Neural network platform solutions to reduce oil and gas drilling incident rate

UDK: 681:518:622.24
DOI: 10.24887/0028-2448-2020-10-71-75
Key words: machine learning, breakdown and drilling problem forecasting, mudlogging, blockchain, Industrial internet of things, microservice, Unofactor digital platform
Authors: I.G. Melnikov (NPO SNGS, RF, Moscow), O.V. Zakharov (NPO SNGS, RF, Moscow), S.O. Kosenkov (NPO SNGS, RF, Moscow)

The article describes the technology developed by the specialists of NPO SNGS to reduce emergency situations during the construction of oil and gas wells using machine learning methods. The technology based on the elements of the Industry 4.0 concept such as digitalization, artificial intelligence, Industrial Internet of things, distributed registry technology (blockchain), is integrated into the Unofactor digital technology platform, which allows you to combine various software and hardware components into a single technological process. The emphasis is made also on ensuring the raw data reliability, achieved through the blockchain technology implementation inside the data acquisition, collection, storage, and transmission system. Methods for solving the problem of forecasting emergencies are given taking into account the applicability of machine learning methods when receiving drilling data from any well within the study area. The results of the application of the developed technology and the minimum necessary requirements for its implementation are presented taking into account the universality of the Unofactor digital platform. The main objects of the proposed technology are difficult wells with the complex environment (Eastern Siberia, Russian offshore fields) because the technology reduces the financial costs of the well designing and construction error checking and correcting by accident prevention.

References

1. Federal norms and rules in the field of industrial safety “Pravila bezopasnosti v neftyanoy i gazovoy promyshlennosti” (Safety rules in the oil and gas industry), URL: http://docs.cntd.ru/document/499011004

2. RD 08-254-98. Instruktsiya po preduprezhdeniyu gazoneftevodoproyavleniy i otkrytykh fontanov pri stroitel'stve i remonte skvazhin v neftyanoy i gazovoy promyshlennosti (Instructions for the prevention of gas and oil water seepage and open fountains during the construction and repair of wells in the oil and gas industry), URL: http://docs.cntd.ru/document/1200005950 (data obrashcheniya 01.04.2020)

3. Krylov V.I., Sukhenko N.I., Bor'ba s pogloshcheniem pri burenii skvazhin (Controlling lost circulation while drilling wells), Moscow: Nedra Publ., 1968, р. 176.

4. Vinnichenko V.M., Goncharov A.E., Maksimenko N.N., Preduprezhdenie i likvidatsiya oslozhneniy i avariy pri burenii razvedochnykh skvazhin (Prevention and elimination of complications and accidents while drilling exploration wells), Moscow: Nedra Publ., 1991, р. 169.

5. RF patent application no. 2019144411/03. Method for reducing emergency situations during the construction of oil and gas wells using machine learning, Inventors: Zakharov O.V., Zakharov I.V.

6. Industriya 4.0: Sozdanie tsifrovogo predpriyatiya (Industry 4.0: Building a digital enterprise), URL: https://www.pwc.com/gx/en/industries/industries-4.0/landing-page/industry-4.0-building-your-digital-...

7. Newman S., Building microservices, O'Reilly Media, Inc., 2015, р. 304..

8. Computer program no.2019667775, Programma rascheta neyronnoy seti dlya prognozirovaniya oslozhneniy i avariy v protsesse stroitel'stva neftegazovykh skvazhin (NeyroSet) (Neural network calculation program for predicting complications and accidents during the construction of oil and gas wells (NeuroSet)), Authors: Zakharov O.V., Kosenkov S.O., Chetyrin Yu.S.

The article describes the technology developed by the specialists of NPO SNGS to reduce emergency situations during the construction of oil and gas wells using machine learning methods. The technology based on the elements of the Industry 4.0 concept such as digitalization, artificial intelligence, Industrial Internet of things, distributed registry technology (blockchain), is integrated into the Unofactor digital technology platform, which allows you to combine various software and hardware components into a single technological process. The emphasis is made also on ensuring the raw data reliability, achieved through the blockchain technology implementation inside the data acquisition, collection, storage, and transmission system. Methods for solving the problem of forecasting emergencies are given taking into account the applicability of machine learning methods when receiving drilling data from any well within the study area. The results of the application of the developed technology and the minimum necessary requirements for its implementation are presented taking into account the universality of the Unofactor digital platform. The main objects of the proposed technology are difficult wells with the complex environment (Eastern Siberia, Russian offshore fields) because the technology reduces the financial costs of the well designing and construction error checking and correcting by accident prevention.

References

1. Federal norms and rules in the field of industrial safety “Pravila bezopasnosti v neftyanoy i gazovoy promyshlennosti” (Safety rules in the oil and gas industry), URL: http://docs.cntd.ru/document/499011004

2. RD 08-254-98. Instruktsiya po preduprezhdeniyu gazoneftevodoproyavleniy i otkrytykh fontanov pri stroitel'stve i remonte skvazhin v neftyanoy i gazovoy promyshlennosti (Instructions for the prevention of gas and oil water seepage and open fountains during the construction and repair of wells in the oil and gas industry), URL: http://docs.cntd.ru/document/1200005950 (data obrashcheniya 01.04.2020)

3. Krylov V.I., Sukhenko N.I., Bor'ba s pogloshcheniem pri burenii skvazhin (Controlling lost circulation while drilling wells), Moscow: Nedra Publ., 1968, р. 176.

4. Vinnichenko V.M., Goncharov A.E., Maksimenko N.N., Preduprezhdenie i likvidatsiya oslozhneniy i avariy pri burenii razvedochnykh skvazhin (Prevention and elimination of complications and accidents while drilling exploration wells), Moscow: Nedra Publ., 1991, р. 169.

5. RF patent application no. 2019144411/03. Method for reducing emergency situations during the construction of oil and gas wells using machine learning, Inventors: Zakharov O.V., Zakharov I.V.

6. Industriya 4.0: Sozdanie tsifrovogo predpriyatiya (Industry 4.0: Building a digital enterprise), URL: https://www.pwc.com/gx/en/industries/industries-4.0/landing-page/industry-4.0-building-your-digital-...

7. Newman S., Building microservices, O'Reilly Media, Inc., 2015, р. 304..

8. Computer program no.2019667775, Programma rascheta neyronnoy seti dlya prognozirovaniya oslozhneniy i avariy v protsesse stroitel'stva neftegazovykh skvazhin (NeyroSet) (Neural network calculation program for predicting complications and accidents during the construction of oil and gas wells (NeuroSet)), Authors: Zakharov O.V., Kosenkov S.O., Chetyrin Yu.S.


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