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Proceedings Papers

Use of Clustering Techniques for Automated Lumping of Components in Compositional Models

Michel A. Cancelliere, J. Andino Saint Antonin
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212211-MS
https://doi.org/10.2118/212211-MS
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View Paper titled, Use of Clustering Techniques for Automated Lumping of Components in Compositional Models
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Proceedings Papers

A Fast History Matching and Optimization Tool and its Application to a Full Field with More than 1,000 Wells

Guotong Ren, Zhenzhen Wang, Yuanbo Lin, Tsubasa Onishi, Xiaoyue Guan, Xian-Huan Wen
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212188-MS
https://doi.org/10.2118/212188-MS
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View Paper titled, A Fast History Matching and Optimization Tool and its Application to a Full Field with More than 1,000 Wells
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Proceedings Papers

A Novel Machine-Learning Assisted Phase-Equilibrium Calculation Model for Liquid-Rich Shale Reservoirs

Fangxuan Chen, Sheng Luo, Shihao Wang, Hadi Nasrabadi
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212193-MS
https://doi.org/10.2118/212193-MS
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View Paper titled, A Novel Machine-Learning Assisted Phase-Equilibrium Calculation Model for Liquid-Rich Shale Reservoirs
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Proceedings Papers

Nonlinearly Constrained Life-Cycle Production Optimization Using Sequential Quadratic Programming (SQP) With Stochastic Simplex Approximated Gradients (StoSAG)

Quang Nguyen, Mustafa Onur, Faruk Omer Alpak
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212178-MS
https://doi.org/10.2118/212178-MS
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View Paper titled, Nonlinearly Constrained Life-Cycle Production Optimization Using Sequential Quadratic Programming (SQP) With Stochastic Simplex Approximated Gradients (StoSAG)
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Proceedings Papers

Feature Extraction in Time-Lapse Seismic Using Deep Learning for Data Assimilation

Rodrigo Exterkoetter, Gustavo Rachid Dutra, Leandro Passos de Figueiredo, Fernando Bordignon, Alexandre Anozé Emerick, Gilson Moura Silva Neto
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212196-MS
https://doi.org/10.2118/212196-MS
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View Paper titled, Feature Extraction in Time-Lapse Seismic Using Deep Learning for Data Assimilation
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Proceedings Papers

Reservoir Connectivity Identification and Robust Production Forecasting Using Physics Informed Machine Learning

Masahiro Nagao, Akhil Datta-Gupta, Tsubasa Onishi, Sathish Sankaran
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212201-MS
https://doi.org/10.2118/212201-MS
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View Paper titled, Reservoir Connectivity Identification and Robust Production Forecasting Using Physics Informed Machine Learning
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Proceedings Papers

Integrated Framework for Optimization of Horizontal/Deviated Well Placement and Control for Geological CO 2 Storage

Amy Zou, Louis J. Durlofsky
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212228-MS
https://doi.org/10.2118/212228-MS
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View Paper titled, Integrated Framework for Optimization of Horizontal/Deviated Well Placement and Control for Geological CO 2 Storage
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Proceedings Papers

A Quasi-Newton Method for Well Location Optimization Under Uncertainty

Esmail Eltahan, Faruk Omer Alpak, Kamy Sepehrnoori
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212212-MS
https://doi.org/10.2118/212212-MS
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View Paper titled, A Quasi-Newton Method for Well Location Optimization Under Uncertainty
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Proceedings Papers

Deep Learning-Based Disentangled Parametrization for Model Calibration Under Multiple Geologic Scenarios

Junjie Yu, Behnam Jafarpour
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212177-MS
https://doi.org/10.2118/212177-MS
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View Paper titled, Deep Learning-Based Disentangled Parametrization for Model Calibration Under Multiple Geologic Scenarios
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Proceedings Papers

Physics Inspired Machine Learning for Solving Fluid Flow in Porous Media: A Novel Computational Algorithm for Reservoir Simulation

