1-20 of 117
Information Management and Systems
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Reliable and Efficient Algorithms to Optimize Gas Well Intermittent Production Through Automatically Intelligent Control

Qingxia Wu, Guoqing Han, Dingding Yang, Zhiyong Zhu, Long Peng, He Ma, Xingyuan Liang
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219130-MS
https://doi.org/10.2118/219130-MS
Add To Cart
View Paper titled, Reliable and Efficient Algorithms to Optimize Gas Well Intermittent Production Through Automatically Intelligent Control
Open the PDF for Reliable and Efficient Algorithms to Optimize Gas Well Intermittent Production Through Automatically Intelligent Control in another window
Add to Citation Manager
Proceedings Papers

Narrowing the Competency Rift: Analyzing Skill Levels with Digital Doubles

A. A. Ahmed Alaa
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219074-MS
https://doi.org/10.2118/219074-MS
Add To Cart
View Paper titled, Narrowing the Competency Rift: Analyzing Skill Levels with Digital Doubles
Open the PDF for Narrowing the Competency Rift: Analyzing Skill Levels with Digital Doubles in another window
Add to Citation Manager
Proceedings Papers

Three-Pressure Prediction Method for Formation Based on Xgboost-gnn Hybrid Model

Lu Zou, Ming Tang, Shiming He, Hanchang Wang, Xinyu Guo
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219095-MS
https://doi.org/10.2118/219095-MS
Add To Cart
View Paper titled, Three-Pressure Prediction Method for Formation Based on Xgboost-gnn Hybrid Model
Open the PDF for Three-Pressure Prediction Method for Formation Based on Xgboost-gnn Hybrid Model in another window
Add to Citation Manager
Proceedings Papers

Inspection of Subsea Conductors Using an Innovative Drop-Down Camera

M. H. Medany, L. Ibrahim
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219085-MS
https://doi.org/10.2118/219085-MS
Add To Cart
View Paper titled, Inspection of Subsea Conductors Using an Innovative Drop-Down Camera
Open the PDF for Inspection of Subsea Conductors Using an Innovative Drop-Down Camera in another window
Add to Citation Manager
Proceedings Papers

Novel Approach to Stimulation Design Optimization for Ultra-Deep, 200°C Temperature Formations: A Case Study in Kunteyi Block

Tengfei Hou, Hai Lin, Xi Wu, Xiaolu Wang, Zhanchun Li, Shiling Zhang, Shengli Feng, Yang Zhang, Yong Liu, Litao Shang, Haoli Bai
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219135-MS
https://doi.org/10.2118/219135-MS
Add To Cart
View Paper titled, Novel Approach to Stimulation Design Optimization for Ultra-Deep, 200°C Temperature Formations: A Case Study in Kunteyi Block
Open the PDF for Novel Approach to Stimulation Design Optimization for Ultra-Deep, 200°C Temperature Formations: A Case Study in Kunteyi Block in another window
Add to Citation Manager
Proceedings Papers

In Situ Generation of Clean Hydrogen in Gas Reservoirs: Experimental and Numerical Study

A. G. Askarova, P. A. Afanasev, E. Y. Popov, A. N. Cheremisin, S. E. Malaniy, D. A. Volkov, A. N. Cheremisin
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219092-MS
https://doi.org/10.2118/219092-MS
Add To Cart
View Paper titled, In Situ Generation of Clean Hydrogen in Gas Reservoirs: Experimental and Numerical Study
Open the PDF for In Situ Generation of Clean Hydrogen in Gas Reservoirs: Experimental and Numerical Study in another window
Add to Citation Manager
Proceedings Papers

Scaling Field and Experimental Data Using Machine Learning Approaches to Evaluate Oilwell Cement Degradation, Stability and Integrity for CCUS Applications

J. J. Abraham, C. Devers, C. Teodoriu, M. Amani
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219115-MS
https://doi.org/10.2118/219115-MS
Add To Cart
View Paper titled, Scaling Field and Experimental Data Using Machine Learning Approaches to Evaluate Oilwell Cement Degradation, Stability and Integrity for CCUS Applications
Open the PDF for Scaling Field and Experimental Data Using Machine Learning Approaches to Evaluate Oilwell Cement Degradation, Stability and Integrity for CCUS Applications in another window
Add to Citation Manager
Proceedings Papers

Vibroacoustic Technology: Revolutionizing Pipeline Integrity Monitoring for Enhanced Performance

