KNOWLEDGE-ORIENTED DECISION-MAKING METHODS IN SIMULATIONS OF TECHNOLOGICAL PROCESS SIMULATION
DOI:
https://doi.org/10.31471/1993-9981-2020-2(45)-132-145Keywords:
parameterization of drilling, model, precedent, knowledge base, computer modeling, drilling simulators.Abstract
The article presents the results of research in the field of simulation of drilling processes using modern computer modeling. The main parameters of the drilling process are determined as theoretical considerations aimed at introducing concepts related to simulation modeling and computer modeling in drilling. The analysis of the models used in the simulation of drilling processes is carried out. The basic characteristics of the simulator modeling are highlighted, which provides a holistic perception of technological processes, as well as any degree of their detailing. The main methods of modeling used in the development of automated control systems and simulators of industrial installations, ways of developing their software and some aspects of creating effective software and computer systems are presented. Further, a review of the essence of technological simulators is carried out, from a technical point of view, the current state of training systems for training operators of technological processes is highlighted. The differences between simulators and other teaching aids and the specifics of simulators for technical processes are presented. The characteristic features and prospects of simulator building in various industries are briefly described. The compulsory components of the simulators and the quality criteria of the simulators are determined. A study of the existing technical solutions for systems of the "Drilling simulators" class was carried out. Conclusions are made regarding the practical aspects of using modern engineering solutions for drilling simulators. The advantages are determined as a result of using simulators in various types of operational-tactical exercises, as the main form of improving the optimization of drilling control both for production tasks and training tasks. Particular emphasis is placed on the Drillsimm5000 simulator, which is used in the training of drilling specialists at the Ivano-Frankivsk Technical National University of Oil and Gas. From the standpoint of various services of the enterprise interested in purchasing simulators, the potential benefits of computer training and the tasks that need to be solved for the successful implementation of simulators are analyzed, problems associated with their implementation are presented.
Downloads
References
Barbosa, Luis Felipe et al. “Machine learning methods applied to drilling rate of penetration prediction and optimization - A review.” Journal of Petroleum Science and Engineering 183 (2019): 106332.
Bello, O. et al. “Application of Artificial Intelligence Techniques in Drilling System Design and Operations: A State of the Art Review and Future Research Pathways.” (2016).
Chernikov A.D., Eremin N.A., Stolyarov V.E., Sboev A.G., Semenova-Chashchina O.K., Fitsner L.K. (2020). Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions. Georesursy = Georesources, 22(3), pp. 87–96. DOI: https://doi.org/10.18599/grs.2020.3.87-96
Chiranth Hegde,Hugh Daigle,Harry Millwater,Ken Gray Analysis of rate of penetration (ROP) prediction in drilling using physics-based and data-driven models. Publication: Journal of Petroleum Science and Engineering Publisher: Elsevier. Date: November 2017.
DrillSIM:5000 Classic [Електронний ресурс] Retrieved from: https://www.drillingsystems.com/product/drillsim5000/.
Hegde, C. et al. “Fully coupled end-to-end drilling optimization model using machine learning.” Journal of Petroleum Science and Engineering 186 (2020): 106681.
Hegde, Chiranth et al. “Performance Comparison of Algorithms for Real-Time Rate-of-Penetration Optimization in Drilling Using Data-Driven Models.” Spe Journal 23 (2018): 1706-1722.
Pollock, J. et al. “Machine Learning for Improved Directional Drilling.” (2018).
Sheketa V. Case-based modelling of data and knowledge // Sheketa V., Chesanovskyy M., Styslo T., Romanyshyn Y., Poteriailo L. // 14th International Scientific and Practical Conference “Mathematical and Imitational Models of Systems - MODS 2019”. Chernigiv. 2019. pp.177–181.
Stanisław DubielBarbara Uliasz-Misiak Analiza decyzji technologicznych podejmowanych w zakresie zarządzania złożem węglowodorów przy dowiercaniu, opróbowaniu i udostępnianiu złóż Przegląd Górniczy 2014; 70 (12) : 106-113; (PL)
Yanlong Li,Lei She,Lifeng Wen,Qiang Zhang Sensitivity analysis of drilling parameters in rock rotary drilling process based on orthogonal test method. Publication: Engineering Geology. Publisher: Elsevier. Date: Available online 5 March 2020.
Biletskyi V., Serhieiev P., Fyk M., Kozyrets S. Modeliuvannia v naftohazovii promyslovosti [Modeling in the oil and gas industry] Geotechnologies Journal homepage: http://library.kpi.kharkov.ua/ Volume 1 (2018), pp. 86-98.
Burenie (dobycha, transportirovka, pererabotka) [Yelektronniy resurs] // Tekhnicheskaya biblioteka transportirovka i khranenie. 2013 Retrieved from: https://neftegaz.ru/tech-library/burenie/141992-burenie-1/ (in Russ.).
Volkova M. M., Manurova R. A., Shaydullina D. N. Primenenie virtualnykh trenazherov dlya obucheniya spetsialistov neftegazovoy otrasli [Using virtual simulators in training oil and gas professionals] Vestnik tekhnologicheskogo universiteta. 2019.; T.22,4 115 UDK 66-9 (in Russ.).
