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Proceedings Papers

Data-Driven Optimization for Oilfield Operations

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Ruchita Robert Rozario
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224336-MS
https://doi.org/10.2118/224336-MS
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View Paper titled, Data-Driven Optimization for Oilfield Operations
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Proceedings Papers

Predicting Oilwell Cement Properties Downhole Using Existing Databases, Modified Neural Networks and Other Machine Learning Approaches

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J. J. Abraham, C. Devers, C. Teodoriu, M. Amani
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224345-MS
https://doi.org/10.2118/224345-MS
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View Paper titled, Predicting Oilwell Cement Properties Downhole Using Existing Databases, Modified Neural Networks and Other Machine Learning Approaches
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Proceedings Papers

Pioneering Digital Transformation of Product and Service Delivery Workflow: Global Application with Local Customized Solution for Energy Industry

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Saurabh Jha, Raghid Nasr
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224347-MS
https://doi.org/10.2118/224347-MS
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View Paper titled, Pioneering Digital Transformation of Product and Service Delivery Workflow: Global Application with Local Customized Solution for Energy Industry
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Proceedings Papers

Development of Well Placement Workflow for Infill Drilling

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P. Zhang, T. Gao, R. Li, J. Fu
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224357-MS
https://doi.org/10.2118/224357-MS
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View Paper titled, Development of Well Placement Workflow for Infill Drilling
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Proceedings Papers

Optimizing Corrosion Inhibitor Package to Mitigate Metal Corrosion and Formation Damage: A Machine-Learning Advisory Model

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Denis Bannikov, Maxim Voronin, Abdul Muqtadir Khan, Murtaza Ziauddin
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224361-MS
https://doi.org/10.2118/224361-MS
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View Paper titled, Optimizing Corrosion Inhibitor Package to Mitigate Metal Corrosion and Formation Damage: A Machine-Learning Advisory Model
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Proceedings Papers

Developing a Machine Learning Application for Integrated Production Forecasting in Complex Reservoirs with Frequently Changing Operating Conditions

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K. Gaurav
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224362-MS
https://doi.org/10.2118/224362-MS
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View Paper titled, Developing a Machine Learning Application for Integrated Production Forecasting in Complex Reservoirs with Frequently Changing Operating Conditions
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Proceedings Papers

Optimizing Depth Selection for Formation Pressure Testing in Complex Reservoirs – A Machine Learning Approach

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M. K. Aljishi, M. Abdullah, D. Devegowda, C. S. Rai
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224365-MS
https://doi.org/10.2118/224365-MS
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View Paper titled, Optimizing Depth Selection for Formation Pressure Testing in Complex Reservoirs – A Machine Learning Approach
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Proceedings Papers

Automated Cutter Damage Classification for PDC Bits in Delaware Vertical Applications

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C. Devers, D. Lyles, W. Dyer
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224387-MS
https://doi.org/10.2118/224387-MS
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View Paper titled, Automated Cutter Damage Classification for PDC Bits in Delaware Vertical Applications
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Proceedings Papers

Friction Reducer Advisor: A Real-Time Machine Learning Approach

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Esteban Ugarte, Abdul Muqtadir Khan, Sidney Flores, Brandon Hobbs, Samir Menasria, Tim Drews
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224388-MS
https://doi.org/10.2118/224388-MS
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View Paper titled, Friction Reducer Advisor: A Real-Time Machine Learning Approach
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Proceedings Papers

Data-Driven Solutions and Artificial Intelligence in the Energy Sector: Leveraging Open GHGRP Data for Emissions Forecasting for U.S. Petroleum and Natural Gas Assets

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Jnana Bairy, Ovais Rehman Shah, June Zhang
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 14–18, 2025
Paper Number: SPE-224384-MS
https://doi.org/10.2118/224384-MS
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View Paper titled, Data-Driven Solutions and Artificial Intelligence in the Energy Sector: Leveraging Open GHGRP Data for Emissions Forecasting for U.S. Petroleum and Natural Gas Assets
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Proceedings Papers

Application of Machine Learning to Evaluate the Performances of Various Downhole Centrifugal Separator Types in Oil and Gas Production Systems

