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Negative Production Factor Recognition and Separation From Other Pore Fluids with Advanced Logging Techniques: A Case Study From Junggar Basin
Z. Zhang1, X. Meng1, J. Lv1, P. Yang1, L. Cai*2, L. Li2, J. Wu2, X. Zhao2 (1. Sinopec Shengli Oilfield Company; 2. SLB)
Permeability Variation During CO2 Pre-Fracturing in Shale Reservoir: A Case Study of Junggar Basin
W. Tang*, F. Zhou, L. Hu, G. Huang, L. Li (China University of Petroleum Beijing)
PVT Correlations for Initial Formation Volume Factor Estimation: A Case Study in Midland Basin
S. Moonesan* (University of Texas)
Unveiling Stimulation Fluid-Driven Alterations of Pore Architecture in the Mowry Shale, Wyoming
Z. Kou2, G. Copeland1, F. McLaughlin1, V. Alvarado*1 (1. University of Wyoming; 2. Columbia University)
Unlocking Gas Potential in Deep Shale by Advanced Pulsed Neutron Logging Behind the Casing: Case Study in Sichuan Basin, China
S. Fang2, Z. An Zhao2, K. Li*1, Y. Wang1, J. Wu1, X. Zhao1, H. Geng Li1 (1. SLB; 2. PetroChina SouthWest Oil and Gas Company)

Deciphering Deep Coalbed Methane Sweet Spots in the Ordos Basin: Geological Influences and Characteristics
Z. Liu*, Z. Hu, B. Shen, D. Feng, W. Du, S. Zhao, X. Chen, J. Zhang, J. Wan, Z. Liu (Sinopec Petroleum Exploration and Production Research Institute)
Porosity, Permeability, and Rock Mechanics Characteristics of Deep Shales Under High-Temperature and High-Pressure Conditions
C. Sun*2, 1, H. Nie2, 1, W. Du2, 1, Z. Hu1 (1. Petroleum Exploration and Production Institution of Sinopec; 2. National Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Efficient Development)

A Novel Workflow to Characterize Production Profiles of Shale Gas Horizontal Wells Using Distributed Temperature Sensing Data
C. Liu*1, X. Yang3, C. Chang3, N. Li2, W. Yu2, K. Sepehrnoori1 (1. University of Texas at Austin; 2. SimTech LLC; 3. Petrochina Southwest Oil and Gas Field Company)
Seismic Characterization of the Vaca Muerta Formation in the Central Region of the Neuquén Basin
S. R. Lagos, K. B. Anis*, A. P. Kautyian Ziyisyian (YPF SA)

An Experimental Study on the Effect of Capillary Condensation on the Geomechanical Properties of Tight Rocks
A. Albannay*1, 2, M. Baig1, A. Alharthi1, A. Al Hashmi1, H. Al Marzooqi1, B. Bui2, S. A. Elazab1, A. Al Blooshi1 (1. Abu Dhabi National Oil Company; 2. Colorado School of Mines)
New Approach for Well Clean-Up and Well Testing Operations in High-Rate Gas-Condensate Fields Resulting in Smart Sand Management System
L. Perez*1, C. Denton1, M. Ferrin1, E. Abbad2, J. Leal2 (1. SOS-STI; 2. Saudi Aramco)
Source-Rock Reservoirs Production Forecast: Investigating the Impact of Pressure-Dependent Permeability (PDP) – A Case Study Approach
J. C. Cardenas1, H. Ribon Barrios1, O. Ortiz2, O. Rojas Conde*3, H. Galvis Silva4 (1. Ecopetrol; 2. Universidad Industrial de Santander (UIS); 3. Viking Engineering; 4. Texas A&M University)
Numerical Modeling of Shear Deformation Measurements From Distributed Fiber Optic Strain Sensing for Detection and Mitigation of Induced Seismicity
A. Srinivasan*1, K. Wu1, G. Jin2, G. Moridis1, 3 (1. Texas A&M University; 2. Colorado School of Mines; 3. Lawrence Berkeley National Laboratory)
Integrating Experiments and Well Logs to Predict Caney Shale Static Mechanical Properties During Production with Supervised Machine Learning
S. M. Elkholy*, H. Lee, M. Radonjic (Oklahoma State University)
Fracture Deflection vs.Penetration at Interfaces: What Matters Most, Strength or Toughness?
J. Gutierrez1, S. Serebrinsky*2, A. Huespe3 (1. INVAP; 2. YPF Tecnología; 3. Centro de Investigación de Métodos Computacionales (CIMEC))

