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From Sensors to Semantics: GenAI and Data Science Driving Production and Facilities Innovation

Tuesday, 21 October
Room 340
Technical Session
This session highlights how the convergence of domain-specific large language models (LLMs), machine learning, and sensor-driven analytics is reshaping production and facilities workflows across the energy sector. Presentations will showcase applied innovations that accelerate access to engineering knowledge, optimize asset performance, and streamline decision-making from the field to the control room. Topics will include GenAI-powered systems for technical document interpretation, predictive maintenance, workflow automation, and operational intelligence in upstream and midstream environments.
Session Chairpersons
Dingzhou Cao - Devon Energy Corporation
Hector Klie - DeepCast
  • 0830-0855 228077
    Flow Rate And AICD Status Prediction From Distributed Acoustic Sensing Data Using Machine Learning
    R.G. Hashish, B. Spivey, K. Walker, B. Campbell, B. Seabrook, ExxonMobil Upstream Research Co.
  • 0855-0920 227916
    Hybrid AI Models For Wet Gas Compressor Modelling
    G. Draskovic, N. Nguyen, B. Torkildsen, N. Butin, SLB
  • 0920-0945 227888
    Detecting Pipeline Leaks Using A Novel Data-driven Statistical Methodology With Earth Mover's Distance
    C. Johnston, Pipewise Technology Ltd.
  • 1015-1040 227906
    Modular Framework Integrating Large Language Models With Drilling Hazard Detection Systems To Provide Operational Context-Informed Interpretations And Recommended Actions
    S. Suhail, T.S. Robinson, O.E. Revheim, P. Bekkeheien, Exebenus
  • 1040-1105 228135
    How To Leverage Agentic Ai And Knowledge Graphs To Enhance Overall Equipment Efficiency (oee)
    A. Jain, P. Rai, N. Sengar, A. Anand, Baker Hughes
  • 1105-1130 227885
    Ai-driven Geology: Vision Rags Decoding Legacy Report Using Colpali
    G. Chirila, Saudi Aramco; M. Al-Sadah, ARAMCO Services Company; B. Hungund, R. Alsubaie, Halliburton
  • Alternate 227990
    Machine Learning Application For Accelerating Fracture Network Analysis: A Geothermal Use Case
    G. Liu, U.S. Department of Energy National Energy Technology Laboratory
  • Alternate 228268
    Deep Natural Language Processing For Automatic Root Cause Analysis Of Non-productive Time Events In Drilling Reports
    H. B. Abdulkhaleq, M. Karnot, Rumaila Operating Organization
  • Alternate 228097
    Building "Energy LLM": A Domain-specific Large Language Model Trained On SPE Content
    J. Eckroth, J. Boden, L. Hough, H. Gatewood, S. Gipson, i2k Connect; R.M. Al-Harbi, Saudi Aramco

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