Preview

PROneft. Professionally about Oil

Advanced search

Technology Overview: From digital to intelligent field

https://doi.org/10.24887/2587-7399-2018-3-68-74

Abstract

The development of information systems allows you to collect, filter, store and process data of the field, describe the physical processes of oil and gas reservoirs and ground infrastructure. Enhanced capabilities of intelligent information systems allows a new angle to look at improving the efficiency of oil and gas field. We can greatly improve the operating efficiency of the asset and the quality of management decisions by combining the rapid collection of data on all systems field with integrated asset model and provide a computational libraries, allows the analysis of the technological system and provide skilled suggestions for optimization and potential loss in future (proactive protection). An integrated approach will allow for the optimization of the global instead of local, which is currently carried out by each service independently. It allows all professionals to focus their efforts on achieving a common goal.

About the Authors

A. I. Vlasov
Gazpromneft NTC LLC
Russian Federation

Saint-Petersburg



A. F. Mozhchil
Gazpromneft NTC LLC
Russian Federation

Saint-Petersburg



References

1. Hardy I.T., Wetzel G.P., Automated production systems, SPE 10005-MS, 1982.

2. Barber E., Shippe M., Neftegazovoe obozrenie, 2007–2008, URL: https://www.slb.com/~/media/Files/resources/oilfield_review/ors07/win07/optimizing.pdf

3. Margelov D.V., The deposit on the palm - an innovative perspective on the prospects of intellectual deposits (In Russ.), Inzhenernaya praktika, 2010, no. 9, pp. 43-46.

4. Vlasov A.I., Andreev K.V., Poplygin V.V., Potential opportunities for the creation of intellectual deposits in the LUKOIL Group (In Russ.), Gazovaya promyshlennost', 2014, no. 7, pp. 43-45.

5. Gul'demond E., Akda L., Andronov M., IT Governance and Organization in Smart Oil Fields (In Russ.), SPE 160557-RU, 2012.

6. URL: http://itps.com/uploads/files/Petex%20IPM%20Brochure%20RUS.pdf.

7. Shevchenko S.D., Navozov V.A., Mironov D.V. et al., Oil production process optimization resultant from intelligent field technologies implementation in Samotlorskoe field (In Russ.), SPE 161978, 2012.

8. Berezina A.A., Cherepovitsyn A.E., Economical conception of oil&gas smart fields (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2014, no. 4, pp. 14-15

9. Eremin N.A., Eremin Al.N., Eremin An.N., Upravlenie razrabotkoy intellektual’nykh mestorozhdeniy (Management of the development of intellectual deposits), Moscow: Publ. of Gubkin Oil and Gas State University, 2011, Part 1, p. 9.

10. Crichlow H.B., Modern reservoir engineering: a simulation approach, Prentice-Hall Inc., New Jersey, 1977.

11. Acosta L.M., Jimenez J., Guedez A. et al., Integrated modeling of the Furrial Field Asset applying risk and uncertainty analysis for the decision taking, SPE 94093, 2005.

12. Grishagin A.V., On the problems of integration of the reservoir-well system - arrangement - the economy by the example of the West-Kommunarskoye oil field development project (In Russ.), Nauchno-tekhnicheskiy vestnik OAO “NK “Rosneft'”, 2009, no. 1, pp. 30-35.

13. Vlasov A.I., Smart field for optimal oil field (In Russ.), Zhurnal-daydzhest EnergyLand.info, 2014, no. 5, pp. 38-43.

14. Ismagilov R.R., Khasanov M.M., Maksimov Yu.V. et al., Prospects of energy optimization on Gazprom Neft JSC objects with use of hydrocarbons (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2014, no. 12, pp. 74-76.


Review

For citations:


Vlasov A.I., Mozhchil A.F. Technology Overview: From digital to intelligent field. PROneft. Professionally about Oil. 2018;(3):68-74. (In Russ.) https://doi.org/10.24887/2587-7399-2018-3-68-74

Views: 299


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2587-7399 (Print)
ISSN 2588-0055 (Online)