1-20 of 373
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

Deep Learning Models for Methane Emissions Identification and Quantification

Ismot Jahan, Mohamed Mehana, Bulbul Ahmmed, Javier E. Santos, Daniel O'Malley, Hari Viswanathan
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3866049-MS
https://doi.org/10.15530/urtec-2023-3866049
Add To Cart
View Paper titled, Deep Learning Models for Methane Emissions Identification and Quantification
Open the PDF for Deep Learning Models for Methane Emissions Identification and Quantification in another window
Add to Citation Manager
Proceedings Papers

Estimating Real-Time Pore Pressure at the Bit via Machine Learning

Matthew Reilly, Gareth Taylor, Orlando De Jesus, Muhlis Unaldi, John Thurmond, Mike Party, Koda Chovanetz
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3865091-MS
https://doi.org/10.15530/urtec-2023-3865091
Add To Cart
View Paper titled, Estimating Real-Time Pore Pressure at the Bit via Machine Learning
Open the PDF for Estimating Real-Time Pore Pressure at the Bit via Machine Learning in another window
Add to Citation Manager
Proceedings Papers

Machine Learning Facilitates Prediction of Geomechanical Properties Directly from SEM Images in Unconventional Plays

Heehwan Yang, Deepak Devegowda, Mark Curtis, Chandra Rai
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3866084-MS
https://doi.org/10.15530/urtec-2023-3866084
Add To Cart
View Paper titled, Machine Learning Facilitates Prediction of Geomechanical Properties Directly from SEM Images in Unconventional Plays
Open the PDF for Machine Learning Facilitates Prediction of Geomechanical Properties Directly from SEM Images in Unconventional Plays in another window
Add to Citation Manager
Proceedings Papers

A Shapley Approach to Permian Rock Quality

Emily Head, Stephen Sagriff, Stephen Pratt, Brad Bernard
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3864794-MS
https://doi.org/10.15530/urtec-2023-3864794
Add To Cart
View Paper titled, A Shapley Approach to Permian Rock Quality
Open the PDF for A Shapley Approach to Permian Rock Quality in another window
Add to Citation Manager
Proceedings Papers

Optimizing Completions by Enhancing Near-Field Connectivity and Mitigating Stress Shadowing in Real-Time via Acoustic Based Workflow

Muhammad Khan, Jim Alsup, Nathan Crawford, Josh Kroschel
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3867323-MS
https://doi.org/10.15530/urtec-2023-3867323
Add To Cart
View Paper titled, Optimizing Completions by Enhancing Near-Field Connectivity and Mitigating Stress Shadowing in Real-Time via Acoustic Based Workflow
Open the PDF for Optimizing Completions by Enhancing Near-Field Connectivity and Mitigating Stress Shadowing in Real-Time via Acoustic Based Workflow in another window
Add to Citation Manager
Proceedings Papers

A Comprehensive Review of Fracture-Driven Interaction in Unconventional Oil and Gas Plays: Characterization, Real-Time Diagnosis, and Impact on Production

Harpreet Singh, Peng Cheng, Yuwei Pan, Chengxi Li, Yu Liu, Xi Wu, Mary Van Domelen, Samuel Rogers, Arash Dahi Taleghani, Meng Cao
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3866134-MS
https://doi.org/10.15530/urtec-2023-3866134
Add To Cart
View Paper titled, A Comprehensive Review of Fracture-Driven Interaction in Unconventional Oil and Gas Plays: Characterization, Real-Time Diagnosis, and Impact on Production
Open the PDF for A Comprehensive Review of Fracture-Driven Interaction in Unconventional Oil and Gas Plays: Characterization, Real-Time Diagnosis, and Impact on Production in another window
Add to Citation Manager
Proceedings Papers

Rock Thin-Section Analysis and Mineral Detection Utilizing Deep Learning Approach

Fatick Nath, Sarker Asish, Shaon Sutradhar, Zhiyang Li, Nazmul Shahadat, Happy R. Debi, S. M. Shamsul Hoque
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3865660-MS
https://doi.org/10.15530/urtec-2023-3865660
Add To Cart
View Paper titled, Rock Thin-Section Analysis and Mineral Detection Utilizing Deep Learning Approach
Open the PDF for Rock Thin-Section Analysis and Mineral Detection Utilizing Deep Learning Approach in another window
Add to Citation Manager
Proceedings Papers

