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Proceedings Papers

Towards Universal Production Forecasting via Adversarial Transfer Learning and Transformer with Application in the Shengli Oilfield, China

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Ji Chang, Jin Meng, Dongwei Zhang, Tianrui Ye, Han Wang, Yitian Xiao
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4032318-MS
https://doi.org/10.15530/urtec-2024-4032318
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View Paper titled, Towards Universal Production Forecasting via Adversarial Transfer Learning and Transformer with Application in the Shengli Oilfield, China
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Proceedings Papers

Physics Informed Deep Learning Models for Improving Shale and Tight Forecast Scalability and Reliability

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Kainan Wang, Lichi Deng, Yuzhe Cai, Guido Di Federico, Keith Ramsaran, Mun Hong Hui, Hussein Alboudwarej, Christian Hager, Yuguang Chen, Xian-Huan Wen
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4042557-MS
https://doi.org/10.15530/urtec-2024-4042557
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View Paper titled, Physics Informed Deep Learning Models for Improving Shale and Tight Forecast Scalability and Reliability
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Proceedings Papers

Real Time Data Driven Framework for Rate of Penetration Optimization of S-Shaped Wells in a Southern Iraq Field Using Prior Knowledge

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Ethar H. AlKamil, Atheer Alattar, Mahdi Karnot, Muntadhar Talib, Abdulla Mazin, Salam Taher
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043246-MS
https://doi.org/10.15530/urtec-2024-4043246
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View Paper titled, Real Time Data Driven Framework for Rate of Penetration Optimization of S-Shaped Wells in a Southern Iraq Field Using Prior Knowledge
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Proceedings Papers

A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation

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Vanessa Simoes, Atul Katole, Bhuvaneswari Sankaranarayanan, Tao Zhao, Aria Abubakar
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4040968-MS
https://doi.org/10.15530/urtec-2024-4040968
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View Paper titled, A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation
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Proceedings Papers

Predicting Coiled-Tubing Drilling Dynamics Using Transformers

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Carlos Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043196-MS
https://doi.org/10.15530/urtec-2024-4043196
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View Paper titled, Predicting Coiled-Tubing Drilling Dynamics Using Transformers
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Proceedings Papers

A Novel Fusion: Integrating Artificial Neural Networks and Production Fit Models for Swift and Coherent Data-Physics Predictive Modeling of a Mature Oil Field in Texas

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Felipe Ospina!, Pallav Sarma, Carlos Calad
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043980-MS
https://doi.org/10.15530/urtec-2024-4043980
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View Paper titled, A Novel Fusion: Integrating Artificial Neural Networks and Production Fit Models for Swift and Coherent Data-Physics Predictive Modeling of a Mature Oil Field in Texas
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Proceedings Papers

An Innovative Approach to Capture Depletion Impact in Unconventional Reservoir Production Prediction Using Machine Learning and a Time-Dependent Depletion Function

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Edwin Ortega, Kirsten Landry
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044069-MS
https://doi.org/10.15530/urtec-2024-4044069
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View Paper titled, An Innovative Approach to Capture Depletion Impact in Unconventional Reservoir Production Prediction Using Machine Learning and a Time-Dependent Depletion Function
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Proceedings Papers

Convolutional Neural Networks Forecasting for Unconventional Drilling Units for US Land

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Francisco J. Parga Garcia, Jie Fang, Niven Shumaker
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044012-MS
https://doi.org/10.15530/urtec-2024-4044012
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View Paper titled, Convolutional Neural Networks Forecasting for Unconventional Drilling Units for US Land
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Proceedings Papers

Analytical and Machine Learning Based Modifications to Unconventional Reservoir Simulation Models to Capture Near-Fracture Transient Effects

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Hector E. Barrios-Molano, Alvaro Rey, Shihao Wang
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044074-MS
https://doi.org/10.15530/urtec-2024-4044074
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View Paper titled, Analytical and Machine Learning Based Modifications to Unconventional Reservoir Simulation Models to Capture Near-Fracture Transient Effects
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Proceedings Papers

