Skip to main content
Log in

Intellectual technologies in the management of oil fields

  • Published:
Scientific and Technical Information Processing Aims and scope

Abstract

This work is aimed at developing new approaches and at improvement of control of oil-producing wells and an oilfield as a whole based on artificial intelligence methods. A three-tier system of intelligent oilfield control that ensures optimization of oil production and the operation of equipment is proposed; the essential features of the applied artificial intelligence tools that are required for implementation at all levels are described. The concept and the proposals that are made in the work can be a starting point for future research and for building real intelligent wells and intelligent oilfields.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Oilconf 2013. http://www.oilconference.ru/#!newsand-publications/c17jc. Cited April 7, 2014.

  2. Moscow Section of the International Society of Petroleum Engineers SPE–SPE MOSCOW SECTION. http://www.spe-moscow.org/ru/news/index.php?id=217. Cited April 7, 2014.

  3. Oil Production, Refining, Chemicals–V International specialized exhibition in Samara. http://packer-service.ru/news_2011-10_gasoilexpo_2011_samara.html. Cited April 7, 2014.

  4. Smart well–What is it? Oil, Gas, Innovations, 2011, no. 11. http://neft-gaz-novacii.ru/ru/component/content/article/674-l-r-. Cited April 7, 2014.

  5. Kul’chitskii, V.V., Addressing the participants of the round table on smaret wells. http://www.weatherford.ru/assets/files/pdf/NGN_11_discussion_article.p df. Cited April 7, 2014.

    Google Scholar 

  6. Pchelnikov, R.L. Mironov, D.V., et al., Smart alarms tool development approach for oil production monitoring system (SPE 166378), SPE: Upravlenie Tsifrovym Mestorozhdeniem (SPE: Digital Mining Field Management), 2013.

    Book  Google Scholar 

  7. Shevchenko, S.D. Mironov, D.V., et al., Samotlor: Optimization of production in real time for the largest deposit in Russia (SPE 149615), SPE: Upravlenie Tsifrovym Mestorozhdeniem (SPE: Digital Mining Field Management), 2013.

    Google Scholar 

  8. Ignat’ev, V., Intelligent control systems, Neftegazov. Vertikal’, 2011, no. 21, pp. 24–32. http://ngv.ru/upload/iblock/78f/78fe66c2e4d54c4d41fa0f510fc01a03.pdf. Cited April 7, 2014.

    Google Scholar 

  9. Production optimization and smart wells. http://www.weatherford.ru/ru/service/production/53. Cited April 7, 2014.

  10. Digital intelligent control systems for oil fields. http://lstart.ru/proucts/resheniya_dlya_neftyanoy_promyshle nnosti/intellektualnye_sistemy_upravleniya_neftyanymi_ polyami/. Cited April 7, 2014.

  11. Controller of intelligent control and simulation of wells. http://naftamatika.com/wpcontent/uploads/2011/05/BrochureRussia.pdf. Cited April 7, 2014.

  12. Smart wells. Optimization of energy consumption of oil production through intelligent control of oil submersible pumps. Register of innovative products, technologies and services recommended for use in the Russian Federation. http://innoprod.startbase.ru/products/23938/. Cited April 7, 2014.

  13. Lepekhin, V.I., Vidyakin, N.G., Valeev, A.S., and Kan, A.G., ZAO ELEKTON: Our ideas and perspectives, Neftyan. Khoz., 2004, no. 5. http://www.elekton.ru/article1.shtml. Cited April 7, 2014.

  14. Golubyatnikov, M.B. and Ganeev, A.R., Intelligent control station for downhole sucker rod pumps. http://knowledge.allbest.ru/geology/d-3c0b65635b2bd78a5c43a89421316d27.html. Cited April 7, 2014.

    Google Scholar 

  15. Business plan of the Smart Wells project (development of the smart well system based on the shape memory effect for dual-partite and sequential extraction of hydrocarbons). http://www.pandia.ru/text/77/178/27887.php. Cited April 7, 2014.

  16. Use of intelligent valves in harsh conditions. 2006. http://controlengrussia.com/artykul/article/ispolzovanieintellektualnykh-zadvizhek-v-tjazhelykh-us/, http://controlengrussia.com/verkhnee-menju/na-glavnuju/. Cited April 7, 2014.

  17. Kravtsov, M., Smart mining field: New opportunities and new solutions. http://ozna.ru/presscenter/articles/detail.php?SECTION_ID=&ELEMENT_ID= 1414. Cited April 7, 2014.

