinivasan, S., Aug 2022, In: SPE Journal. 27, 4, p. 2510-2524 15 p.

Research output: Contribution to journalArticlepeer-review

Indicator-based data assimilation with multiple-point statistics for updating an ensemble of models with non-Gaussian parameter distributions

Kumar, D. & Srinivasan, S., Jul 2020, In: Advances in Water Resources. 141, 103611.

Research output: Contribution to journalArticlepeer-review

Development of Proxy Model for Hydraulic Fracturing and Seismic Wave Propagation Processes

Singh, M. & Srinivasan, S., Jan 1 2020, In: Mathematical Geosciences. 52, 1, p. 81-110 30 p.

Research output: Contribution to journalArticlepeer-review

Geological and production uncertainty assessments of the cyclic CO 2 -assisted gravity drainage EOR process: a case study from South Rumaila oil field

Al-Mudhafar, W. J., Rao, D. N. & Srinivasan, S., Jun 1 2019, In: Journal of Petroleum Exploration and Production Technology. 9, 2, p. 1457-1474 18 p.

Research output: Contribution to journalArticlepeer-review

Modeling natural fracture networks using improved geostatistical inferences

Chandna, A. & Srinivasan, S., 2019, In: Energy Procedia. 158, p. 6073-6078 6 p.

Research output: Contribution to journalConference articlepeer-review

Ensemble-Based Assimilation of Nonlinearly Related Dynamic Data in Reservoir Models Exhibiting Non-Gaussian Characteristics

Kumar, D. & Srinivasan, S., Jan 10 2019, In: Mathematical Geosciences. 51, 1, p. 75-107 33 p.

Research output: Contribution to journalArticlepeer-review

Big-data analytics for production-data classification using feature detection: Application to restimulation-candidate selection

Udegbe, E., Morgan, E. & Srinivasan, S., 2019, In: SPE Reservoir Evaluation and Engineering. 22, 2, p. 364-385 22 p.

Research output: Contribution to journalArticlepeer-review

Big data analytics for seismic fracture identification using amplitude-based statistics

Udegbe, E., Morgan, E. & Srinivasan, S., Dec 1 2019, In: Computational Geosciences. 23, 6, p. 1277-1291 15 p.

Research output: Contribution to journalArticlepeer-review

Reservoir sensitivity analysis for heterogeneity and anisotropy effects quantification through the cyclic CO2-Assisted Gravity Drainage EOR process – A case study from South Rumaila oil field

Al-Mudhafar, W. J., Rao, D. N. & Srinivasan, S., Jun 1 2018, In: Fuel. 221, p. 455-468 14 p.

Research output: Contribution to journalArticlepeer-review