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SPE Orange and Blue Logo ATCE
20–22 October 2025 | George R. Brown Convention Center | Houston, TX, USA

20–22 October 2025
George R. Brown Convention Center
Houston, TX, USA

SPE white Logo ATCE

20–22 October 2025
George R. Brown Convention Center
Houston, TX, USA

2025 Technical Program

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SPE ATCE

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Use of Machine Learning Models and Data Analytics: From Complex Parent-Child Well Interactions, Production Forecasting, to Enhance Oil Recovery

Monday, 20 October
Room 340
Technical Session
This session highlights various applications of machine learning models and data analytics to gain understanding about complex parent-child well interactions, evaluate petrophysical properties, improve production forecasting, and optimize oil and gas developments.
Session Chairpersons
Mun-Hong Hui - Chevron Corporation
Elyezer Lolon - Liberty Energy
  • 1400-1425 227985
    A Physics-Informed Transformer Framework for Spatio-Temporal Modeling and Energy-Carbon Tradeoffs in CCUS-EOR
    B. Shen, China University of Petroleum, Beijing; S. Yang, China University of Petroleum Beijing; X. Gao, China University of Petroleum, Beijing; H. Zeng, University of Alberta
  • 1425-1450 227942
    Ensemble-based Interpretation of Inter-well Tracer Tests for Residual Oil Saturation Estimation Using ESMDA and Fourier Neural Operators
    Z. Zhao, Y. Ou, The University of Texas at Austin; C. Jia, King Abdullah University of Science & Tech; R. Li, K. Mohanty, The University of Texas at Austin
  • 1450-1515 228014
    Forecasting Oil Production With Time-series Foundation Models - A Benchmark Study Against Classical Machine Learning Models
    A. Centeno Franco, N. Belayouni, R. Ayoubi, AIQ; F. Al-Kaabi, Khalifa University
  • 1545-1610 227945
    Demystifying Child Well Degradation with Novel Feature Engineering: Part2 − Machine Learning Analysis for Child Well Degradation with Multiple Parent Wells in the Delaware Basin
    Y. Ben, C. Gao, S. Choudhry, Occidental Petroleum Corporation; J. Cassanelli, Occidental Petroleum Corp.; J. Han, Texas A&M University; V. Muralidharan, Occidental Petroleum Corp.; R. Vaidya, OXY USA Inc.; H. Deng, R. Esquivel Sandoval, Y. Li, Occidental Petroleum Corp.
  • 1610-1635 228040
    Unconventional Inflow Performance Relationship and Machine Learning Study
    Y. Tang, Chevron North America E&P; S. Choi, Chevron Technology Center; J. Sun, Y. Lin, S. Khorsandi, Chevron Corporation; K. Marsac, Chevron Global Upstream; A. Zejli, Chevron Technical Center; A. Kurup, Chevron Subsurface; J. Visser, Chevron Technology Co; M. Noh, L. Olabinjo, Chevron Corporation
  • 1635-1700 228091
    Multi-constraint Intelligent Optimization for Accelerated Horizontal Well Pattern Deployment in Complex Unconventional Reservoirs
    H. Li, China University of Petroleum-Beijing; C. Xian, China University of Petroleum Beijing; J. Liao, China Oilfield Services Limited; Y. Liu, F. Li, China University of Petroleum-Beijing; X. Huang, Y. He, PetroChina Zhejiang Oilfield Company
  • Alternate 228032
    Dynamic Optimization of SAGD Injection-Production Parameters Using Reinforcement Learning for Enhanced Thermal Recovery and Subcool Control
    Q. Wu, G. Han, Z. Zhu, China University of Petroleum (Beijing); L. Peng, CNPC Engineering Technology R&D Company Ltd; X. Liang, China University of Petroleum (Beijing)
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