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Proceedings Papers
Towards Universal Production Forecasting via Adversarial Transfer Learning and Transformer with Application in the Shengli Oilfield, China
Available to Purchase
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4032318-MS
Proceedings Papers
Physics Informed Deep Learning Models for Improving Shale and Tight Forecast Scalability and Reliability
Available to PurchaseKainan 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
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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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043246-MS
Proceedings Papers
A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4040968-MS
Proceedings Papers
Predicting Coiled-Tubing Drilling Dynamics Using Transformers
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043196-MS
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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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4043980-MS
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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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044069-MS
Proceedings Papers
Convolutional Neural Networks Forecasting for Unconventional Drilling Units for US Land
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044012-MS
Proceedings Papers
Analytical and Machine Learning Based Modifications to Unconventional Reservoir Simulation Models to Capture Near-Fracture Transient Effects
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4044074-MS
Proceedings Papers
Evaluation of Empirical Correlations and Time Series Models for the Prediction and Forecast of Unconventional Wells Production in Wolfcamp A Formation
Available to PurchaseAimen 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
Proceedings Papers
Artificial Intelligence Integration for Optimal Reservoir Data Analysis and Pattern Recognition
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4054687-MS
Proceedings Papers
Cluster Efficiency-Based Stimulation: Real-Time Quantified Screenout Monitoring and Diversion Evaluation Through a Data Model Approach
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4056167-MS
Proceedings Papers
Effects of Early-Time Production Data on Machine-Learning-Assisted Long-Term Production Forecasting
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4055265-MS
Proceedings Papers
A Deep Learning Approach to Predicting Remaining Useful Life for Downhole Drilling Sensors Using Synthetic Data Generation
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4046687-MS
Proceedings Papers
Using ANN Prediction in Carbonate Reservoir Properties: Implication for Large-Scale Reservoir Correlation
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4054990-MS
Proceedings Papers
Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models
Available to PurchaseFatick 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
Proceedings Papers
Optimization Method for Fracture-Network Design Under Transient and Pseudosteady Condition Using UFD Technique and Deep Learning Approach
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3853784-MS
Proceedings Papers
Predicting Facies, Rock, and Geomechanical Properties Using Convolutional Neural Networks: A Case Study from an Unconventional Shale Reservoir
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3862247-MS
Proceedings Papers
Deep Learning Models for Methane Emissions Identification and Quantification
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3866049-MS
Proceedings Papers
Auto-Identification and Real-Time Warning Method of Multiple Type Events During Multistage Horizontal Well Fracturing
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Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3863378-MS
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