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Data Science Innovations for Oilfield Monitoring and Decision-Making

Thursday, 11 June
Louvre I
Technical Session
This session explores the latest advances in data science and digital technologies for oilfield operations, featuring practical applications of machine learning, AI agent systems, and open data strategies. Presentations cover natural language search in geoscience, real-time anomaly detection for well integrity, automated identification of perforation targets, and collaborative approaches to building public datasets for oil well monitoring. Designed for engineers, researchers, and students, the session delivers actionable insights for enhancing operational safety, efficiency, and decision-making in the petroleum industry.
Chairperson
Raquel Correa - Schlumberger WTA Malaysia Sdn Bhd
Emilio Coutinho - Petrobras
  • 1055-1120 231650
    Empowering Natural Language Search In Geoscience With An Agentic System And Knowledge Graph
    J. Richardson, Viridien; R. Gadrbouh, CGG
  • 1120-1145 231631
    Data-driven Strategies For Predicting Anomalies Impacting Offshore Well Integrity: Design And Implementation
    P.E. Aranha, PETROBRAS; N. Policarpo, M.A. Sampaio, Universidade De Sao Paulo
  • 1145-1210 231646
    Mass Identification Of Potencial Perforation Targets And Workover Priorization Through Machine Learning
    M. Fraguio, Interfaces SA; M.L. Maestri, Fractal Science
  • 1210-1235 231671
    Classical And Deep Learning Models For Anomaly Detection In Oil Wells
    E. Soares, R.G. Pires, M. Silva Santana, Universidade Estadual Paulista; D. Colombo, A. Abrego, Petrobras; J. Papa, Universidade Estadual Paulista
  • Alternate 231655
    The 3W Project And Its Approach To Unlock Data-driven Solutions For Oil Wells Monitoring
    R. Vargas, C. Lima, Petrobras

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