logo
calendar1 Aprel 2026
view37
Main language:Uzbek

Applying Linear Regression for Predicting Production Rates in Natural Gas Refinery Plant

Field of Science:Artificial IntelligenceComputational Theory and MathematicsComputer Graphics and Computer-Aided DesignComputer Networks and CommunicationsComputer Science (miscellaneous)Information SystemsSignal ProcessingSoftware
National field of science (HAC):05.01.01 — Engineering geometry and computer graphics. Audio and video technologies05.01.02 — Systems analysis, control and information processing05.01.03 — Theoretical foundations of informatics05.01.04 — Mathematical and software support of computers, complexes and computer networks05.01.05 — Information protection methods and systems. Information security05.02.03 — Technological machines. Robots, mechatronics and robotic systems05.01.08 — Automation and control of technological processes and productions05.01.09 — Document studies. Archival science. Library science05.01.10 — Information retrieval systems and processes05.01.11 — Digital technologies and artificial intelligence05.04.01 — Telecommunication and computer systems, telecommunication networks and devices. Information distribution05.04.02 — Radio engineering, radionavigation, radiolocation and television systems and devices. Mobile and fiber-optic communication systems08.00.14 — Information systems and technologies in economics08.00.16 — Digital economy and international digital integration11.00.07 — Geoinformatics21.01.09 — Military command and communication systems21.02.12 — Military cybernetics, systems analysis, operations research, modeling of combat operations and military systems (including Armed Forces branches, arms of service and special units)05.01.06 — Elements and devices of computer engineering and control systems05.01.07 — Mathematical modeling. Numerical methods and software packages10.00.11 — Language theory. Applied and computational linguistics13.00.06 — Theory and methods of e-learning (by education fields and levels)21.02.13 — Informatics and computer technologies in military affairs
pdf

26._Mirsoatov_F.S.__Naz....pdf

PDF

Scientific electronic journal "Digital Economy"

Scientific electronic journal "Digital Economy"

Publish Articlesee more

ARTICLE ANNOTATION

quote
The petroleum sector faces numerous challenges related to data management, processing, and analysis due to the vast amount of information generated across its global and distributed operations. Recently, Artificial Intelligence and Machine Learning have gained traction as powerful tools to address these challenges. This paper examines the prospects of applying machine learning, specifically the use of Linear Regression to predict and forecast production natural gas plant rates.

AUTHORS

F.Mirsoatov

O`ZBEKISTON RESPUBLIKASI RAQAMLI TEXNOLOGIYALAR VAZIRLIGI HUZURIDAGI SUN`IY INTELLEKT VA RAQAMLI IQTISODIYOTNI RIVOJLANTIRISH MARKAZI

Z.Nazarova

O`ZBEKISTON RESPUBLIKASI RAQAMLI TEXNOLOGIYALAR VAZIRLIGI HUZURIDAGI SUN`IY INTELLEKT VA RAQAMLI IQTISODIYOTNI RIVOJLANTIRISH MARKAZI

Tags

# digitalization# artificial intelligence# machine learning# linear regression# petroleum sector# data management# gas refinery

SIMILAR ARTICLES

OTHER ARTICLES IN THIS JOURNAL

Rate Article

0
0 ratings
5
4
3
2
1

Article Identifiers

ROI:

https://eroi.uz/11.142/A026-059196

DOI:

Not Available

References

Indolia, S., Goswami, A. K., Mishra, S., & Asopa, P. (2018). Conceptual understanding of Convolutional Neural Network- a deep learning approach. Procedia Computer Science, 132, 679–688. https://doi.org/10.1016/j.procs.2018.05.069

Zolotukhin, A. B., & Gayubov, A. T. (2019). Machine learning in reservoir permeability prediction and modelling of fluid flow in porous media. IOP Conference Series Materials Science and Engineering, 700(1), 012023. https://doi.org/10.1088/1757-899x/700/1/012023

Valiyev, M., Razak, S. M., & Jafarpour, B. (2021). Deep learning-based multiresolution parameterization for spatially adaptive model updating. Society of Petroleum Engineers. https://doi.org/10.2118/212167-MS

Maulud, D., & Abdulazeez, A. M. (2020). A review on Linear Regression comprehensive in Machine Learning. Journal of Applied Science and Technology Trends, 1(4), 140–147. https://doi.org/10.38094/jastt1457

Bishop, C. M., & Bishop, H. (n.d.). Deep Learning. https://doi.org/10.1007/978-3-031-45464

Uzbekneftegaz JSC. Open data: Gas processing dataset. Available at: https://ung.uz/open-data/18/sub/42/4

Sircar, A., Yadav, K., Rayavarapu, K., Bist, N., & Oza, H. (2021b). Application of machine learning and artificial intelligence in oil and gas industry. Petroleum Research, 6(4), 379–391. https://doi.org/10.1016/j.ptlrs.2021.05.009

Ahmad, R. W., Salah, K., Jayaraman, R., Yaqoob, I., & Omar, M. (2022). Blockchain in oil and gas industry: Applications, challenges, and future trends. Technology in Society, 68, 101941. https://doi.org/10.1016/j.techsoc.2022.101941

Al-Rbeawi, S. (2023). A review of modern approaches of digitalization in oil and gas industry. Upstream Oil and Gas Technology, 11, 100098. https://doi.org/10.1016/j.upstre.2023.100098