Hobyr L.M. Ymovirnisna otsinka rezultativ interpretatsii danykh ta parametriv heofizychnykh doslidzhen / Hobyr L.M., Vovk R.B., Poteriailo L.O., Sheketa V.I. // Vseukrainskyi shchokvartalnyi naukovo-tekhnichnyi zhurnal “Rozvidka ta rozrobka naftovykh i hazovykh rodovyshch”. 2018;3(68).p. 46-59(in Ukr.).
Horbiichuk M.I. Optymizatsii protsesu burinnia hlybokykh sverdlovyn / M.I.Horbiichuk, H.N.Sementsov. – Ivano-Frankivsk: Fakel, 2003, 493 p. (in Ukr.)
Grib P.S. Tsifrovye trenazhernye kompleksy kak sredstvo optimizatsii bureniya i ekspluatatsii skvazhin Inzhenernaya praktika 08.2019 (in Russ.).
Darin A. A. Nekotorye aspekty modelirovaniya pri sozdanii interaktivnykh sredstv obucheniya operatorov Tip: statya v sbornike trudov konferentsii. 2020 pp: 116-118 (in Russ.).
Dozortsev V. M., Kneller D. V., Levit M. Yu. O probleme adekvatnosti trenazhernykh modeley tekhnologicheskikh protsessov//Trudy mezhdunar. konferentsii «Identifikatsiya sistem i zadachi upravleniya (SICPRO’2000)». Moskow: 2000. p. 51–61 (in Russ.).
Mukhametgaliev I.D., Agzamov Z.V. Razrabotka cheloveko-mashinnogo interfeysa trenazhera naklonno-napravlennogo bureniya «Molodoy uchenyy» 27(317), 07.2020 (in Russ.).
Myslyuk M.A., Stefurak R.I., Rybchich I.I., Yu.M.Vasylyuk Sovershenstvovanie tekhnologii obrabotki trekhsharoshkovykh dolot pri rotornom burenii skvazhin/ Moskow: OAO VNIIOENG, 2005. – 212 p. (in Russ.).
Poteriailo L.O. Modeliuvannia imitatsionnoi modeli keruvannia protsesamy burinnia na osnovi pretsedentiv /Poteriailo L.O. , Protsiuk V.V. ,. Kravtsiv K.I// Vseukrainskoi nauk.-prakt. konf. «Informatsiini tekhnolohii v osviti, tekhnitsi ta promyslovosti » - ITOTP-2020 -Ivano-Frankivsk, 8 zhovtnia 2020.
Poteriailo L.O. Vykorystannia CBR pry realizatsii inzhenernykh rishen system klasu «Burovi trenazhery» /Poteriailo L.O. , Protsiuk V.V. ,. Kravtsiv K.I//VI Mizhnar. nauk.-tekhn. konf. «Kompiuterne modeliuvannia ta optymizatsiia skladnykh system», Dnipro, 4.11.2020. – Dnipro, 2020. (in Ukr.)
Razrabotka protsessa prinyatiya resheniy pri modelirovanii i proektirovanii mestorozhdeniy uglevodorodov na osnove vyvoda po pretsedentam. Novye informatsionnye tekhnologii v neftegazovoy otrasli i obrazovanii: materialy VIII Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii; otv. red. O. N. Kuzyakov. Tyumen: TIU, 2019. 324 p. (in Russ.).
Funktsionalnye vozmozhnosti polnomasshtabnogo burovogo trenazhera DrillSim-5000 [Yelektronniy resurs] – Retrieved from: https://www.gubkin.ru/faculty/oil_and_gas_development/chairs_and_departments/drill_center/DrillSim-5000.php. (in Russ.).
Chesanovskyi M.S. Osoblyvosti kontroliu parametriv protsesu burinnia v konteksti pidtrymky pryiniattia relevantnykh rishen / Chesanovskyi M.S., Sheketa V.I., Protsiuk_V.V. // Vseukrainskyi shchokvartalnyi naukovo-tekhnichnyi zhurnal “Rozvidka ta rozrobka naftovykh i hazovykh rodovyshch”. 2018(in Ukr.).
Sheketa V.I. Formalno-alhorytmichna implementatsiia modelei keisiv danykh pro protses burinnia / V.I. Sheketa, M.S. Chesanovskyi, L.O. Poteriailo // Kompiuterne modeliuvannia ta optymizatsiia skladnykh system: IV Mizhnar. nauk.-tekhn. konf., Dnipro, 1-2 lystopada 2018r. Dnipro, 2018. p. 312-314 (in Ukr.).
Efendiev, Aliev S.A., Sarbopeeva M.D., Agaeva K.K., Kirisenko O.G. Prinyatie resheniy pri vybore dolot i rezhimnykh parametrov bureniya v zavisimosti ot kharaktera iskhodnoy informatsii g.m., geoіnformatika, 2016, 3 (59) (in Russ.).
.png)
