The framework of the fracture network in the subsurface using data-driven models and mathematical models

  • Amanbek, Yerlan (PI)
  • Merembayev, Timur (Other Faculty/Researcher)
  • Omirbekov, Sagyn (Other Faculty/Researcher)
  • Kurmanbek, Bakytzhan (Other Faculty/Researcher)
  • Kazidenov, Daniyar (Other Faculty/Researcher)

Project: MES RK

Conference contribution

Search results

  • 2023

    Natural Fracture Network Model Using Machine Learning Approach

    Merembayev, T. & Amanbek, Y., 2023, Computational Science and Its Applications – ICCSA 2023 Workshops, Proceedings. Gervasi, O., Murgante, B., Scorza, F., Rocha, A. M. A. C., Garau, C., Karaca, Y. & Torre, C. M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 384-397 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14107 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access