A. P. Gomes, M. Marino, S. del Giudice
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219125-MS
https://doi.org/10.2118/219125-MS
Add To Cart
View Paper titled, Vibroacoustic Technology: Revolutionizing Pipeline Integrity Monitoring for Enhanced Performance
Open the PDF for Vibroacoustic Technology: Revolutionizing Pipeline Integrity Monitoring for Enhanced Performance in another window
Add to Citation Manager
Proceedings Papers

The ESG Path to Low-Carbon Footprint: Recommended Practices and Lessons Learnt from Electrifying Recovery of the Giant Shale-Gas Basin in China

Zheng Tong, Shaolin Zhang, Shuai Li, Xiaoqi Wang, Zhigang Zhang, Ran Wei, Xinzhong Wang, Qiang Sun, Dingwei Weng
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219111-MS
https://doi.org/10.2118/219111-MS
Add To Cart
View Paper titled, The ESG Path to Low-Carbon Footprint: Recommended Practices and Lessons Learnt from Electrifying Recovery of the Giant Shale-Gas Basin in China
Open the PDF for The ESG Path to Low-Carbon Footprint: Recommended Practices and Lessons Learnt from Electrifying Recovery of the Giant Shale-Gas Basin in China in another window
Add to Citation Manager
Proceedings Papers

Challenges of Cementing in Extreme Environments

Ahmed Abdulhamid Mahmoud, Eslam M. Abdalrahman, Lobe Nje, Abdallah Almadani, Mustafa Al Ramadan, Salaheldin Elkatatny, Abdullah Sultan
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219144-MS
https://doi.org/10.2118/219144-MS
Add To Cart
View Paper titled, Challenges of Cementing in Extreme Environments
Open the PDF for Challenges of Cementing in Extreme Environments in another window
Add to Citation Manager
Proceedings Papers

Real-Time Sand Detection for Gas Wells Using AI Applications

A. Maharramli, F. Taghiyev, Sh. Alkhasli, T. Mammadov, I. Yusifov, R. Javadzade, Kh. Ahmadov
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219168-MS
https://doi.org/10.2118/219168-MS
Add To Cart
View Paper titled, Real-Time Sand Detection for Gas Wells Using AI Applications
Open the PDF for Real-Time Sand Detection for Gas Wells Using AI Applications in another window
Add to Citation Manager
Proceedings Papers

Harnessing Ensemble Learning Techniques for Accurate Interfacial Tension Estimation in Aqueous CO 2 Systems

Joshua Nsiah Turkson, Muhammad Aslam Md Yusof, Ingebret Fjelde, Yen Adams Sokama-Neuyam, Victor Darkwah-Owusu, Bennet Nii Tackie-Otoo
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219176-MS
https://doi.org/10.2118/219176-MS
Add To Cart
View Paper titled, Harnessing Ensemble Learning Techniques for Accurate Interfacial Tension Estimation in Aqueous CO 2 Systems
Open the PDF for Harnessing Ensemble Learning Techniques for Accurate Interfacial Tension Estimation in Aqueous CO 2 Systems in another window
Add to Citation Manager
Proceedings Papers

A Machine Learning Based Framework for Brine-Gas Interfacial Tension Prediction: Implications for H 2 , CH 4 and CO 2 Geo-Storage

Bin Pan, Tianru Song, Xia Yin, Yiran Jiang, Ming Yue, Hussein Hoteit, Hassan Mahani, Stefan Iglauer
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219225-MS
https://doi.org/10.2118/219225-MS
Add To Cart
View Paper titled, A Machine Learning Based Framework for Brine-Gas Interfacial Tension Prediction: Implications for H 2 , CH 4 and CO 2 Geo-Storage
Open the PDF for A Machine Learning Based Framework for Brine-Gas Interfacial Tension Prediction: Implications for H 2 , CH 4 and CO 2 Geo-Storage in another window
Add to Citation Manager
Proceedings Papers

Prediction of Total Skin Factor in Perforated Wells Using Models Powered by Deep Learning and Machine Learning

S. Thabet, H. M. Zidan, A. Elhadidy, A. Helmy, T. Yehia, H. Elnaggar, M. Elshiekh
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219187-MS
https://doi.org/10.2118/219187-MS
Add To Cart
View Paper titled, Prediction of Total Skin Factor in Perforated Wells Using Models Powered by Deep Learning and Machine Learning
Open the PDF for Prediction of Total Skin Factor in Perforated Wells Using Models Powered by Deep Learning and Machine Learning in another window
Add to Citation Manager
Proceedings Papers