    Google Scholar 

  18. Kabaev, M.V., Smart extraction control in the TsDNG4(T) Tevlino-Russkinskoye field, Inzh. Prakt., 2010, no. 10. http://www.glavteh.ru/files/IP-10_Kabaev.pdf. Cited April 7, 2014.

    Google Scholar 

  19. Adaptive system for downhole monitoring and control to optimize the operation of the well (Smart Well). http://www.tc-irz.ru/tek?Id=76&Pic=1. Cited April 7, 2014.

  20. Ivanovskii, B.N. and Sabirov, A.A., On the question of intellectualization of oil production. http://neftegas.info/territoriya-neftegaz/3216-k-voprosuob-intellektualizacii-dobychi-nefti.html. Cited April 7, 2014.

    Google Scholar 

  21. Osipov, G.S., Dynamic models and tools that use empirical and expert knowledge, Trudy 3-go rasshirennogo seminara “Ispol’zovanie metodov iskusstvennogo intellekta i vysokoproizvoditel’nykh vychislenii v aerokosmicheskikh issledovaniyakh” (Proc. 3rd Expanded Seminar on the use of artificial intelligence methods and high-performance computing in aerospace research), Pereslavl-Zalesskii: Feniks, 2003, pp. 17–27.

    Google Scholar 

  22. Osipov, G.S., Metody iskusstvennogo intellekta (Artificial Intelligence Techniques), Moscow: Fizmatlit, 2011.

    Google Scholar 

  23. Osipov, G.S., Priobretenie znanii intellektual’nymi sistemami: Osnovy teorii i tekhnologii (Acquisition of Knowledge by Intelligent Systems: Basics of Theory and Technology), Moscow: Fizmatlit, 1997.

    Google Scholar 

  24. Solov’ev, I.G., Control and management of the hydrodynamics well system in non-stationary environments. http://www.ipdn.ru/rics/pdf/543.pdf. Cited April 7, 2014.

    Google Scholar 

  25. Solov’ev, I.G. and Fomin, V.V., A mathematical model of the process of development of wells with UENTs after the killing. http://www.ipdn.ru/rics/doc0/DB/b4/1-solf.htm. Cited April 7, 2014.

    Google Scholar 

  26. Zhukova, S.V., Zolotukhin, Yu.N., and Rakhmanova, L.A., Genetic approach and fuzzy estimation in optimization of PID-controllers, in ROI-98. Raspredelennaya obrabotka informatsii. Trudy shestogo mezhdunarodnogo seminara (ROI-98. Distributed data processing. Proc. 6th Int. Sem.),Novosibirsk, 1998, pp. 313–317.

    Google Scholar 

  27. Vinogradov, A.N., Zhilyakova, L.Yu., and Osipov, G.S., Dynamic intelligent systems. I. Submission of knowledge and basic algorithms, Izv. Akad. Nauk. Teor. Sist. Upr., Moscow: Nauka, 2002, no. 6, pp. 119–127.

    MathSciNet  Google Scholar 

  28. Vinogradov, A.N., Zhilyakova, L.Yu., and Osipov, G.S., Dynamic intelligent systems. II. Modeling of purposeful behavior, Izv. Akad. Nauk. Teor. Sist. Upr., Moscow: Nauka, 2003, no. 1, pp. 87–94.

    MathSciNet  Google Scholar 

  29. Balkova, A., A precision electric drive with brushless motor, Electron. Compon., 2008, no. 11. pp. 32–43. http://www.russianelectronics.ru/leaderr/review/40498/doc/44462/. Cited April 7, 2014.

    Google Scholar 

  30. Makarov, D.A., The method for adjusting the PID controller based on expert knowledge, Teoriya and Praktika Sistemnogo Analiza: Trudy I Vserossiiskoi Nauchnoi Konferentsii Molodykh Uchenykh (Theory and Practice of System Analysis: Proc. 1st All-Russian Sci. Conf. of Young Scientists), Rybinsk, 2010, vol. 1, pp. 67–73.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. F. Zadneprovskii.

Additional information

Original Russian Text © V.F. Zadneprovskii, V.P. Fralenko, M.V. Khachumov, 2014, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2014, No. 4, pp. 59–67.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zadneprovskii, V.F., Fralenko, V.P. & Khachumov, M.V. Intellectual technologies in the management of oil fields. Sci. Tech.Inf. Proc. 42, 448–454 (2015). https://doi.org/10.3103/S0147688215060131

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0147688215060131

Keywords

Navigation