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2021 SPE Reservoir Simulation Conference Special Issue

Guest Editors: Knut-Andreas Lie, SINTEF Digital, and Rami Younis, University of Tulsa


Since 1968, Society of Petroleum Engineers (SPE) has organized 25 conferences and symposia on numerical reservoir simulation. These meetings have brought numerous generations of innovators, scholars, and professionals together to tackle some of the most pressing technical challenges in the use of computation, to advance prudent and efficient business needs. It has also served to inspire future innovation while cultivating a strong sense of culture, community, and stewardship. The conference series has presented more than 1,300 technical papers and has had an immense impact on reservoir simulation technology.

This special issue presents selected and peer-reviewed versions of technical papers presented at the 2021 SPE Reservoir Simulation Conference, which is the 26th meeting in the conference series. The papers represent a cross section of contemporary research and cover a wide range of topics, from research on basic discretization schemes, solution strategies, and optimization methods, to uncertainty quantification, fractured unconventionals, machine-learning methods, and implementations on last generation multicore architectures.

The special issue will also contain an overview paper prepared for the opening ceremony of the conference, which will celebrate the 25 previous conferences by reflecting on the past 60 years of reservoir simulation to empower future generations of leaders and technical experts. This paper will be coauthored by an international cross-institutional team of authors, including influential pioneers who have been there through significant portions of the journey.

Note: This special issue is being compiled in real time. New papers will appear below in the order that they are accepted for publication.

Dimensionless Solutions for the Time-Dependent and Rate-Dependent Productivity Index of Wells in Deformable Reservoirs
W. Zhang and A. Mehrabian
SPE J. (in press; posted online 7 May 2021)

A Recurrent Neural Network–Based Proxy Model for Well-Control Optimization with Nonlinear Output Constraints
Y. D. Kim and L. J. Durlofsky
SPE J. (in press; posted online 25 May 2021)

Deep Reinforcement Learning for Generalizable Field Development Optimization
J. He, M. Tang, C. Hu, S. Tanaka, K. Wang, X.-H. Wen, and Y. Nasir
SPE J. (in press; posted online 12 July 2021)

Biobjective Optimization of Well Placement: Algorithm, Validation, and Field Testing
F. Alpak, V. Jain, Y. Wang, and G. Gao
SPE J. (in press; posted online 13 July 2021)

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