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Type curves calculation of incremental oil production for the miscible displacement based on compositional simulation

UDK: 622.276.43:661.97
DOI: 10.24887/0028-2448-2017-12-42-45
Key words: miscible displacement, EOR methods, type curves, oil production forecast, flow simulation
Authors: N.G. Glavnov, V.V. Kunzevich, M.V. Vershinina, V.M. Babin (Gazpromneft NTC LLC, RF, Sain-Petersburg)

Calculation of incremental oil production by the application of a certain method of enhanced oil recovery for a particular development object remains complex, time-consuming task, requiring deep specialized knowledge in various areas. However, at an early stage, technology assessment, its elaboration, forecast its effectiveness, especially for a group of objects or fields often used so-called express methods: analytical approximations, statistical results of analogue deposits, as well as the typical oil production curves. Each of the above methods has drawbacks, some very coarse, others cover a narrow range of properties and cannot be applied simultaneously to a large number of different objects (by properties) to guarantee a unified approach and the rightness of the further analysis.

This work is devoted to the effectiveness assessment of the miscible displacement application based on using type curves. The article suggests the way to obtain the library type curves of incremental oil production from the implementation method based on compositional reservoir simulation. The approach is expensive only at the stage of creating type curves (definition of varied parameters, pitch their sampling, execution and processing of calculations), which is easily compensated by ease of use, scale, flexibility and scalability in the future. The analysis identified the main parameters for determining the effectiveness of the technology and proposed the boundaries of their variation, covering the range of changes in the properties of the fields studied. Their discretization was performed depending on the impact of the factor on the development forecasts, the oil miscible displacement by carbon dioxide or WAG. On the basis of type curve set some factors were identified (geological and technological) that affect the amount of incremental oil production and its behavior over time.

The generated library covers the entire range of geological and physical characteristics of the company object Gazprom Neft PJSC and efficiency can be applied to any development object.

References

1. Koottungal Leena, 2014 Worldwide EOR survey, Oil & Gas Journal, 2014, no. 4, pp. 79–91.

2. Denbury corporate presentation, 2017, April, URL: http://s1.q4cdn.com/ 594864049/files/doc_presentations/2017/April_2017-Corporate-Presentation_FINAL.pdf

3. Lake L.W., Walsh M.P., Technical report. Enhanced oil recovery, field data, literature search, Austin. 2008, 119 p.

4. Wood D.J., Lake L.W., Johns R.T., A screening model for CO2 Flooding and storage in Gulf coast reservoirs based on dimensionless groups, SPE 100021, 2006.

5. Surguchev M.L., Vtorichnye i tretichnye metody uvelicheniya nefteotdachi plastov (Secondary and tertiary methods of enhanced oil recovery), Moscow: Nedra Publ., 1985, 308 p.

6. Aladasani Ahmad, Bai Baojun, Recent development and updated screening criteria of enhanced oil recovery techniques, SPE 130726, 2010.

7. Stepanova G.S., Tolokonskaya L.D., Nenartovich T.L., Matasova O.A., Enhanced oil recovery from oil rim of East area of Orenburg gas condensate field (In Russ.), Gazovaya promyshlennost’ = GAS Industry of Russia, 2007, no. 3, pp. 38–41.

8. Khasanov M.M., Babin V.M., Melchaeva O.U. et al., Application of mathematical optimization techniques for well pattern selection, SPE 171163-MS, 2014.

9. Babin V.M., Vashevnik A.M., Ushmaev O.S. et al., A methodology for the refinement of well locations during operational drilling in presence of geological uncertainty (In Russ.), SPE 181992-MS, 2016.

10. Surguchev M.L., Gorbunov A.T., Zabrodin D.P., Metody izvlecheniya ostatochnoy nefti (Methods of the residual oil extraction), Moscow: Nedra Publ., 1991, 308 p.

Calculation of incremental oil production by the application of a certain method of enhanced oil recovery for a particular development object remains complex, time-consuming task, requiring deep specialized knowledge in various areas. However, at an early stage, technology assessment, its elaboration, forecast its effectiveness, especially for a group of objects or fields often used so-called express methods: analytical approximations, statistical results of analogue deposits, as well as the typical oil production curves. Each of the above methods has drawbacks, some very coarse, others cover a narrow range of properties and cannot be applied simultaneously to a large number of different objects (by properties) to guarantee a unified approach and the rightness of the further analysis.

This work is devoted to the effectiveness assessment of the miscible displacement application based on using type curves. The article suggests the way to obtain the library type curves of incremental oil production from the implementation method based on compositional reservoir simulation. The approach is expensive only at the stage of creating type curves (definition of varied parameters, pitch their sampling, execution and processing of calculations), which is easily compensated by ease of use, scale, flexibility and scalability in the future. The analysis identified the main parameters for determining the effectiveness of the technology and proposed the boundaries of their variation, covering the range of changes in the properties of the fields studied. Their discretization was performed depending on the impact of the factor on the development forecasts, the oil miscible displacement by carbon dioxide or WAG. On the basis of type curve set some factors were identified (geological and technological) that affect the amount of incremental oil production and its behavior over time.

The generated library covers the entire range of geological and physical characteristics of the company object Gazprom Neft PJSC and efficiency can be applied to any development object.

References

1. Koottungal Leena, 2014 Worldwide EOR survey, Oil & Gas Journal, 2014, no. 4, pp. 79–91.

2. Denbury corporate presentation, 2017, April, URL: http://s1.q4cdn.com/ 594864049/files/doc_presentations/2017/April_2017-Corporate-Presentation_FINAL.pdf

3. Lake L.W., Walsh M.P., Technical report. Enhanced oil recovery, field data, literature search, Austin. 2008, 119 p.

4. Wood D.J., Lake L.W., Johns R.T., A screening model for CO2 Flooding and storage in Gulf coast reservoirs based on dimensionless groups, SPE 100021, 2006.

5. Surguchev M.L., Vtorichnye i tretichnye metody uvelicheniya nefteotdachi plastov (Secondary and tertiary methods of enhanced oil recovery), Moscow: Nedra Publ., 1985, 308 p.

6. Aladasani Ahmad, Bai Baojun, Recent development and updated screening criteria of enhanced oil recovery techniques, SPE 130726, 2010.

7. Stepanova G.S., Tolokonskaya L.D., Nenartovich T.L., Matasova O.A., Enhanced oil recovery from oil rim of East area of Orenburg gas condensate field (In Russ.), Gazovaya promyshlennost’ = GAS Industry of Russia, 2007, no. 3, pp. 38–41.

8. Khasanov M.M., Babin V.M., Melchaeva O.U. et al., Application of mathematical optimization techniques for well pattern selection, SPE 171163-MS, 2014.

9. Babin V.M., Vashevnik A.M., Ushmaev O.S. et al., A methodology for the refinement of well locations during operational drilling in presence of geological uncertainty (In Russ.), SPE 181992-MS, 2016.

10. Surguchev M.L., Gorbunov A.T., Zabrodin D.P., Metody izvlecheniya ostatochnoy nefti (Methods of the residual oil extraction), Moscow: Nedra Publ., 1991, 308 p.


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