Reservoir Simulation Resources

Research and findings from our reservoir simulation software team and colleagues.

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Oil & Gas


ECHELON: SPE10 Case Study →


A Revolution in Performance using a GPU Based Simulator →

Jamal Siavoshi, Husky Energy; Karthik Mukundakrishnan, Stone Ridge Technology


Full-GPU Reservoir Simulation Delivers on its Promise for Giant Carbonate Fields →

A. Vidyasagar, L. Patacchini, P. Panfili, F. Caresani, A. Cominelli, R. Gandham and K. Mukundakrishnan EAGE Conference Proceedings, Third EAGE WIPIC Workshop: Reservoir Management in Carbonates, Nov 2019, Volume 2019, p.1 - 5


GPU Acceleration of Equation of State Calculations in Compositional Reservoir Simulation →

R. Gandham* (Stone Ridge Technology), K. Esler (Stone Ridge Technology), K. Mukundakrishnan (Stone Ridge Technology), Y.P. Zhang (Stone Ridge Technology), C. Fang (The University of Tulsa) & V. Natoli (Stone Ridge Technology)


Unconventional Reservoir Model Predictions Using Massively-Parallel Flow-Simulation →

M. Shahvali, J. R. Gilman, O. Angola, M. Uland, and H. Meng, iReservoir.com Inc.; K. Esler, K. Mukundakrishnan, M. Ghasemi, and V. Natoli, Stone Ridge Technology


A High Performance Reservoir Simulator on GPU →

Reza Ghasemi, Rice HPC in Oil and Gas Meeting, March 2016


Unconventional Reservoir Model Predictions Using Massively-Parallel Flow-Simulation: Bakken/Three Forks Reservoir Development Cases and SRV Testing →

M. Shahvali, J.R. Gilman, O. Angola, M. Uland, H. Meng, iReservoir.com Inc. and K. Esler, K. Mukundakrishnan, M. Ghasemi, V. Natoli, Stone Ridge Technology, SPE Low-Perm Symposium May 2016


Recent Trends in High Performance Computing: Implications for Reservoir Simulation →


Unconventional Reservoir Model Predictions Using Massively-Parallel GPU Flow-Simulation →

J. R. Gilman, M. Uland*, O. Angola, R. Michelena, H. Meng, iReservoir.com Inc. and K. Esler, K. Mukundakrishnan, V. Natoli, Stone Ridge Technology


Accelerating Tight Reservoir Simulation Workflows With GPUs →

K. Mukundakrishnan, K. Esler, D. Dembeck, V. Natoli, J. Shumway, Y. Zhang, Stone Ridge Technology, and J. R. Gilman, H. Meng, iReservoir.com, Inc.


Realizing the Potential of GPUs for Reservoir Simulation →

K. Esler, K. Mukundakrishnan, V. Natoli, J. Shumway, Y. Zhang and J. Gilman, ECMOR XIV – 14th European Conference on the Mathematics of Oil Recovery, 8 September 2014


A GPU Accelerated Aggregation Algebraic Multigrid Method →

R. Gandham, K. Esler and Y. Zhang, Computers and Mathematics with Applications 68(2014) 1151-1160


GAMPACK (GPU Accelerated Algebraic Multigrid Package) →

K. Esler, V. Natoli and A. Samardzic, ECMOR XIII – 13th European Conference on the Mathematics of Oil Recovery, 10 September 2012


A Novel GPGPU Approach to Kirchhoff Time Migration →

W. Brouwer, V. Natoli and M. Lamont, 2011 SEG Annual Meeting, September 18 – 23, 2011 , San Antonio, Texas


Survey of Two-Point Seismic Travel Time Methods →

V. Natoli and K. Esler, SRT White paper August 2011


Accelerating Reservoir Simulation with GPUs →

K. Esler, S. Atan, B. Ramirez and V. Natoli, 73rd EAGE Conference and Exhibition, 23 May 2011


General Technology


Recent Trends in High Performance Computing: Implications for Reservoir Simulation →


Webinars


ECHELON 2.0 Software Overview And Case Studies Webinar →