Artificial Intelligence (AI) Integration for Optimal Reservoir Data Analysis and Pattern Recognition
L. Hamilton*2, M. Rauch1 (1. TGS; 2. none)
Machine Learning Prediction and the Impact of CO2 Injection on S-Wave in 20 Years in the Legacy Well Field
S. Morshed1, S. Khan*2, W. Hao3 (1. Rayscent Limited Company; 2. Texas State University; 3. Cella Mineral Storage)
Using ANN Prediction in Carbonate Reservoir Properties: Implication for Large-Scale Reservoir Correlation
A. Abdelkarim*, J. Humphrey (CPG)
Estimation of Stimulated Reservoir Region for Hydraulic Fracturing in Shale Gas Well Based on Ensemble Learning Algorithm
Y. Luo*1, 2, B. Kang1, Y. Feng3, H. Wang1, Z. Mi1, Y. Cheng1, Y. Xiao1, X. Zhao1, J. Guo2, C. Lu2 (1. Zhenhua Oil Co.; 2. Southwest Petroleum University; 3. Exploration and Development Research Institute of PetroChina Southwest Oil and Gas Field Company)
Evaluation of Empirical Correlations and Time Series Models for the Prediction and Forecast of Unconventional Wells Production in Wolf Camp A Formation
A. Laalam*1, H. Khalifa2, H. Ouadi2, M. Benabid1, O. Tomomewo2, M. Al Krmagi3 (1. Colorado School of Mines; 2. University of North Dakota; 3. Texas A&M University)
Machine Learning-Based Sweet Spot Prediction Method for Canada Tight Sandstone Gas Reservoir
Z. Chen*1, Y. Fang2, H. Su1, Y. Qian1, Y. Chen*3 (1. Sinopec Petroleum Exploration and Production Research Institute; 2. CNPC Engineering Technology R&D Company Limited; 3. Oil and Gas Technology Research Institute Changqing Oilfield Company)
Machine Learning-Powered EUR Prediction and Performance Forecasting for Unconventional Reservoirs
C. Vega*, P. Panja, M. Deo, B. J. McPherson (University of Utah)
Estimated Ultimate Recovery in Horizontal Wells: A Data-Driven Approach
A. Alzahabi1, A. Kamel*1, A. Trindade2 (1. University of Texas Permian Basin; 2. Texas Tech University)
Evaluation Of Chemical Additives Impact on Well Productivity by Using Machine Learning Algorithms
S. Baki*, S. Dursun, N. M. Alotaibi (Saudi Aramco)
Real Time Data Driven Framework for Rate of Penetration Optimization of S-Shaped Wells in a Southern Iraq Field Using Prior Knowledge
E. H. AlKamil2, A. Alattar*1, M. Karnot4, M. Talib4, A. Mazin2, S. Taher4, M. Al Alwani3 (1. Spotfire; 2. University Of Basra; 3. Chesapeake; 4. SLB)
A Machine-Learning-Based Workflow for Drilling Risk Prediction of Wellbore Instability and Trajectory Optimization in Ultra-Deep Formation
H. Wang1, R. Zhang2, Z. Deng3, J. Meng1, H. Wang1, Y. Zhou1, F. Yang1, J. Chang1, Y. Xiao1, H. Pang*4 (1. SINOPEC Exploration and Production Research Institute; 2. Texas A&M University; 3. China University of Geoscience; 4. China University of Petroleum)

A New and Cost Effective Way to Estimate Production in Unconventional Fields Using Advanced Multiphase Flowmeter Technology in North Dakota
K. Moncada*, L. Husoschi, B. Marmon, B. Theuveny, J. A. Dodds, J. Hussenet (SLB)
Case Studies: Integrated Production Profiling Analyses from Distributed Temperature and Acoustic Data
Y. Mao*, C. Godefroy, A. Gysen (Interpretive Software Products (ISP))
Horizontal Well Flow Profile Assessment: Advanced Thermal-Hydrodynamic Modeling with Fracture Flow Analysis
M. Volkov* (TGT Oilfield Services)
Unique Resiliency of Biosurfactants in the Lab and Field with Depleting Concentration
M. Pearl*, E. Kakadjian, J. Hancock, H. Au Yong, S. Pradhan (Locus Bio-Energy)
Smart Control: Advancing the Optimization and Control of Artificial Lift Systems
S. Bost*, J. Searle (SIG Machine Learning Pty Ltd.)
Direct Characterization of Complex Fracture Network Using Improved Rate-Transient Analysis Method in Tight Oil Reservoir Exhibiting Multiphase Flow
J. Tian*, B. Yuan, J. Li, W. Zhang (China University of Petroleum East China)

Geothermal Potential and Risk Assessment of Repurposing Old Wellbores for Geothermal Applications: Case Study of Oklahoma and Texas
N. Konate*, S. Salehi (University of Oklahoma)
Predicting Gas EUR in Shale Plays Using Machine Learning Methods: A Comparative Study of Marcellus, Barnett, and Eagle Ford Shales
A. F. Ibrahim*1, N. Darraj2, A. Gharieb3, M. A. Gabry5, A. Algarhy4 (1. King Fahd University of Petroleum & Minerals; 2. Imperial College London; 3. Apache Corporation; 4. Marietta College; 5. University of Houston)
A Holistic Approach for Rapid Unconventional Reservoir Optimization
W. Zheng*, R. Banerjee, R. Carvajal, M. Koley (SLB)
Enhanced Decision Making and Asset Optimization for Unconventional Resources with Type Wells (DCA), RTA- Based Numerical Modeling and Machine Learning
A. Haghighat*, T. Burrough (S&P Global)
Effects of Early-Time Production Data on Machine-Learning-Assisted Long-Term Production Forecasting
M. H. Elkady*1, S. Misra1, V. T. Kumar1, U. Odi2, A. Silver2 (1. Texas A&M University; 2. Aramco Americas)
Forecasting Production Loss for Delayed Secondary Bench Development in the Midland Basin
D. Niederhut*, A. Cui, B. Davis (Novi Labs)
Application of a Sparse Hybrid Data-Driven and Physics Model in Unconventional Reservoirs for Production Forecasting
H. Zalavadia*, P. S. Chauhan, S. Sankaran (Xecta Digital Labs)

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Sponsoring Organizations

Society of Petroleum Engineers American Association of Petroleum Geologists Society of Exploration Geophysicists

Endorsing Organizations

American Rock Mechanics Association The Minerals, Metals and Materials Society Society of Petrophysicists and Well Log Analysts

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URTeC 2024
17-19 June 2024
George R. Brown Convention Center
Houston, Texas