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Generative Artificial intelligence and advanced analytics on facility and asset management in oil and gas industry

Tuesday, 24 September
231 - 232
Technical Session
This session consists of two parts. Part 1 focuses on the forefront of large language model applications in the petroleum industry, exploring this new horizon of generative AI adoption. Part 2 introduces innovative advanced analytics methods for field facility optimization, showcasing digital advancement in asset management.
Session Chairpersons
Zhenyu Guo - Xecta Digital Labs
Youli Mao - Halliburton
  • 0830-0855 220810
    Developing Large Language Model (llm) Framework To Extract Oil And Gas Field Data From Literature
    Z. Chen, Stanford University; W. Long, University of Pittsburgh; A.R. Brandt, H. Tang, R. Zhong, X. Yang, Stanford University
  • 0855-0920 221083
    Textual Data Augmentation For NER In Geosciences With LLMs
    E. Maze, R. Farahbakhsh, P. Barrallon, P. JALLAIS, TotalEnergies SE
  • 0920-0945 220921
    Damage Classification Of Oil & Gas Equipment Components Using Siamese Networks
    A. Sirothia, G. Nair, R. Pandya, ExxonMobil Services & Technology Pvt Ltd
  • 1015-1040 221022
    Leveraging Large Language Models For Cost Management And Supply Chain Optimization
    M. Shahini, Y. Wang, M. Roeder, S. Coffman, B. Hu, S. Pethe, P. Howard, J. Arnwine, H. Wasserman, ConocoPhillips
  • 1040-1105 220932
    Success Cases And Lessons Learned After 20 Years Of Oilfield Digitalization Efforts
    L. Saputelli, Abu Dhabi National Oil Company
  • 1105-1130 220979
    An Automated Workflow For Condition Monitoring Of Centrifugal Compressors Using A Combined Data-driven And Physics-based Approach
    C.S. Santiago, H. Abbas, SLB; P. Thangamani, SLB Middle East
  • Alternate 220918
    Examining Oil And Gas Companies' Stated Strategy: A Machine Learning Analysis Of 10k Statements
    S. Singh, University of Texas at San Antonio; V. Mittal, Jones Graduate School of Business, Rice University; A. Parasnis, Carnegie Vanguard High School; S. Seaton, Society of Petroleum Engineers
  • Alternate 220712
    Application Of Large Language Models For Analysis Of Textual Data From The Oil & Gas Industry
    P.S. Rathore, G. Nair, A. Srivastava, Halliburton
  • Alternate 220833
    Preliminary Research On Applications Of Large Language Models In e&P Industry
    X. Zhou, Research Institute of Petroleum Exploration and Development of PetroChina; X. Jing, Digital and Information Department of PetroChina; W. Wu, Research Institute of Petroleum Exploration and Development of PetroChina; G. Gao, Yangtze University

Prepare for an Unforgettable Opening Session!

Through an insightful discussion, we aim to provide a comprehensive understanding of the past, present, and future of innovation within the Oil & Gas industry, inspiring a new era of energy professionals committed to shaping a resilient and sustainable energy landscape.

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