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Laura Camila Osorio Ojeda, Michael Olubode, Hamidreza Karami, Tony Podio
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 17–19, 2023
Paper Number: SPE-213059-MS
https://doi.org/10.2118/213059-MS
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View Paper titled, Application of Machine Learning to Evaluate the Performances of Various Downhole Centrifugal Separator Types in Oil and Gas Production Systems
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Proceedings Papers

Application of Machine Learning Optimization Workflow to Improve Oil Recovery

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Abdul-Muaizz Koray, Dung Bui, William Ampomah, Emmanuel Appiah Kubi, Joshua Klumpenhower
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 17–19, 2023
Paper Number: SPE-213095-MS
https://doi.org/10.2118/213095-MS
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View Paper titled, Application of Machine Learning Optimization Workflow to Improve Oil Recovery
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Proceedings Papers

Petrophysical Rock Typing in Uinta Basin Using Models Powered by Machine Learning Algorithms

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Carlos L. Arengas, Mark E. Curtis, Son T. Dang, Chandra S. Rai
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 17–19, 2023
Paper Number: SPE-213061-MS
https://doi.org/10.2118/213061-MS
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View Paper titled, Petrophysical Rock Typing in Uinta Basin Using Models Powered by Machine Learning Algorithms
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Proceedings Papers

Generating New Production Type Curves through Machine Learning Utilizing Dimensional Analysis

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Gene Michael Mask, Xingru Wu
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 17–19, 2023
Paper Number: SPE-213080-MS
https://doi.org/10.2118/213080-MS
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View Paper titled, Generating New Production Type Curves through Machine Learning Utilizing Dimensional Analysis
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Proceedings Papers

Projection of Logging While Drilling Data at the Bit by Implementing Supervised Machine Learning Algorithm

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Ashutosh Sharma, Tunc Burak, Runar Nygaard, Svein Hellvik, Espen Hoel, Morten Welmer
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 17–19, 2023
Paper Number: SPE-213070-MS
https://doi.org/10.2118/213070-MS
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View Paper titled, Projection of Logging While Drilling Data at the Bit by Implementing Supervised Machine Learning Algorithm
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Proceedings Papers

Automated Core Fracture Characterization by Computer Vision and Image Analytics of CT Images

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Ryan Antle
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 9–10, 2019
Paper Number: SPE-195181-MS
https://doi.org/10.2118/195181-MS
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View Paper titled, Automated Core Fracture Characterization by Computer Vision and Image Analytics of CT Images
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Proceedings Papers

Data-Driven Analysis of Natural Gas EOR in Unconventional Shale Oils

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Cenk Temizel, Karthik Balaji, Celal Hakan Canbaz, Yildiray Palabiyik, Raul Moreno, Minou Rabiei, Zifu Zhou, Rahul Ranjith
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 9–10, 2019
Paper Number: SPE-195194-MS
https://doi.org/10.2118/195194-MS
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View Paper titled, Data-Driven Analysis of Natural Gas EOR in Unconventional Shale Oils
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Proceedings Papers

Hypervolume-Based Multiobjective Optimization for Gas Lift Systems

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Lichi Deng, Feyisayo Olalotiti-Lawal, Ehsan Davani, David Castiñeira
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 9–10, 2019
Paper Number: SPE-195208-MS
https://doi.org/10.2118/195208-MS
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View Paper titled, Hypervolume-Based Multiobjective Optimization for Gas Lift Systems
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Proceedings Papers

Accelerated Completion Optimization with Uncertainty Reduction Through Coupled Data and Physics Based Hybrid Models

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Guoxiang Liu, Hayley Stephenson, Alireza Shahkarami, Glen Murrell, Robert Klenner, Naresh Iyer, Brian Barr, Nurali Virani
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, April 9–10, 2019
Paper Number: SPE-195238-MS
https://doi.org/10.2118/195238-MS
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View Paper titled, Accelerated Completion Optimization with Uncertainty Reduction Through Coupled Data and Physics Based Hybrid Models
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Proceedings Papers

Using Type Wells to Economically Schedule DUC Well Completions

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T. Dash, D. W. Scott, C. K. Kwok
Paper presented at the SPE Oklahoma City Oil and Gas Symposium, March 27–31, 2017
Paper Number: SPE-185109-MS
https://doi.org/10.2118/185109-MS
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View Paper titled, Using Type Wells to Economically Schedule DUC Well Completions
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