Data Driven Oil Production Prediction and Uncertainty Quantification for Unconventional Asset Development Planning Through Machine Learning

Xiang (Rex) Ren, Jichao Yin, Feng Xiao, Sasha Miao, Sri Lolla, Changqing Yao, Steve Lonnes, Huafei Sun, Yang Chen, James Brown, Jorge Garzon, Piyush Pankaj
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3865670-MS
https://doi.org/10.15530/urtec-2023-3865670
Add To Cart
View Paper titled, Data Driven Oil Production Prediction and Uncertainty Quantification for Unconventional Asset Development Planning Through Machine Learning
Open the PDF for Data Driven Oil Production Prediction and Uncertainty Quantification for Unconventional Asset Development Planning Through Machine Learning in another window
Add to Citation Manager
Proceedings Papers

Experimental and Numerical Analysis of Toe-Up Trajectory Inclination Angle and Gas Lift Rate Effect on Unconventional Oil Well Performance

Youcef Khetib, Ala Eddine Aoun, Kegang Ling
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3869530-MS
https://doi.org/10.15530/urtec-2023-3869530
Add To Cart
View Paper titled, Experimental and Numerical Analysis of Toe-Up Trajectory Inclination Angle and Gas Lift Rate Effect on Unconventional Oil Well Performance
Open the PDF for Experimental and Numerical Analysis of Toe-Up Trajectory Inclination Angle and Gas Lift Rate Effect on Unconventional Oil Well Performance in another window
Add to Citation Manager
Proceedings Papers

Optimizing Production Potential of Unconventional Oil and Gas Wells: Insights from Statistical and Machine Learning Analysis of Well Spacing, Sequencing, and Landing Zone TVD Across Eleven North American Plays

Harpreet Singh, Chengxi Li, Peng Cheng, Huailiang Liu
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3866325-MS
https://doi.org/10.15530/urtec-2023-3866325
Add To Cart
View Paper titled, Optimizing Production Potential of Unconventional Oil and Gas Wells: Insights from Statistical and Machine Learning Analysis of Well Spacing, Sequencing, and Landing Zone TVD Across Eleven North American Plays
Open the PDF for Optimizing Production Potential of Unconventional Oil and Gas Wells: Insights from Statistical and Machine Learning Analysis of Well Spacing, Sequencing, and Landing Zone TVD Across Eleven North American Plays in another window
Add to Citation Manager
Proceedings Papers

Maximizing Efficiency of Deep-Reinforcement Learning Agents in Autonomous Directional Drilling with Hyperparameter Optimization

Vivek Kesireddy, Georgy Kompantsev, Sheelabhadra Dey, Eduardo Gildin, Enrique Z. Losoya, Narendra Vishnumolakala
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3865879-MS
https://doi.org/10.15530/urtec-2023-3865879
Add To Cart
View Paper titled, Maximizing Efficiency of Deep-Reinforcement Learning Agents in Autonomous Directional Drilling with Hyperparameter Optimization
Open the PDF for Maximizing Efficiency of Deep-Reinforcement Learning Agents in Autonomous Directional Drilling with Hyperparameter Optimization in another window
Add to Citation Manager
Proceedings Papers

A Geomechanics and Pore Pressure Informed Stage Level Optimization Case Study for Unconventional, Infill Development in the Powder River Basin

Joel Mazza, Justin Kegel, Steve Van Delinder, Tom Hewett, Beth Emborsky, Scott Patrick
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3869179-MS
https://doi.org/10.15530/urtec-2023-3869179
Add To Cart
View Paper titled, A Geomechanics and Pore Pressure Informed Stage Level Optimization Case Study for Unconventional, Infill Development in the Powder River Basin
Open the PDF for A Geomechanics and Pore Pressure Informed Stage Level Optimization Case Study for Unconventional, Infill Development in the Powder River Basin in another window
Add to Citation Manager
Proceedings Papers

Auto-Identification and Real-Time Warning Method of Multiple Type Events During Multistage Horizontal Well Fracturing

Mingze Zhao, Yue Li, Yuyang Liu, Bin Yuan, Siwei Meng, Wei Zhang, He Liu
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3863378-MS
https://doi.org/10.15530/urtec-2023-3863378
Add To Cart
View Paper titled, Auto-Identification and Real-Time Warning Method of Multiple Type Events During Multistage Horizontal Well Fracturing
Open the PDF for Auto-Identification and Real-Time Warning Method of Multiple Type Events During Multistage Horizontal Well Fracturing in another window
Add to Citation Manager
Proceedings Papers