Introducing the Power of Augmented Reality Revolutionizes Subsea Installation in Gulf of Suez. Case History: - First Time in Egypt

A. Ismail, M. Abdelrazik., A. Salama, L. Abouelmaati, M. Saloma, M. Medany
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219212-MS
https://doi.org/10.2118/219212-MS
Add To Cart
View Paper titled, Introducing the Power of Augmented Reality Revolutionizes Subsea Installation in Gulf of Suez. Case History: - First Time in Egypt
Open the PDF for Introducing the Power of Augmented Reality Revolutionizes Subsea Installation in Gulf of Suez. Case History: - First Time in Egypt in another window
Add to Citation Manager
Proceedings Papers

Revealing Insights in Evaluating Tight Carbonate Reservoirs: Significant Discoveries via Statistical Modeling. An In-Depth Analysis Using Integrated Machine Learning Strategies

Amr Gharieb, Mohamed Adel Gabry, Ahmed Algarhy, Mohamed Elsawy, Nihal Darraj, Samuel Adel, Maged Taha, Abdelrafae Hesham
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219199-MS
https://doi.org/10.2118/219199-MS
Add To Cart
View Paper titled, Revealing Insights in Evaluating Tight Carbonate Reservoirs: Significant Discoveries via Statistical Modeling. An In-Depth Analysis Using Integrated Machine Learning Strategies
Open the PDF for Revealing Insights in Evaluating Tight Carbonate Reservoirs: Significant Discoveries via Statistical Modeling. An In-Depth Analysis Using Integrated Machine Learning Strategies in another window
Add to Citation Manager
Proceedings Papers

Extensive Study on the Influencing Parameters of Sc CO 2 Foam Viscosity for Enhanced Oil Recovery and Carbon Sequestration: A Machine Learning Approach

Ahmed Bashir, Ahmed Kasha, Shirish Patil, Murtada Saleh Aljawad, Muhammad Shahzad Kamal
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219163-MS
https://doi.org/10.2118/219163-MS
Add To Cart
View Paper titled, Extensive Study on the Influencing Parameters of Sc CO 2 Foam Viscosity for Enhanced Oil Recovery and Carbon Sequestration: A Machine Learning Approach
Open the PDF for Extensive Study on the Influencing Parameters of Sc CO 2 Foam Viscosity for Enhanced Oil Recovery and Carbon Sequestration: A Machine Learning Approach in another window
Add to Citation Manager
Proceedings Papers

Gas Rate Predictive Model as an Alternative to Choke Equations

Abdullah BinZiad, Abdul Muqtadir Khan, Fahad O. Alshammari, Abdullah Alsubaii
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219234-MS
https://doi.org/10.2118/219234-MS
Add To Cart
View Paper titled, Gas Rate Predictive Model as an Alternative to Choke Equations
Open the PDF for Gas Rate Predictive Model as an Alternative to Choke Equations in another window
Add to Citation Manager
Proceedings Papers

AI-Driven Green Optimization in Well Construction: Carbon Emission Management Through Technical Limit Performance Benchmarking

K. W. Amadi, M. T. Alsaba, J. H. El Achkar, R. M Elgaddafi
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219214-MS
https://doi.org/10.2118/219214-MS
Add To Cart
View Paper titled, AI-Driven Green Optimization in Well Construction: Carbon Emission Management Through Technical Limit Performance Benchmarking
Open the PDF for AI-Driven Green Optimization in Well Construction: Carbon Emission Management Through Technical Limit Performance Benchmarking in another window
Add to Citation Manager
Proceedings Papers

Real-Time Identification of Geological Factuals by Integrating Formation Micro Resistivity Imaging Logs With Computer Vision

Amr Gharieb, Mohamed Adel Gabry, Ahmed Algarhy, Mohamed Elsawy, Ahmed Farid Ibrahim, Nihal Darraj, Samuel Adel, Abdelrafae Hesham
Paper presented at the GOTECH, May 7–9, 2024
Paper Number: SPE-219194-MS
https://doi.org/10.2118/219194-MS
Add To Cart
View Paper titled, Real-Time Identification of Geological Factuals by Integrating Formation Micro Resistivity Imaging Logs With Computer Vision
Open the PDF for Real-Time Identification of Geological Factuals by Integrating Formation Micro Resistivity Imaging Logs With Computer Vision in another window
Add to Citation Manager

Product(s) added to cart

Go to Cart Continue Browsing
Close Modal