Department Geoenergy

Organisational unit: Departments and Institutes

Research output

  1. 2023
  2. Published
  3. Published
  4. Published
  5. Published

    Simultaneous interpretation of SCAL data with different degrees of freedom and uncertainty analysis

    Amrollahinasab Mahdiabad, O., Azizmohammadi, S. & Ott, H., Jan 2023, In: Computers and geotechnics. 153.2022, January, 11 p., 105074.

    Research output: Contribution to journalArticleResearchpeer-review

  6. E-pub ahead of print

    Forced imbibition and uncertainty modeling using the morphological method

    Arnold, P., Dragovits, M., Linden, S., Hinz, C. & Ott, H., 15 Jan 2023, (E-pub ahead of print) In: Advances in Water Resources. 172.2023, February, 11 p., 104381.

    Research output: Contribution to journalArticleResearchpeer-review

  7. Published

    A Reinforcement Learning Approach for Real-Time Autonomous Decision-Making in Well Construction

    Keshavarz, S., Vita, P., Rückert, E., Ortner, R. & Thonhauser, G., 19 Jan 2023, SPE AI Symposium 2023: Leveraging Artificial Intelligence to Shape the Future of the Energy Industry. (Society of Petroleum Engineers - SPE Symposium: Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, AIS 2023).

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

  8. E-pub ahead of print

    Large-scale underground hydrogen storage: Integrated modeling of reservoir-wellbore system

    Abdellatif, M., Hashemi, M. & Azizmohammadi, S., 24 Feb 2023, (E-pub ahead of print) In: International Journal of Hydrogen Energy . 48.2023, 50, p. 19160-19171 12 p.

    Research output: Contribution to journalArticleResearchpeer-review

  9. Published

    Interactions of Hydraulic Fractures With Grain Boundary Discontinuities in the Near Wellbore Region

    Yoshioka, K., Katou, M., Tamura, K., Arima, Y., Ito, Y., Chen, Y. & Ishida, T., 2 Mar 2023, In: Journal of geophysical research. 128.2023, 3, 22 p., e2022JB024509.

    Research output: Contribution to journalArticleResearchpeer-review

  10. Published

    Application of machine learning to determine the shear stress and filtration loss properties of nano-based drilling fluid

    Cai Ning, Y., Ridha, S., Umer Ilyas, S., Krishna, S., Dzulkarnain, I. & Abdurraham, M., Apr 2023, In: Journal of Petroleum Exploration and Production Technology. 13.2023, April, p. 1031-1052 22 p.

    Research output: Contribution to journalArticleResearchpeer-review

  11. Published