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Automated solution to unlock base production potential

UDK: 622.276.5.014
Key words: achievement of a base production potential, waterflooding management, selection of candidates for transfer to injection, selection of candidates for the recovery of productivity
Authors: А.V. Bilinchuk, F.F. Khaliullin (Gazprom Neft PJSC, RF, Saint-Petersburg), A.N. Sitnikov, А.А. Pustovskikh, A.S. Margarit, I.A. Zhdanov, T.V. Andzhukaev (GazpromNeft NTC LLC, RF, Saint-Petersburg)
In current external conditions effective assets management has the highest priority for the oil industry. The global production process optimization and performance improvement of all employees are one of the key growth driver of operating efficiency. Although there are many theoretical studies to monitor the achievement of the potential wells, in the most of Russian companies control is carried out by expertise using poorly integrated approaches and tools. This leads to non-optimal and untimely decisions related to development management of current assets and such corresponding consequences: a production loss, increasing water cut, time increase of achieving a planned recovery factor, and unproductive injection to induced fractures. The objective of the work is development and implementation of a system to effectively control achievement of the base production potential. The system is based on the self-consistent numerical and analytical models, which continuously adapting to information from corporate databases. To control changes in well productivity incoming and calculated indicators are automatically examined. In case of problems, the system selects the workover process with estimated potential effect or recommends additional investigations. The presented algorithms form the basis of a decision support system. It is a complete IT solution, embedded into commercial operation. During development of the information system, the organizational structure of the geological departments of the company was taken into account, which is reflected in the functional division into subsystems. At the present, a production program of activities was aimed to optimize a base production, is based in a large extent on the results which had calculated by the information system.

References

1. Rezapour A., Ortega A., Ershaghi I., Reservoir waterflooding system identification

and model validation with injection, SPE 174052-MS, 2015.

2. Doublet L.E., Pande P.K., McCollum T.J., Blasingame T.A., Decline curve

analysis using type curves – analysis of oil well production data using material

balance time: application to field cases, SPE 28688-MS, 1994.

3. Grinestaff G.H., Waterflood pattern allocations: Quantifying the injector to

producer relationship with streamline simulation, SPE 54616-MS, 1999.

4. Ojo K.P., Tiab D., Osisanya S.O., Dynamic material balance equation and

solution technique using production and PVT data, SPE Petroleum Society of

Canada, 2006, March 1, DOI:10.2118/06-03-03.

5. Nelder J.A., Mead R., Computer Journal, 1965, V. 7, pp. 308–313.

6. Dietz D.N., Determination of average reservoir pressures from build up surveys,

JPT, 1965, August, pp. 955–959.

7. Baykov V.A., Zhdanov R.M., Mullagalieva T.I., Usmanov T.S., Selecting the optimal

system design for the fields with low-permeability reservoirs (In Russ.),

Neftegazovoe delo = The electronic scientific journal Oil and Gas Business,

2011, no. 1, pp. 84–98.

In current external conditions effective assets management has the highest priority for the oil industry. The global production process optimization and performance improvement of all employees are one of the key growth driver of operating efficiency. Although there are many theoretical studies to monitor the achievement of the potential wells, in the most of Russian companies control is carried out by expertise using poorly integrated approaches and tools. This leads to non-optimal and untimely decisions related to development management of current assets and such corresponding consequences: a production loss, increasing water cut, time increase of achieving a planned recovery factor, and unproductive injection to induced fractures. The objective of the work is development and implementation of a system to effectively control achievement of the base production potential. The system is based on the self-consistent numerical and analytical models, which continuously adapting to information from corporate databases. To control changes in well productivity incoming and calculated indicators are automatically examined. In case of problems, the system selects the workover process with estimated potential effect or recommends additional investigations. The presented algorithms form the basis of a decision support system. It is a complete IT solution, embedded into commercial operation. During development of the information system, the organizational structure of the geological departments of the company was taken into account, which is reflected in the functional division into subsystems. At the present, a production program of activities was aimed to optimize a base production, is based in a large extent on the results which had calculated by the information system.

References

1. Rezapour A., Ortega A., Ershaghi I., Reservoir waterflooding system identification

and model validation with injection, SPE 174052-MS, 2015.

2. Doublet L.E., Pande P.K., McCollum T.J., Blasingame T.A., Decline curve

analysis using type curves – analysis of oil well production data using material

balance time: application to field cases, SPE 28688-MS, 1994.

3. Grinestaff G.H., Waterflood pattern allocations: Quantifying the injector to

producer relationship with streamline simulation, SPE 54616-MS, 1999.

4. Ojo K.P., Tiab D., Osisanya S.O., Dynamic material balance equation and

solution technique using production and PVT data, SPE Petroleum Society of

Canada, 2006, March 1, DOI:10.2118/06-03-03.

5. Nelder J.A., Mead R., Computer Journal, 1965, V. 7, pp. 308–313.

6. Dietz D.N., Determination of average reservoir pressures from build up surveys,

JPT, 1965, August, pp. 955–959.

7. Baykov V.A., Zhdanov R.M., Mullagalieva T.I., Usmanov T.S., Selecting the optimal

system design for the fields with low-permeability reservoirs (In Russ.),

Neftegazovoe delo = The electronic scientific journal Oil and Gas Business,

2011, no. 1, pp. 84–98.



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