Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Oney Erge"'
Publikováno v:
Energies, Vol 15, Iss 16, p 5776 (2022)
Well construction operations require continuous complex decision-making and multi-step action planning. Action selection at every step demands a careful evaluation of the vast action space, while guided by long-term objectives and desired outcomes. C
Externí odkaz:
https://doaj.org/article/7f98418c26754a6bbe63ec8eeda0d67b
Publikováno v:
Energies, Vol 14, Iss 5, p 1484 (2021)
Effectively transporting drilled cuttings to the surface is a vital part of the well construction process. Usually, mechanistic models are used to estimate the cuttings concentration during drilling. Based on the results from these model, operational
Externí odkaz:
https://doaj.org/article/9fac05e0ba5f4632b14ef57b2e94a338
Publikováno v:
Volume 10: Petroleum Technology.
In this study, a deep learning model is proposed that can accurately predict the rate of penetration during geothermal or oil and gas well construction operations. Also, a genetic algorithm is applied and used together with the deep learning model to
Publikováno v:
Volume 10: Petroleum Technology.
Drilling practice has been evolving parallel to the developments in the oil and gas industry. Current supply and demand for oil and gas dictate search for hydrocarbons either at much deeper and hard-to-reach fields, or at unconventional fields, both
Autor:
Oney Erge, Eric van Oort
Publikováno v:
Day 5 Fri, March 12, 2021.
During drilling operations, it is common to see pump pressure spikes when flow is initiated, including after a connection or after a prolonged break in drilling operations. It is important to be able to predict the magnitude of such pressure spikes t
Autor:
Charles Bose, Oney Erge, Sercan Gul, Luky Hendraningrat, Muhammed Jahangir, Bao Jia, Fatma Sebnem Küçük, Kamil Küçük, Hon Chung Lau, Shidong Li, Dupeng Liu, Adil Ozdemir, Varun Rai, Rahul Ranjith, Alperen Sahinoglu, Javid Shiriyev, Vivek Singhal, Cenk Temizel, Ole Torsæter, Hongsheng Wang, Sai Wang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3835a250f6c03a4c0033e654905dde5
https://doi.org/10.1016/b978-0-12-824380-0.00014-1
https://doi.org/10.1016/b978-0-12-824380-0.00014-1
Publikováno v:
Sustainable Materials for Oil and Gas Applications ISBN: 9780128243800
The oil and gas well construction is often associated with the unknowns and uncertainties while executing the operations. Because, while drilling, the drilling bit is under the ground where the information is usually gained through interpreting sever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7affd1e7bd880a0d16af6aea84ff5a0a
https://doi.org/10.1016/b978-0-12-824380-0.00004-9
https://doi.org/10.1016/b978-0-12-824380-0.00004-9
Autor:
Eric van Oort, Oney Erge
Publikováno v:
Scopus-Elsevier
One of the primary functions of the drilling fluid is to transport cuttings from the bit to the surface. This transport is mainly a function of fluid properties (rheology and density), pump rate, wellbore trajectory and geometry, drillstring rotation
Publikováno v:
Scopus-Elsevier
Optimum well construction operations require frequent and accurate measurements of drilling fluid properties. Optimized hydraulics, hole cleaning and well control requires proper management and characterization of fluid rheology and density. Currentl
Autor:
Oney Erge, Eric van Oort
Publikováno v:
Journal of Natural Gas Science and Engineering. 97:104348
This study presents a hybrid modeling approach combining physics-based and data-driven models for improved standpipe pressure prediction during well constructing. The proposed approach provides a more robust and accurate model that mitigates some of