Machine-Learning-Assisted Induced Seismicity Characterization and Forecasting of the Ellenburger Formation in Northern Midland Basin

Niven Shumaker, Kaustubh Shrivastava, Mohamed Afia
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3855873-MS
https://doi.org/10.15530/urtec-2023-3855873
Add To Cart
View Paper titled, Machine-Learning-Assisted Induced Seismicity Characterization and Forecasting of the Ellenburger Formation in Northern Midland Basin
Open the PDF for Machine-Learning-Assisted Induced Seismicity Characterization and Forecasting of the Ellenburger Formation in Northern Midland Basin in another window
Add to Citation Manager
Proceedings Papers

Understanding Unconventional Reservoirs with an Integrated Physics and Machine Learning Based Methods – Case Studies and Novel Approaches from Tight Gas and Tight Oil Reservoir

Gaurav Sharma, Breandan Gaffney, Jaron Van Dijken, Jim Lee, Marshal Doig
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3863143-MS
https://doi.org/10.15530/urtec-2023-3863143
Add To Cart
View Paper titled, Understanding Unconventional Reservoirs with an Integrated Physics and Machine Learning Based Methods – Case Studies and Novel Approaches from Tight Gas and Tight Oil Reservoir
Open the PDF for Understanding Unconventional Reservoirs with an Integrated Physics and Machine Learning Based Methods – Case Studies and Novel Approaches from Tight Gas and Tight Oil Reservoir in another window
Add to Citation Manager
Proceedings Papers

Data-Driven Analysis for Causality of Parent–Child Interactions in the Bakken

Kyoung Suk Min, Alexander V. Chakhmakhchev, Xue Yu, Nicholas A. Azzolina, Darren D. Schmidt, Bethany A. Kurz, James A. Sorensen
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3862589-MS
https://doi.org/10.15530/urtec-2023-3862589
Add To Cart
View Paper titled, Data-Driven Analysis for Causality of Parent–Child Interactions in the Bakken
Open the PDF for Data-Driven Analysis for Causality of Parent–Child Interactions in the Bakken in another window
Add to Citation Manager
Proceedings Papers

System and Method for Automated Detection of Fracture Dependent Interactions

Edgar Dias, Larry Bowden
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3861644-MS
https://doi.org/10.15530/urtec-2023-3861644
Add To Cart
View Paper titled, System and Method for Automated Detection of Fracture Dependent Interactions
Open the PDF for System and Method for Automated Detection of Fracture Dependent Interactions in another window
Add to Citation Manager
Proceedings Papers

Enhancing Surface Production Measurements and Simplifying Field Architecture with Multiphase Flowmeters in the Permian and Eagle Ford Shale

Katharine Moncada, Liviu Husoschi, Bertrand Theuveny
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3861108-MS
https://doi.org/10.15530/urtec-2023-3861108
Add To Cart
View Paper titled, Enhancing Surface Production Measurements and Simplifying Field Architecture with Multiphase Flowmeters in the Permian and Eagle Ford Shale
Open the PDF for Enhancing Surface Production Measurements and Simplifying Field Architecture with Multiphase Flowmeters in the Permian and Eagle Ford Shale in another window
Add to Citation Manager
Proceedings Papers

Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models

Fatick Nath, Sarker Asish, Happy R. Debi, Mohammed Omar S. Chowdhury, Zackary J. Zamora, Sergio Muñoz
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3863926-MS
https://doi.org/10.15530/urtec-2023-3863926
Add To Cart
View Paper titled, Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models
Open the PDF for Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models in another window
Add to Citation Manager
Proceedings Papers

Predicting Facies Controls on Well Performance, Lea County NM

Michael Maler, Jason Eleson, Andrew Lewis
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3862919-MS
https://doi.org/10.15530/urtec-2023-3862919
Add To Cart
View Paper titled, Predicting Facies Controls on Well Performance, Lea County NM
Open the PDF for Predicting Facies Controls on Well Performance, Lea County NM in another window
Add to Citation Manager

Product(s) added to cart

Go to Cart Continue Browsing
Close Modal