Chico Sambo, Yin Feng
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203917-MS
https://doi.org/10.2118/203917-MS
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View Paper titled, Physics Inspired Machine Learning for Solving Fluid Flow in Porous Media: A Novel Computational Algorithm for Reservoir Simulation
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Proceedings Papers

Physics Informed Deep Learning for Flow and Transport in Porous Media

Cedric G. Fraces, Hamdi Tchelepi
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203934-MS
https://doi.org/10.2118/203934-MS
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View Paper titled, Physics Informed Deep Learning for Flow and Transport in Porous Media
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Proceedings Papers

Optimization of Water-Alternating-CO 2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

You Junyu, Ampomah William, Sun Qian
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203913-MS
https://doi.org/10.2118/203913-MS
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View Paper titled, Optimization of Water-Alternating-CO 2 Injection Field Operations Using a Machine-Learning-Assisted Workflow
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Proceedings Papers

Caveats and Pitfalls of Production Forecast Uncertainty Analysis Using Design of Experiments

Boxiao Li, Hemant Phale, Yanfen Zhang, Timothy Tokar, Xian-Huan Wen
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203919-MS
https://doi.org/10.2118/203919-MS
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View Paper titled, Caveats and Pitfalls of Production Forecast Uncertainty Analysis Using Design of Experiments
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Proceedings Papers

An Efficient Bi-Objective Optimization Workflow Using the Distributed Quasi-Newton Method and Its Application to Field Development Optimization

Yixuan Wang, Faruk Alpak, Guohua Gao, Chaohui Chen, Jeroen Vink, Terence Wells, Fredrik Saaf
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203971-MS
https://doi.org/10.2118/203971-MS
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View Paper titled, An Efficient Bi-Objective Optimization Workflow Using the Distributed Quasi-Newton Method and Its Application to Field Development Optimization
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Proceedings Papers

Efficient Drill Sequence Optimization Using a Heuristic Priority Function

Zhenzhen Wang, Jincong He, Shusei Tanaka, Xian-Huan Wen
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203986-MS
https://doi.org/10.2118/203986-MS
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View Paper titled, Efficient Drill Sequence Optimization Using a Heuristic Priority Function
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Proceedings Papers

Intelligent Time-Stepping for Practical Numerical Simulation

Soham Sheth, Francois McKee, Kieran Neylon, Ghazala Fazil
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-204002-MS
https://doi.org/10.2118/204002-MS
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View Paper titled, Intelligent Time-Stepping for Practical Numerical Simulation
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Proceedings Papers

Deep Learning for Latent Space Data Assimilation LSDA in Subsurface Flow Systems

Syamil Mohd Razak, Atefeh Jahandideh, Ulugbek Djuraev, Behnam Jafarpour
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203997-MS
https://doi.org/10.2118/203997-MS
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View Paper titled, Deep Learning for Latent Space Data Assimilation LSDA in Subsurface Flow Systems
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Proceedings Papers

Artificial Neural Network Modeling of Compaction-Dilation Data for Unconventional Oil Reservoirs

Eugene Fedutenko, Long Nghiem, Chaodong Yang, Tong Chen, Mojtaba Seifi
Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193811-MS
https://doi.org/10.2118/193811-MS
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View Paper titled, Artificial Neural Network Modeling of Compaction-Dilation Data for Unconventional Oil Reservoirs
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Proceedings Papers

Robust Fuzzy Timestep Selector for a Fully Implicit Reservoir Simulator

Paul Crumpton
Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193809-MS
https://doi.org/10.2118/193809-MS
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View Paper titled, Robust Fuzzy Timestep Selector for a Fully Implicit Reservoir Simulator
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Proceedings Papers

Accelerated Compositional Simulation of Tight Oil and Shale Gas Reservoirs Using Proxy Flash Calculation

Shihao Wang, Nicolas Sobecki, Didier Ding, Yu-Shu Wu, Lingchen Zhu
Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193878-MS
https://doi.org/10.2118/193878-MS
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View Paper titled, Accelerated Compositional Simulation of Tight Oil and Shale Gas Reservoirs Using Proxy Flash Calculation
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