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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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Energy Transition: Data Science and Engineering Analytics in CCUS, Renewable Geothermal and LNG Applications

Tuesday, 21 October
Room 332AD
Technical Session
This technical session highlights several energy transition explorations with data science and engineering analytics. The coverage of the topics includes: 1) carbon storage and utilization for screening, pressure, and plume tracking, EOR, and uncertainty analysis with advanced machine learnings. 2) renewable energy of geothermal studies for fracture network quantification and thermal/heat behaviors in use cases with various of the machine learning techniques. 3) Oil & LNG markets studies with machine learning for trading dynamics. Encourage you join the session to catch up such innovative data science and engineering analytics applications, energy transition trends, and use cases.
Session Chairpersons
Guoxiang Liu - U.S. Department of Energy National Technology Lab
Annie Shen - Enverus
  • 0830-0855 228266
    Quantifying The Uncertainty Of The 3d Evolution Of Co2 Mass And Pressure Plumes For Site Screening Applications With Fourier Neural Operators
    S. Pawar, A. Chandra, Shell Information Technology International Inc.; A. Panda, Shell India Markets Pvt. Ltd.; F. Alpak, Shell International Exploration and Production Inc.; J. Snippe, Shell Global Solutions International B.V.; P. Devarakota, Shell Information Technology International Inc.; M. Koch, K. Azizzadenesheli, NVIDIA; D. Hohl, Shell Information Technology International Inc.
  • 0855-0920 227900
    Co2-brine Gravity-driven Displacement Estimation Using Traditional Numerical Methods And Deep Learning
    J.K. Pauyac Estrada, Louisiana State University (Petr. Eng. Dept); M. Zeidouni, Louisiana State University
  • 0920-0945 228196
    Proxy Model Optimization For Brine Production In Carbon Capture And Storage Operations
    K. Alokla, J. OMEKE, Texas A&M University; D. Lochary, Enbridge Inc; Q. Al Maqbali, Advanced Resources International (ARI); J. Lee, T. Blasingame, Texas A&M University
  • 1015-1040 227866
    Near-Real Time CO2 Plume Monitoring And Visualization Considering Geologic Uncertainty At The Illinois Basin-Decatur Carbon Sequestration Project
    T. Sakai, M. Nagao, A. Datta-gupta, Texas A&M University
  • 1040-1105 227935
    Deep Learning Driven Reservoir Simulation For Mapping Performance Of Co2-eor And Storage In Tight Oil Reservoir
    H. Vo Thanh, K. Furui, Waseda University
  • 1105-1130 227883
    Knowledge-based Machine Learning For Optimized Cement Design In Co₂ Storage And Geothermal Wells
    A. Alsubaih, university of Texas at Austin; K. Sepehrnoori, The University of Texas At Austin; W.J. Al-Mudhafar, Basra Oil Company
  • Alternate 228102
    Do We Really Need Hundreds Of Machine Learning Models In Petroleum Industry?
    Q. Mao, University of British Columbia; X. Yang, University of Calgary; J. Yang, PetroChina Changqing Oilfield Company; Y. Cao, University of British Columbia
  • Alternate 228167
    Leveraging Artificial Intelligence To Predict Thermal Conductivity And Heat Extraction From Utah Forge Geothermal System
    F. Nath, Texas A&M International University
  • Alternate 228121
    Virtual Barrels And Real Markets: Bridging Physical Trading And Financial Speculation In Oil And LNG Markets Through System Dynamics And Machine Learning
    F. Vera, Mire Petroleum Associates
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