Evaluation of Empirical Correlations and Time Series Models for the Prediction and Forecast of Unconventional Wells Production in Wolfcamp A Formation

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Aimen Laalam, Houdaifa Khalifa, Habib Ouadi, Mouna Keltoum Benabid, Olusegun Stanley Tomomewo, Mouad Al Krmagi
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043738-MS
https://doi.org/10.15530/urtec-2024-4043738
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View Paper titled, Evaluation of Empirical Correlations and Time Series Models for the Prediction and Forecast of Unconventional Wells Production in Wolfcamp A Formation
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Proceedings Papers

Artificial Intelligence Integration for Optimal Reservoir Data Analysis and Pattern Recognition

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Leon Hamilton, Marianne Rauch
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4054687-MS
https://doi.org/10.15530/urtec-2024-4054687
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View Paper titled, Artificial Intelligence Integration for Optimal Reservoir Data Analysis and Pattern Recognition
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Proceedings Papers

Cluster Efficiency-Based Stimulation: Real-Time Quantified Screenout Monitoring and Diversion Evaluation Through a Data Model Approach

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Roman Korkin, Abdul Muqtadir Khan
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4056167-MS
https://doi.org/10.15530/urtec-2024-4056167
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View Paper titled, Cluster Efficiency-Based Stimulation: Real-Time Quantified Screenout Monitoring and Diversion Evaluation Through a Data Model Approach
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Proceedings Papers

Effects of Early-Time Production Data on Machine-Learning-Assisted Long-Term Production Forecasting

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Mohammad H. Elkady, Siddharth Misra, Veena T. Kumar, Uchenna Odi, Andrew Silver
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4055265-MS
https://doi.org/10.15530/urtec-2024-4055265
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View Paper titled, Effects of Early-Time Production Data on Machine-Learning-Assisted Long-Term Production Forecasting
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Proceedings Papers

A Deep Learning Approach to Predicting Remaining Useful Life for Downhole Drilling Sensors Using Synthetic Data Generation

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Aamir Bader Shah, Yu Wen, Jiefu Chen, Xuqing Wu, Xin Fu
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4046687-MS
https://doi.org/10.15530/urtec-2024-4046687
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View Paper titled, A Deep Learning Approach to Predicting Remaining Useful Life for Downhole Drilling Sensors Using Synthetic Data Generation
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Proceedings Papers

Using ANN Prediction in Carbonate Reservoir Properties: Implication for Large-Scale Reservoir Correlation

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Abdallah Abdelkarim, John Humphrey
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4054990-MS
https://doi.org/10.15530/urtec-2024-4054990
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View Paper titled, Using ANN Prediction in Carbonate Reservoir Properties: Implication for Large-Scale Reservoir Correlation
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Proceedings Papers

Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models

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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
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View Paper titled, Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models
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Proceedings Papers

Optimization Method for Fracture-Network Design Under Transient and Pseudosteady Condition Using UFD Technique and Deep Learning Approach

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Junlei Wang, Yunsheng Wei, Yuewei Pan, Wei Yu
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3853784-MS
https://doi.org/10.15530/urtec-2023-3853784
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View Paper titled, Optimization Method for Fracture-Network Design Under Transient and Pseudosteady Condition Using UFD Technique and Deep Learning Approach
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Proceedings Papers

Predicting Facies, Rock, and Geomechanical Properties Using Convolutional Neural Networks: A Case Study from an Unconventional Shale Reservoir

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Ted Holden, Ruth Kurian, Mohammed Ibrahim, Daniel Hampson, Jonathan Downton
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3862247-MS
https://doi.org/10.15530/urtec-2023-3862247
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View Paper titled, Predicting Facies, Rock, and Geomechanical Properties Using Convolutional Neural Networks: A Case Study from an Unconventional Shale Reservoir
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Proceedings Papers

Deep Learning Models for Methane Emissions Identification and Quantification

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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
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View Paper titled, Deep Learning Models for Methane Emissions Identification and Quantification
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Proceedings Papers

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

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