Sahar Keshavarz
1 - 4 out of 4Page size: 10
Research output
- 2024
- Published
Smart predictions of petrophysical formation pore pressure via robust data-driven intelligent models
Krishna, S., Irfan, S. A., Keshavarz, S., Thonhauser, G. & Umer Ilyas, S., 24 Jul 2024, In: Multiscale and multidisciplinary modeling, experiments and design. 7.2024, 6, p. 5611-5630 20 p.Research output: Contribution to journal › Article › Research › peer-review
- E-pub ahead of print
Evaluating Multi-target Regression Framework for Dynamic Condition Prediction in Wellbore
Keshavarz, S., Elmgerbi, A., Vita, P. & Thonhauser, G., 23 Apr 2024, (E-pub ahead of print) In: The Arabian journal for science and engineering. 49.2024, June, p. 8953-8982 30 p.Research output: Contribution to journal › Article › Research › peer-review
- Published
Deep reinforcement learning algorithm for wellbore cleaning across drilling operation
Keshavarz, S., Elmgerbi, A. & Thonhauser, G., 25 Mar 2024, Fourth EAGE Digitalization Conference & Exhibition, Mar 2024, Volume 2024, p.1 - 5. Vol. 2024.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- 2023
- 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 proceeding › Conference contribution
