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ERA:Production – an integrated platform for increasing the efficiency of the operation of the artificial lift and oil fields

UDK: 681.518:622.276.53
DOI: 10.24887/0028-2448-2017-12-60-63
Key words: oil production, artificial lift, total cost of ownership, energy consumption for liquid lifting, bottomhole pressure, time between failures, cost model, cash flow, optimal operating mode selection
Authors: A.A. Shushakov, A.V. Bilinchuk, N.M. Pavlechko, F.N. Khalikov (Gazprom Neft PJSC, RF, Saint-Petersburg), A.G. Suleymanov, A.N. Sitnikov, A.A. Slabetski, N.F. Teplyakov, N.P. Sarapulov (Gazpromneft NTC LLC, RF, Saint-Petersburg), D.A. Shestakov, R.Yu. Mansafov (ITSK LLC, RF, Moscow)

The history of the development of projects related to the strategy of the company intellectual field development & production (ERA) began in 2013 with the information systems ERA.Mechfond and Electronic Shahmatka. To date, the platform ERA is composed of over 30 modules associated with oil production for the automation of business processes, report generation, engineering calculations and monitoring of deviations fr om preset modes. The system was put into commercial operation in seven subsidiaries of Gazprom Neft, as the system is deployed in the STC and the Corporate center. Currently, there are already over 1800 unique registered users. The company has received 12 certificates of registration of computer programs and in the development attended 6 different structural units. During the operation of the information modules ERA has allowed a 60% reduction in non-productive time of technical staff, improve data quality, efficiency of management decision-making, increase MTBF and to produce additional volume of hydrocarbons.

In the article methodical approaches are considered for a comprehensive assessment of the profitability of the fund and optimization of oil production processes implemented in a common IT platform that is able to consolidate continuously incoming large volumes of updated data in order to determine the optimal parameters and operating modes. The analysis is carried out taking into account the linkage of the calculation of the technological lim it to achieve the minimum bottomhole pressure existing on the market pump equipment, the dynamics of residual recoverable oil reserves, the forecast of the production of the well for failure, the consumption of electricity from the operating mode of the well, the impact on the optimization of infrastructure, complicating and other factors. Continuous self-adaptation of the model for forecasting NPVs for individual objects with the definition of an economic extremum is taken into account. The main result should be on-line formation of optimal well operation scenarios in order to increase profitability. The developed approaches open up new opportunities for increasing operational efficiency of oil field exploitation.

References

1. Khasanov M.M., Prokof'ev D.O., Ushmaev O.S., Belozerov B.V. et al., Promising Big Data technologies in petroleum engineering: the experience of the Gazprom Neft PJSC (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2016, no. 12, pp. 76–79

2. Doktor S.A., Korolev D.M. et al., Organising artificial lifting management: example of Electronic Fields Development project (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2013, no. 12, pp. 70–72.

3. Jacobs T., Automated drilling technologies showing promise, JPT, 2015, V. 67, no. 6 (June).

4. Rawi Zaid, Machinery predictive analytics, SPE 128559, 2010.

5. Stone P., Introducing predictive analytics: Opportunities, SPE 106865, 2007.

6. Makarov A.V., Ekonomicheskie voprosy proektirovaniya i razrabotki neftyanykh mestorozhdeniy (Economic issues of design and development of oil fields), St. Peterburg: Nedra Publ., 2010, 196 p.

7. Khasanov M.M., Maksimov Yu.V., Skudar' O.O. et al., Cost engineering in Gazprom Neft PJSC: current situation and future development (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2015, no. 12, pp. 30–33.

The history of the development of projects related to the strategy of the company intellectual field development & production (ERA) began in 2013 with the information systems ERA.Mechfond and Electronic Shahmatka. To date, the platform ERA is composed of over 30 modules associated with oil production for the automation of business processes, report generation, engineering calculations and monitoring of deviations fr om preset modes. The system was put into commercial operation in seven subsidiaries of Gazprom Neft, as the system is deployed in the STC and the Corporate center. Currently, there are already over 1800 unique registered users. The company has received 12 certificates of registration of computer programs and in the development attended 6 different structural units. During the operation of the information modules ERA has allowed a 60% reduction in non-productive time of technical staff, improve data quality, efficiency of management decision-making, increase MTBF and to produce additional volume of hydrocarbons.

In the article methodical approaches are considered for a comprehensive assessment of the profitability of the fund and optimization of oil production processes implemented in a common IT platform that is able to consolidate continuously incoming large volumes of updated data in order to determine the optimal parameters and operating modes. The analysis is carried out taking into account the linkage of the calculation of the technological lim it to achieve the minimum bottomhole pressure existing on the market pump equipment, the dynamics of residual recoverable oil reserves, the forecast of the production of the well for failure, the consumption of electricity from the operating mode of the well, the impact on the optimization of infrastructure, complicating and other factors. Continuous self-adaptation of the model for forecasting NPVs for individual objects with the definition of an economic extremum is taken into account. The main result should be on-line formation of optimal well operation scenarios in order to increase profitability. The developed approaches open up new opportunities for increasing operational efficiency of oil field exploitation.

References

1. Khasanov M.M., Prokof'ev D.O., Ushmaev O.S., Belozerov B.V. et al., Promising Big Data technologies in petroleum engineering: the experience of the Gazprom Neft PJSC (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2016, no. 12, pp. 76–79

2. Doktor S.A., Korolev D.M. et al., Organising artificial lifting management: example of Electronic Fields Development project (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2013, no. 12, pp. 70–72.

3. Jacobs T., Automated drilling technologies showing promise, JPT, 2015, V. 67, no. 6 (June).

4. Rawi Zaid, Machinery predictive analytics, SPE 128559, 2010.

5. Stone P., Introducing predictive analytics: Opportunities, SPE 106865, 2007.

6. Makarov A.V., Ekonomicheskie voprosy proektirovaniya i razrabotki neftyanykh mestorozhdeniy (Economic issues of design and development of oil fields), St. Peterburg: Nedra Publ., 2010, 196 p.

7. Khasanov M.M., Maksimov Yu.V., Skudar' O.O. et al., Cost engineering in Gazprom Neft PJSC: current situation and future development (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2015, no. 12, pp. 30–33.


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