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Estimation of gauges configuration value for digital oilfield ESP-producing oil wells

UDK: 622.276.53.054.23:621.67-83
DOI: 10.24887/0028-2448-2018-2-72-75
Key words: gauges, downhole telemetry system, smart field, digital oilfield, cost optimization, automation, value of information
Authors: M.G. Volkov (RN-UfaNIPIneft LLC, RF, Ufa; Ufa State Petroleum Technical University, RF, Ufa), P.I. Chermyanin (RN-UfaNIPIneft LLC, RF, Ufa)

Ability to make decisions using validated real time data is known as a base tier of a digital oilfield. The goal of digitalization is enhancing oil production and cost reducing. But for mature onshore fields with thousands of producing wells with low oil rates upgrading the data acquisition system may be economically unreasonable.

This paper describes the methodology of gauge configuration value estimation using the value of information concept. The main idea of the research is that additional information has value only when it drives to new well works or you can make right decision faster.

Authors analyzed statistics of a general well works on the ESP-producing oil wells (including costs and effects) and distinguished the datasets (and gauge configurations) needed to make decisions about well intervention. Results of a gauge configuration value estimation for considered onshore field are shown as a pallet that allow to choose most economically reasonable configuration using oil rate and mean time to failure parameters. Complex of low oil rate and normal MTTF values assign that there are no economic reasons to upgrade actual gauges configuration. Before using these results for investment decision it’s necessary to analyze fact well works effects, cost and nomenclature of gauges and actual business-processes in company conditions.

References

1. Reddick С., Castro A., Pannett A. et al., BP's field of the future program: Delivering success, SPE 112194, 2008.

2. Tofig A., AL-Dhubaib, Intelligent fields: Industry's Frontier&Opportunities, SPE 141874-MS-P, 2011.

3. Mabian A., Volokitin Y., Beliakova N. et al., Well and reservoir management project at Salym Petroleum Development, SPE 128834-MS-P, 2010.

4. Lilleng T., Sagatun I., Integrated operations methology and value proposition, SPE 128576-MS-P, 2010.

5. Bratvold R.B., Bickel E.J., Lohne H.P., Value of information in the oil and gas industry: Past, present, and future, SPE 110378, 2007.

6. Lohrenz J., Net values of our information, Journal of Petroleum Technology, 1988, pp. 499-503.

7. Copeland T., Antikarnov V., Real options: A practitioner's guide, New York: Texere, 2001, 384 p.

8. Coopersmith E.M., Canningham P.C., A practical approach to evaluating the value of information and real option decisions in the upstream petroleum industry, SPE 77582, 2002.

9. Shevchenko S.D., Mironov D.V., Navozov V.A. et al., Samotlor: Real-time production optimization for Russia's largest field, SPE 149615, 2011.

10. Van den Berg F., Mabian A., Knoppe R. et al., Managing fields using intelligent surveillance, production optimization and collaboration, SPE 150079-MS-P, 2012.

11. Mabian E., Intellektual'nye mestorozhdeniya Salyma (Intellectual fields of Salym), Proceedings ofВ  “Intellektual'noe mestorozhdenie: ot modelirovaniya k optimizatsii i upravleniyu” (Intellectual fields: from modeling to optimization and management), 2012.

Ability to make decisions using validated real time data is known as a base tier of a digital oilfield. The goal of digitalization is enhancing oil production and cost reducing. But for mature onshore fields with thousands of producing wells with low oil rates upgrading the data acquisition system may be economically unreasonable.

This paper describes the methodology of gauge configuration value estimation using the value of information concept. The main idea of the research is that additional information has value only when it drives to new well works or you can make right decision faster.

Authors analyzed statistics of a general well works on the ESP-producing oil wells (including costs and effects) and distinguished the datasets (and gauge configurations) needed to make decisions about well intervention. Results of a gauge configuration value estimation for considered onshore field are shown as a pallet that allow to choose most economically reasonable configuration using oil rate and mean time to failure parameters. Complex of low oil rate and normal MTTF values assign that there are no economic reasons to upgrade actual gauges configuration. Before using these results for investment decision it’s necessary to analyze fact well works effects, cost and nomenclature of gauges and actual business-processes in company conditions.

References

1. Reddick С., Castro A., Pannett A. et al., BP's field of the future program: Delivering success, SPE 112194, 2008.

2. Tofig A., AL-Dhubaib, Intelligent fields: Industry's Frontier&Opportunities, SPE 141874-MS-P, 2011.

3. Mabian A., Volokitin Y., Beliakova N. et al., Well and reservoir management project at Salym Petroleum Development, SPE 128834-MS-P, 2010.

4. Lilleng T., Sagatun I., Integrated operations methology and value proposition, SPE 128576-MS-P, 2010.

5. Bratvold R.B., Bickel E.J., Lohne H.P., Value of information in the oil and gas industry: Past, present, and future, SPE 110378, 2007.

6. Lohrenz J., Net values of our information, Journal of Petroleum Technology, 1988, pp. 499-503.

7. Copeland T., Antikarnov V., Real options: A practitioner's guide, New York: Texere, 2001, 384 p.

8. Coopersmith E.M., Canningham P.C., A practical approach to evaluating the value of information and real option decisions in the upstream petroleum industry, SPE 77582, 2002.

9. Shevchenko S.D., Mironov D.V., Navozov V.A. et al., Samotlor: Real-time production optimization for Russia's largest field, SPE 149615, 2011.

10. Van den Berg F., Mabian A., Knoppe R. et al., Managing fields using intelligent surveillance, production optimization and collaboration, SPE 150079-MS-P, 2012.

11. Mabian E., Intellektual'nye mestorozhdeniya Salyma (Intellectual fields of Salym), Proceedings ofВ  “Intellektual'noe mestorozhdenie: ot modelirovaniya k optimizatsii i upravleniyu” (Intellectual fields: from modeling to optimization and management), 2012.



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