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Proceedings Papers

Application of Machine Learning for Estimating Petrophysical Properties of Carbonate Rocks Using NMR Core Measurements

Ravan Farmanov, Felix Feldmann, Eric Sonny Mathew, Moussa Tembely, Emad W. Al-Shalabi, Waleed AlAmeri, Shehadeh Masalmeh, Ali AlSumaiti
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212625-MS
https://doi.org/10.2118/212625-MS
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View Paper titled, Application of Machine Learning for Estimating Petrophysical Properties of Carbonate Rocks Using NMR Core Measurements
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Proceedings Papers

Deriving New Type Curves through Machine Learning in the Wolfcamp Formation

Gene Michael Mask, Xingru Wu
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212624-MS
https://doi.org/10.2118/212624-MS
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View Paper titled, Deriving New Type Curves through Machine Learning in the Wolfcamp Formation
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Proceedings Papers

Super-Resolution Reconstruction of Reservoir Saturation Map with Physical Constraints Using Generative Adversarial Network

Nandita Doloi, Somnath Ghosh, Jyoti Phirani
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212611-MS
https://doi.org/10.2118/212611-MS
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View Paper titled, Super-Resolution Reconstruction of Reservoir Saturation Map with Physical Constraints Using Generative Adversarial Network
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Proceedings Papers

Novel Approach for Automated Pore Network Characterization and Machine Learning Assisted Capillary Pressure Modeling for an Improved Water Saturation Modelling in Carbonate Reservoirs

Nader Gerges, Gennady Makarychev, Luisa Ana Barillas, Christophe Darous, Alaa Maarouf, Midhun Madhavan, Sushmitha Kuruba, Lulwa Almarzooqi, Chakib Kada Kloucha, Hussein Mustapha
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212612-MS
https://doi.org/10.2118/212612-MS
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View Paper titled, Novel Approach for Automated Pore Network Characterization and Machine Learning Assisted Capillary Pressure Modeling for an Improved Water Saturation Modelling in Carbonate Reservoirs
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Proceedings Papers

An Innovative AI Physics Hybrid Technology to Overcome the Time-Intensive History Matching Challenges, A Case Study: Minagish Oil Field

Ali Qubian, Mohammed Ahmad Zekraoui, Sina Mohajeri, Emad Mortezazadeh, Reza Eslahi, Maryam Bakhtiari, Abrar Al Dabbous, Asma Al Sagheer, Ali Alizadeh, Mostafa Zeinali
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212608-MS
https://doi.org/10.2118/212608-MS
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View Paper titled, An Innovative AI Physics Hybrid Technology to Overcome the Time-Intensive History Matching Challenges, A Case Study: Minagish Oil Field
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Proceedings Papers

Using Isotope Technology to Identify Oil and Gas Reservoir Sweet Spots

Feng Hu Lu
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212642-MS
https://doi.org/10.2118/212642-MS
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View Paper titled, Using Isotope Technology to Identify Oil and Gas Reservoir Sweet Spots
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Proceedings Papers

Machine Learning Assisted Flash Calculation for Sour Gas and Crude Oil

Madiyar Koyanbayev, Lei Wang, Aset Zhumatai
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212673-MS
https://doi.org/10.2118/212673-MS
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View Paper titled, Machine Learning Assisted Flash Calculation for Sour Gas and Crude Oil
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Proceedings Papers

Real Time Artificial Intelligence Assisted Operations Geology: Lithology and Fluids Early Identification and Automatic Well Correlation

Arcangelo Di Palo, Stefano Pianaro, Ada Crottini, Pamela Tempone, Carla Sanasi
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212669-MS
https://doi.org/10.2118/212669-MS
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View Paper titled, Real Time Artificial Intelligence Assisted Operations Geology: Lithology and Fluids Early Identification and Automatic Well Correlation
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Proceedings Papers

Physics Informed Surrogate Model Development in Predicting Dynamic Temporal and Spatial Variations During CO 2 Injection into Deep Saline Aquifers

Zeeshan Tariq, Bicheng Yan, Shuyu Sun
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212693-MS
https://doi.org/10.2118/212693-MS
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View Paper titled, Physics Informed Surrogate Model Development in Predicting Dynamic Temporal and Spatial Variations During CO 2 Injection into Deep Saline Aquifers
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Proceedings Papers

A Novel Semi-Supervised Clustering Method for Carbonate Pore Size Distribution in Middle East Using Earth Mover Distance

Ruicheng Ma, Dandan Hu, Zeqi Zhao, Yong Li, Yixuan Zhao, Fei Gu, Yuning Wang
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212593-MS
https://doi.org/10.2118/212593-MS
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View Paper titled, A Novel Semi-Supervised Clustering Method for Carbonate Pore Size Distribution in Middle East Using Earth Mover Distance
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Proceedings Papers

