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Concepts, Data and Algorithms - Exploring Integrated Approaches in Reservoir Characterization

Tuesday, 17 October
Room 217 D
Technical Session
From Data-driven to deep learning, concepts, data and algorithms, this session which explore approaches in reservoir characterization.
  • 0830-0855 215019
    Seismic Reflectivity Inversion Using A Semi-supervised Learning Approach
    A. Abd Rahman, PETRONAS; A.M. El Sheikh, Heriot-Watt University; M. Jaya, PETRONAS
  • 0855-0920 215133
    Causal Inference for the Characterization of Microseismic Events Induced by Hydraulic Fracturing
    O. Rojas Conde, S. Misra, R. Liu, Texas A&M University
  • 0920-0945 215072
    Deep-learning-based Approach For Optimizing Infill Well Placement
    P. Zhang, T. Gao, B. Fu, R. Li, Variables Intelligence Corporation
  • 1015-1040 214792
    Modeling Heterogeneity Of Glacial Reservoir Using Geostatistical Approach: A Case Study, Southwest Libya.
    F.A. Bergigh, Akakus Oil Operations Libya; W.S. Meddaugh, Midwestern State University; T.M. Alkhemri, Akakus Oil Operations Libya
  • 1040-1105 214789
    Rock Physics Modeling Of Hydrogen-bearing Sandstone: Implications For Natural Hydrogen Exploration And Storage
    M. Ahmad Fuad, H. Zhao, M. Jaya, E. Jones Jr, PETRONAS RESEARCH SDN BHD

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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