Features of the development of the digital twin drilling rig information system project based on big data technologies, machine learning, and the Internet of Things

Peter Boldyrev

Abstract


The article considers a schematic diagram of the development of an information system for a digital twin of a drilling rig based on elements of the fourth industrial revolution ("Industry 4.0"). Subsystems using artificial intelligence algorithms, Internet of Things technology (IoT-InternetofThings), big data (BigData) are investigated. The interrelation of subsystems with the solution of information system tasks is analyzed. The characteristics of the hardware are described, as well as ways of storing and presenting information system data.Special attention is paid to modeling the types of information requests and data transmission methods. A list of technical and software tools is described, with the help of which there is a fundamental possibility of implementing the project. Numerical metrics of parameters are given, on the basis of which quantitative and qualitative characteristics of the information system project are predicted.

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References


BYKOVA V.N., KIM E., GABDULShAEV M.R., MUSIENKO V.O., OGURCOV A.O., TUROVSKAJa E.A. Primenenie cifrovogo dvojnika v neftegazovoj otrasli // Aktual'nye problemy nefti i gaza. 2020. Vyp. 1(28). S. https://doi.org/10.29222/ipng.2078-5712.2020-28.art8

EREMINN.A.,EREMINAl. N. Cifrovoj dvojnik v neftegazovom proizvodstve // Neft'. Gaz. Novacii;2018; #12;S.14–17

ZOLOTAREV O.V. Primenenie cifrovyh dvojnikov v gornodobyvajushhej promyshlennosti: cifrovoj dvojnik mel'nicy izmel'chenija. – Mezhdunarodnyj forum SEYMARTEC Mining. Jeffektivnost' i bezopasnost' gornodobyvajushhej promyshlennosti, Cheljabinsk, 2019.

KOKOREV D.S., JuRIN A. A. Cifrovye dvojniki: ponjatie, tipy i preimushhestva dlja biznesa: [Jelektronnyj resurs]:URL: https://cyberleninka.ru/article/n/tsifrovye-dvoyniki-ponyatie-tipy-i-preimuschestva-dlya-biznesa.

LEONT''EVA I.N. Tehnologija «cifrovoj dvojnik» kak instrument integracii mezhdu vuzami i promyshlennymi predprijatijami. PRONEFT''. Professional'no o nefti.2022;7(3): 119-128.https://doi.org/10.51890/2587-7399-2022-7-3-119-128

MARKOVA N. I., UZhEGOVA A. M. Cifrovaja real'nost': ot modeli k obrazu // Voprosy upravlenija. 2019. # 2 (38). S. 45—50

MATVEEVA A.V. Bol'shie dannye kak issledovatel'skaja tehnologija: vozmozhnosti i ogranichenija primenenija v sovremennoj upravlencheskoj // Obshhestvo: sociologija, psihologija, pedagogika. –2021. – # 12. – S. 94–103.

Iskusstvennyj intellekt (II) [Jelektronnyj resurs]: – Rezhim dostupa: https://www.oracle.com/cis/artificial-intelligence/

Svedenija o modeljah dvojnikov i ih opredelenii v AzureDigitalTwins [Jelektronnyj resurs]: – Rezhim dostupa: https://learn.microsoft.com/ru-ru/azure/digital-twins/concepts-models

SOSFENOV D.A. Cifrovoj dvojnik: istorija vozniknovenija i perspektivy razvitija // Intellekt. Innovacii. Investicii. – 2023. – #4. – S. 35-43, https://doi.org/10.25198/2077-7175-2023-4-35.

Cifrovoj dvojnik [Jelektronnyj resurs]: – Rezhim dostupa: https://hes.mephi.ru/?page_id=18708

ChERNIKOV A.D., EREMIN N.A., STOLJaROV V.E., SBOEV A.G., SEMENOVA-ChAShhINA O.K., FICNER L.K. (2020). Primenenie metodov iskusstvennogo intellekta dlja vyjavlenija i prognozirovanija oslozhnenij pri stroitel'stve neftjanyh i gazovyh skvazhin: problemy i osnovnye napravlenija reshenija. Georesursy, 22(3), s. 87–96.DOI:https://doi.org/10.18599/grs2020.3.87-96

Chto takoe tehnologija cifrovogo dvojnika? [Jelektronnyj resurs]: – Rezhim dostupa: https://aws.amazon.com/ru/what-is/digital-twin/

BHOWMIK S. Digital twin of subsea pipelines: conceptual design integrating IoT, machine learning and data analytics // Offshore Technology Conference. 6–9 May 2019; Proceedings. Houston, Texas, USA, 2019. Paper OTC-29455-MS. 9 p

BÖSCHEN S., HEINRICH C., ROSEN R. Next Generation Digital Twin // Proceedings of TMCE 2018, Las Palmas de Gran Canaria, Spain, 7-11 May, 2018.

Digital Twins for Industrial Applications: An Industrial Internet Consortium White Paper. Version 1. 2020-02-18. 19 p.

GRIEVES, M.Virtually Intelligent Product Systems: Digital and Physical Twins, in Complex Systems Engineering: Theory and Practice, S. Flumerfelt, et al., Editors. 2019, American Institute of Aeronautics and Astronautics. p. 175-200

MICHAEL G. KAPTEYN, JACOB V.R. PRETORIUS, AND KAREN E. WILLCOX. A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale[Jelektronnyjresurs]: https://kiwi.oden.utexas.edu/papers/Digital-twin-scale-graphical-model-Kapteyn-Willcox.pdf

NOSHATI, C.L. & SCHUBERT, J.J. The Role of Machine Learning in Drilling Operations. A Review, in Society of Petroleum Engineers. 2018[Jelektronnyjresurs]: https://doi.org/10.2118/191823-18ERM-MS

SINGH, K., YALAMARTY, S.S., KAMYAB, M., & CHEATHAM, C. Cloud-Based ROP Prediction and Optimization in Real Time Using Supervised Machine Learning, Unconventional Resources Technology Conference. 2019[Jelektronnyjresurs]: https://doi.org/10.15530/urtec-2019-343


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