Express method for determining development system parameters taking into account geological heterogeneity

UDK: 622.276.1/.4.001
DOI: 10.24887/0028-2448-2020-3-54-57
Key words: optimal parameters of the development system, hydraulic fracturing, geological heterogeneity, the dependence of coverage on the current line length, the pallet for determining of the optimal grid of wells density
Authors: Е.А. Spirina (RN-BashNIPIneft LLC, RF, Ufa), S.A. Rabtsevich (RN-BashNIPIneft LLC, RF, Ufa), D.R. Mulyukov (RN-BashNIPIneft LLC, RF, Ufa), A.V. Kolonskikh (RN-BashNIPIneft LLC, RF, Ufa)

This article proposes a method for selecting of optimal oil field development system using a two-dimensional semi-analytical simulator, based on solving of Laplace equation for calculating pressure fields and using the Buckley – Leverett theory with the method of current lines for calculating saturation fields, taking into account the geological heterogeneity of the reservoir. The account of geological heterogeneity in the two-dimensional simulator is made by means of dependence of the grid coverage coefficient on length of the current line. The distribution of current line lengths in the three-dimensional hydrodynamic model characterizes the geometry of sand bodies and geological heterogeneity of the reservoir, and the value of the grid coverage coefficient numerically expresses this heterogeneity. This approach makes it possible to speed up the process of selecting the optimal parameters of development (density of the well grid, types of well completion, parameters of the hydraulic fracturing design on producing wells, half-length of fractures after auto-fracturing on injection wells, value of bottom-hole pressure on producing and injection wells, deformation coefficient for the grid of wells, etc.) at the decision-making stage. The parameter for choosing of the optimal development system, i.e. its optimal parameters, is the maximum value of the net present value when the conditions for achieving of the design oil recovery ratio are met. The calculation of economic parameters is carried out according to the dependencies inherent in the two-dimensional semi-analytical simulator, which allows the entire cycle of technical and economic analysis in one tool. In particular, this technique is extremely relevant for fields with low permeability and disjointed reservoir. Since the key feature of this approach is the account of geological heterogeneity.

References

1. Antonenko D.A., Pavlov V.A., Sevastyanova K.K. et al., Integrated modeling of the Priobskoe oilfield (In Russ.), SPE-117413-RU, 2008, https://doi.org/10.2118/117413-RU.

2. Sidel'nikov K.A., Vasil'ev V.V., Analysis of applications of mathematical modeling of reservoir systems based on the streamline method (In Russ.), Neftegazovoe delo, 2005, no. 1.

3. Chawathé A., Taggart I., Insights into upscaling using 3D streamlines,

SPE-88846-PA, 2004, https://doi.org/10.2118/88846-PA.

4. Ates H. et al., Ranking and upscaling of geostatistical reservoir models using streamline simulation: A field case study, SPE-81497-MS, 2003, https://doi.org/10.2118/81497-MS.

5. Portella R.C.M., Hewett T.A., Upscaling, gridding, and simulating using streamtubes, SPE-65684-PA, 2000, https://doi.org/10.2118/65684-PA.

6. Baker R.O., Kuppe F., Chugh S. et al., Full-field modeling using streamline-based simulation: 4 case studies, SPE-66405-MS, 2001, https://doi.org/10.2118/66405-MS.

7. Idrobo E.A., Choudhary M.K., Datta-Gupta A., Swept volume calculations and ranking of geostatistical reservoir models using streamline simulation,

SPE-62557-MS, 2000, https://doi.org/10.2118/62557-MS.

8. Viktorov E.P., Nurlyev D.R., Rodionova I.I., Tight reservoir simulation study under geological and technological uncertainty (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2018, no. 10, pp. 60–63.

9.  Willhite G.P., Waterflooding, SPE Textbook Series, 1986.

10. Baykov V.A., Zhdanov R.M., Mullagaliev T.I., Usmanov T.S., Selecting the optimal system design for the fields with low-permeability reservoirs (In Russ.), Neftegazovoe delo, 2011, no. 1, pp. 84–97.

11. Rabtsevich C.A., Kolonskikh A.V., Mustafin R.Kh., Kostrigin I.V., Designing of oilfield development using software package RN-KIN (In Russ.), Vestnik PAO “Rosneft'”, 2014, no. 2, pp. 8–13.

12. Krylov A.P., Sostoyanie teoreticheskikh rabot po proektirovaniyu razrabotki neftyanykh mestorozhdeniy i zadachi po uluchsheniyu etikh rabot (The state of theoretical work on the design of oil fields and the tasks to improve these works), Collected papers “Opyt razrabotki neftyanykh mestorozhdeniy i zadachi po uluchsheniyu etikh rabot” (Experience in the development of oil fields and tasks to improve these works), Moscow: Gostoptekhizdast Publ., 1957, pp. 116–139.

