A digital twin of well as a tool of digitalization of bringing the well on to stable production in Bashneft PJSOC

UDK: 681.518:622.276.5
DOI: 10.24887/0028-2448-2021-3-80-84
Key words: digital twin, bringing well on to stable production, electric submersible pump
Authors: A.A. Pashali (Rosneft Oil Company, RF, Moscow), A.V. Kolonskikh (RN-BashNIPIneft LLC, RF, Ufa), R.S. Khalfin (RN-BashNIPIneft LLC, RF, Ufa), D.V. Silnov (RN-BashNIPIneft LLC, RF, Ufa), A.S. Topolnikov (RN-BashNIPIneft LLC, RF, Ufa), B.M. Latypov (RN-BashNIPIneft LLC, RF, Ufa), K.R. Urazakov (RN-BashNIPIneft LLC, RF, Ufa), A.V. Katermin (Bashneft PJSOC, RF, Ufa), A.A. Palaguta (Bashneft PJSOC, RF, Ufa), R.M. Enikeev (Bashneft PJSOC, RF, Ufa)

The digital twins are one of the necessary attributes of digitalization of the industrial facilities and technological processes. Gathering data from sensors and measuring devices they model behavior of the facility or the process and marks risks and deviations from the normal work and provide the optimal way of the system operation. Oil and gas production today is one of the industry leaders in the application of digital twins to improve the production efficiency. This is so because such factors, as the diversity of output processes (reservoir engineering, well construction, artificial lift, oil transport and treatment, refining of hydrocarbon raw materials), the existence of large volume of industrial information and high level of automation (high accuracy sensors and analyzers, systems of telemechanic and telemetry, industrial databases, special software for modeling), high return on investment (by increasing of oil production and decreasing OPEX and CAPEX). In Bashneft PJSOC the concept of maximum involvement of the digital twins in oil and gas production processes is taken into service.

In this paper, the description of a digital twin of an artificial lift well equipped by the electric submersible pump is presented, which allows minimizing risks of complications during bringing the well on to stable production and to reduce the oil losses. The digital twin contains the model of elements of the well and pump installation, algorithms of adjustment to field measurements and algorithms of the forecast of the well and equipment operation. All this together enables to use it during all the stages of bringing the well on to stable production starting from initial state up to the moment of bringing the well on to stable production.

References

1. Grieves M., Origins of the digital twin concept. Working paper, Florida: Institute of Technology, 2016, 7 p.

2. Saddik A.El., Digital twins: The convergence of multimedia technologies, IEEE MultiMedia, 2018, no 25 (2), pp. 87–92.

3. Carvajal G., Mausec M., Cullick S., Intelligent digital oil and gas fields: Concepts, collaboration, and right–time decisions, Cambridge: Unitied States, 2018, 357 p.

4. Dmitrievskiy A.N., Eremin N.A., Digital modernization of oil and gas ecosystems – 2018 (In Russ.),  Aktual'nye problemy nefti i gaza, 2018, no. 2 (21), pp. 1–12.

5. Kostyukov V.E., Zhigalov V.I.., Kibkalo A.A., Baturin V.P., Digital subsea production facility (In Russ.), Neft'. Gaz. Novatsii, 2018, no. 12, pp. 21–23.

6. Brill J.P., Mukherjee H., Multiphase flow in wells, SPE Monograph, Henry L. Dogherty Series, V.17, 1999, 164 p.

7. Topol'nikov A.S., Obosnovanie primeneniya kvazistatsionarnoy modeli pri opisanii periodicheskogo rezhima raboty skvazhiny (Justification of the application of the quasi-stationary model in the description of the periodic well operation mode), Proceedings of Institute of Mechanics. R.R. Mavlyutova, 2017, V. 12, no. 1, pp. 15–26.

8. Topol'nikov A.S., Primenenie metodov matematicheskogo modelirovaniya pri kontrole i optimizatsii nestatsionarnogo rezhima raboty neftyanoy skvazhiny (Application of mathematical modeling methods for monitoring and optimization of unsteady operation of an oil well), Proceedings of Institute of Mechanics. R.R. Mavlyutova, 2016, V. 11, no. 1, pp. 53–59.

9. Volkov M.G., Optimization of low productivity wells cyclic operating (In Russ.), Neftegazovoe delo, 2017, V. 15, no. 1, pp. 70–74.

10. Andriasov R.S., Mishchenko I.T., Petrov A.I. et al., Spravochnoe rukovodstvo po proektirovaniyu razrabotki i ekspluatatsii neftyanykh mestorozhdeniy. Dobycha nefti (Reference guide for the design, development and operation of oil fields. Oil production): edited by Gimatudinov Sh.K., Moscow:  Nedra Publ., 1983, 455 p.