Identifying New Behind Casing Opportunities Using Machine Learning

Imran M Fadhil, Jamari M Shah, Salmi Sansudin, Asaad Abdollahzadeh, Husni Husiyandi, Nur Aimi Azimah Azizul, Fairuz Hidayah Hasnan, Yuan Jiun Thai
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212627-MS
https://doi.org/10.2118/212627-MS
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View Paper titled, Identifying New Behind Casing Opportunities Using Machine Learning
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Proceedings Papers

Physics Informed Machine Learning for Production Forecast

Roman Manasipov, Denis Nikolaev, Dmitrii Didenko, Ramez Abdalla, Michael Stundner
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212666-MS
https://doi.org/10.2118/212666-MS
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Proceedings Papers

Case Study Artificial Intelligence (AI) Assisted Numerical Reservoir Simulations in a Mature Reservoir Under Waterflood Development in the Sultanate of Oman

Fakhriya Abdullah Shuaibi, Munira Mohamed Hadhrami, Awadh Harbouq Sheheimi, Binayak Agarwal, Qassim Mohamed Riyami, Mohammed Ruqaishi, Naima Habsi, Emad Mortezazadeh, Sina Mohajeri
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212623-MS
https://doi.org/10.2118/212623-MS
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View Paper titled, Case Study Artificial Intelligence (AI) Assisted Numerical Reservoir Simulations in a Mature Reservoir Under Waterflood Development in the Sultanate of Oman
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Proceedings Papers

Application of Machine Learning in a Giant Mature Reservoir to Speed-Up Infill Prospects Screening, Optimize Field Development and Improve the Ultimate Recovery Factor

Clement Fabbri, Nagaraju Reddicharla, Wen Shi, Alaa Al Shalabi, Sara Al Hashmi, Sulaiman Al Jaberi
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212678-MS
https://doi.org/10.2118/212678-MS
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View Paper titled, Application of Machine Learning in a Giant Mature Reservoir to Speed-Up Infill Prospects Screening, Optimize Field Development and Improve the Ultimate Recovery Factor
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Proceedings Papers

Recovery Estimates from Micromodel Experiments: Processing, Uncertainty, and Rate-dependence

Ziyad Kaidar, Abdulkareem AlSofi, Amer Al-Anazi
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196623-MS
https://doi.org/10.2118/196623-MS
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View Paper titled, Recovery Estimates from Micromodel Experiments: Processing, Uncertainty, and Rate-dependence
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Proceedings Papers

Deep Recurrent Neural Network DRNN Model for Real-Time Step-Down Analysis

Srinath Madasu, Keshava Prasad Rangarajan
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196621-MS
https://doi.org/10.2118/196621-MS
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View Paper titled, Deep Recurrent Neural Network DRNN Model for Real-Time Step-Down Analysis
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Proceedings Papers

Locate the Remaining Oil ltro and Predictive Analytics Application for Development Decisions on the Z Field

Cristian Masini, Khalid Said Al Shuaili, Dmitry Kuzmichev, Yulia Mironenko, Saeed Majidaie, Rina Buoy, Laurent Didier Alessio, Denis Malakhov, Sergey Ryzhov, Willem Postuma
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196631-MS
https://doi.org/10.2118/196631-MS
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View Paper titled, Locate the Remaining Oil ltro and Predictive Analytics Application for Development Decisions on the Z Field
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Proceedings Papers

Production Optimisation Under Uncertainty with Automated Scenario Reduction: A Real-Field Case Application

E.. Barros, R. M. Fonseca, R. J. de Moraes
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196637-MS
https://doi.org/10.2118/196637-MS
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View Paper titled, Production Optimisation Under Uncertainty with Automated Scenario Reduction: A Real-Field Case Application
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Proceedings Papers

Machine Learning for 3D Image Recognition to Determine Porosity and Lithology of Heterogeneous Carbonate Rock

Omar Al-Farisi, Hongtao Zhang, Aikifa Raza, Djamel Ozzane, Mohamed Sassi, TieJun Zhang
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196657-MS
https://doi.org/10.2118/196657-MS
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View Paper titled, Machine Learning for 3D Image Recognition to Determine Porosity and Lithology of Heterogeneous Carbonate Rock
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Proceedings Papers

Leveraging Data Analytics with Numerical Modeling for Optimizing Oil Field Development and Management

Mohamad Yousef Alklih, Tengku Mohd Tengku Ab Hamid, Tariq Ali Alshabibi, Shahab Mohagheg
Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, September 17–19, 2019
Paper Number: SPE-196646-MS
https://doi.org/10.2118/196646-MS
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View Paper titled, Leveraging Data Analytics with Numerical Modeling for Optimizing Oil Field Development and Management
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