13. Muskat M., The flow of homogeneous fluids through porous media, McGraw-Hill, New York, 1937.

14. Kanevskaya R.D., Matemeticheskoe modelirovanie razrabotki mestorozhdeniy nefti i gaza s primeneniem gidravlicheskogo razryva plasta (Mathematical modeling of the development of oil and gas using hydraulic fracturing), Moscow: Nedra-Biznestsentr Publ., 1999, 212 p.

This article proposes a method for selecting of optimal oil field development system using a two-dimensional semi-analytical simulator, based on solving of Laplace equation for calculating pressure fields and using the Buckley – Leverett theory with the method of current lines for calculating saturation fields, taking into account the geological heterogeneity of the reservoir. The account of geological heterogeneity in the two-dimensional simulator is made by means of dependence of the grid coverage coefficient on length of the current line. The distribution of current line lengths in the three-dimensional hydrodynamic model characterizes the geometry of sand bodies and geological heterogeneity of the reservoir, and the value of the grid coverage coefficient numerically expresses this heterogeneity. This approach makes it possible to speed up the process of selecting the optimal parameters of development (density of the well grid, types of well completion, parameters of the hydraulic fracturing design on producing wells, half-length of fractures after auto-fracturing on injection wells, value of bottom-hole pressure on producing and injection wells, deformation coefficient for the grid of wells, etc.) at the decision-making stage. The parameter for choosing of the optimal development system, i.e. its optimal parameters, is the maximum value of the net present value when the conditions for achieving of the design oil recovery ratio are met. The calculation of economic parameters is carried out according to the dependencies inherent in the two-dimensional semi-analytical simulator, which allows the entire cycle of technical and economic analysis in one tool. In particular, this technique is extremely relevant for fields with low permeability and disjointed reservoir. Since the key feature of this approach is the account of geological heterogeneity.

References

1. Antonenko D.A., Pavlov V.A., Sevastyanova K.K. et al., Integrated modeling of the Priobskoe oilfield (In Russ.), SPE-117413-RU, 2008, https://doi.org/10.2118/117413-RU.

2. Sidel'nikov K.A., Vasil'ev V.V., Analysis of applications of mathematical modeling of reservoir systems based on the streamline method (In Russ.), Neftegazovoe delo, 2005, no. 1.

3. Chawathé A., Taggart I., Insights into upscaling using 3D streamlines,

SPE-88846-PA, 2004, https://doi.org/10.2118/88846-PA.

4. Ates H. et al., Ranking and upscaling of geostatistical reservoir models using streamline simulation: A field case study, SPE-81497-MS, 2003, https://doi.org/10.2118/81497-MS.

5. Portella R.C.M., Hewett T.A., Upscaling, gridding, and simulating using streamtubes, SPE-65684-PA, 2000, https://doi.org/10.2118/65684-PA.

6. Baker R.O., Kuppe F., Chugh S. et al., Full-field modeling using streamline-based simulation: 4 case studies, SPE-66405-MS, 2001, https://doi.org/10.2118/66405-MS.

7. Idrobo E.A., Choudhary M.K., Datta-Gupta A., Swept volume calculations and ranking of geostatistical reservoir models using streamline simulation,

SPE-62557-MS, 2000, https://doi.org/10.2118/62557-MS.

8. Viktorov E.P., Nurlyev D.R., Rodionova I.I., Tight reservoir simulation study under geological and technological uncertainty (In Russ.), Neftyanoe khozyaystvo = Oil Industry, 2018, no. 10, pp. 60–63.

9.  Willhite G.P., Waterflooding, SPE Textbook Series, 1986.

10. Baykov V.A., Zhdanov R.M., Mullagaliev T.I., Usmanov T.S., Selecting the optimal system design for the fields with low-permeability reservoirs (In Russ.), Neftegazovoe delo, 2011, no. 1, pp. 84–97.

11. Rabtsevich C.A., Kolonskikh A.V., Mustafin R.Kh., Kostrigin I.V., Designing of oilfield development using software package RN-KIN (In Russ.), Vestnik PAO “Rosneft'”, 2014, no. 2, pp. 8–13.

12. Krylov A.P., Sostoyanie teoreticheskikh rabot po proektirovaniyu razrabotki neftyanykh mestorozhdeniy i zadachi po uluchsheniyu etikh rabot (The state of theoretical work on the design of oil fields and the tasks to improve these works), Collected papers “Opyt razrabotki neftyanykh mestorozhdeniy i zadachi po uluchsheniyu etikh rabot” (Experience in the development of oil fields and tasks to improve these works), Moscow: Gostoptekhizdast Publ., 1957, pp. 116–139.

13. Muskat M., The flow of homogeneous fluids through porous media, McGraw-Hill, New York, 1937.

14. Kanevskaya R.D., Matemeticheskoe modelirovanie razrabotki mestorozhdeniy nefti i gaza s primeneniem gidravlicheskogo razryva plasta (Mathematical modeling of the development of oil and gas using hydraulic fracturing), Moscow: Nedra-Biznestsentr Publ., 1999, 212 p.


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