11. Marquez M., Modeling downhole natural separation: PhD dissertation, Tulsa, 2004, 154 p.

12. Pashali A.A., Mikhaylov V.G., Topol'nikov A.S., Flow rate retrieval on the basis of algorithms of the “virtual flowmeter” for wells testing (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2017, no. 11, pp. 63–67.

13. Volkov M.G., Dynamic models of flowing and mechanized oil producing wells to analyze their stability and control (In Russ.), Neftepromyslovoe delo, 2017, no. 4, pp. 17–20.

The digital twins are one of the necessary attributes of digitalization of the industrial facilities and technological processes. Gathering data from sensors and measuring devices they model behavior of the facility or the process and marks risks and deviations from the normal work and provide the optimal way of the system operation. Oil and gas production today is one of the industry leaders in the application of digital twins to improve the production efficiency. This is so because such factors, as the diversity of output processes (reservoir engineering, well construction, artificial lift, oil transport and treatment, refining of hydrocarbon raw materials), the existence of large volume of industrial information and high level of automation (high accuracy sensors and analyzers, systems of telemechanic and telemetry, industrial databases, special software for modeling), high return on investment (by increasing of oil production and decreasing OPEX and CAPEX). In Bashneft PJSOC the concept of maximum involvement of the digital twins in oil and gas production processes is taken into service.

In this paper, the description of a digital twin of an artificial lift well equipped by the electric submersible pump is presented, which allows minimizing risks of complications during bringing the well on to stable production and to reduce the oil losses. The digital twin contains the model of elements of the well and pump installation, algorithms of adjustment to field measurements and algorithms of the forecast of the well and equipment operation. All this together enables to use it during all the stages of bringing the well on to stable production starting from initial state up to the moment of bringing the well on to stable production.

References

1. Grieves M., Origins of the digital twin concept. Working paper, Florida: Institute of Technology, 2016, 7 p.

2. Saddik A.El., Digital twins: The convergence of multimedia technologies, IEEE MultiMedia, 2018, no 25 (2), pp. 87–92.

3. Carvajal G., Mausec M., Cullick S., Intelligent digital oil and gas fields: Concepts, collaboration, and right–time decisions, Cambridge: Unitied States, 2018, 357 p.

4. Dmitrievskiy A.N., Eremin N.A., Digital modernization of oil and gas ecosystems – 2018 (In Russ.),  Aktual'nye problemy nefti i gaza, 2018, no. 2 (21), pp. 1–12.

5. Kostyukov V.E., Zhigalov V.I.., Kibkalo A.A., Baturin V.P., Digital subsea production facility (In Russ.), Neft'. Gaz. Novatsii, 2018, no. 12, pp. 21–23.

6. Brill J.P., Mukherjee H., Multiphase flow in wells, SPE Monograph, Henry L. Dogherty Series, V.17, 1999, 164 p.

7. Topol'nikov A.S., Obosnovanie primeneniya kvazistatsionarnoy modeli pri opisanii periodicheskogo rezhima raboty skvazhiny (Justification of the application of the quasi-stationary model in the description of the periodic well operation mode), Proceedings of Institute of Mechanics. R.R. Mavlyutova, 2017, V. 12, no. 1, pp. 15–26.

8. Topol'nikov A.S., Primenenie metodov matematicheskogo modelirovaniya pri kontrole i optimizatsii nestatsionarnogo rezhima raboty neftyanoy skvazhiny (Application of mathematical modeling methods for monitoring and optimization of unsteady operation of an oil well), Proceedings of Institute of Mechanics. R.R. Mavlyutova, 2016, V. 11, no. 1, pp. 53–59.

9. Volkov M.G., Optimization of low productivity wells cyclic operating (In Russ.), Neftegazovoe delo, 2017, V. 15, no. 1, pp. 70–74.

10. Andriasov R.S., Mishchenko I.T., Petrov A.I. et al., Spravochnoe rukovodstvo po proektirovaniyu razrabotki i ekspluatatsii neftyanykh mestorozhdeniy. Dobycha nefti (Reference guide for the design, development and operation of oil fields. Oil production): edited by Gimatudinov Sh.K., Moscow:  Nedra Publ., 1983, 455 p.

11. Marquez M., Modeling downhole natural separation: PhD dissertation, Tulsa, 2004, 154 p.

12. Pashali A.A., Mikhaylov V.G., Topol'nikov A.S., Flow rate retrieval on the basis of algorithms of the “virtual flowmeter” for wells testing (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2017, no. 11, pp. 63–67.

13. Volkov M.G., Dynamic models of flowing and mechanized oil producing wells to analyze their stability and control (In Russ.), Neftepromyslovoe delo, 2017, no. 4, pp. 17–20.



Attention!
To buy the complete text of article (a format - PDF) or to read the material which is in open access only the authorized visitors of the website can. .

Mobile applications

Read our magazine on mobile devices

Загрузить в Google play

Press Releases

11.10.2021
07.10.2021
29.09.2021
Конкурс на соискание молодежной премии имени академика И.М. Губкина