Chair of Drilling and Completion Engineering (590)
Organisational unit: Chair
151 - 160 out of 365Page size: 10
Research output
- Published
Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration
Jason, C., Umer Ilyas, S., Ridha, S., Sehar, U., Alsaady, M. & Krishna, S., 2024, Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration. p. 469-477 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Hydraulic Subsurface Pump kinetic CFD Simulation
Jax, G., Langbauer, C. & Vita, P., 6 Nov 2017.Research output: Contribution to conference › Poster › Research
- Published
Hydraulic Subsurface Pump Numerical Study
Jax, G., Langbauer, C. & Vita, P., 19 Apr 2018, DGMK - Tagungsband 2018. p. 217 226 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Dynamic Load Evaluation of Large Dimensioned Casing Strings at Primary Cementing
Jedlitschka, V., 2007Research output: Thesis › Master's Thesis
- Published
Optimum Well Design and Risk Mitigation for Efficient Use of Geothermal Energy in South East Europe Case Study
Juricic, T., 2018Research output: Thesis › Master's Thesis
- Published
Design of a quality control system for logging while drilling data in horizontal wells
Karimov, A., 2019Research output: Thesis › Master's Thesis
- 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
- 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
- Published
Drilling Performance Analysis by Means of Real-Time Data and Offset Study for an Actual Well Onshore Croatia
Kesner, J., 2019Research output: Thesis › Master's Thesis
