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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, R. Gadrbouh, Viridien
  • 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 Prioritization Through Machine Learning
    M. Fraguio, Interfaces SA; M.L. Maestri, Fractal Science
  • 1210-1235 231671
    Comparative Analysis of Classical Machine Learning and Deep Learning Models forMulti-Class Anomaly Detection in Petroleum Wells Using the 3W Dataset
    E. Soares, R.G. Pires, M. Silva Santana, Universidade Estadual Paulista; D. Colombo, A. Abrego, Petrobras; J. Papa, Universidade Estadual Paulista

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