Prediction of reservoir pressure and study of its behavior in the development of oil fields based on the construction of multilevel multidimensional probabilistic-statistical models

Determination of the current reservoir pressure in oil production wells selection zones is an urgent task of field development monitoring. The main method for its determination is hydrodynamic studies under unsteady conditions. At the same time, the process of restoring bottomhole pressure to the value of reservoir pressure often lasts a significant period of time, which leads to long downtime of the fund and significant shortfalls in oil production. In addition, it seems rather difficult to compare reservoir pressures with each other in the wells due to the different timing of the studies, since it is impossible to simultaneously stop the entire fund for measuring the reservoir pressure in the field. The article proposes a new method for determining the current reservoir pressure in the extraction zones, based on the construction of multidimensional mathematical models using the data of geological and technological development indicators. As the initial data, the values of reservoir pressure, determined during processing of the materials of hydrodynamic studies of wells, as well as a set of geological and technological indicators, probably affecting its value, were used (initial reservoir pressure for each well, the duration of its operation at the time of study, liquid rate, bottomhole pressure, the initial permeability and the current collector in the drainage area, GOR accumulated values oil, and liquid water, and skin factor). In the course of the research, several variants of statistical modeling were used, in the process of which the regularities of the reservoir pressure behavior during the development of reserves were established, individual for the object of development. The obtained models are characterized by a high degree of reliability and make it possible to determine the desired value with an error of no more than 1.0 MPa.

1. Aaditya Khanal, Mohammad Khoshghadam, W. John Lee, Michael Nikolaou (2017). New forecasting method for liquid rich shale gas condensate reservoirs with data driven approach using principal component analysis. Journal of Natural Gas Science and Engineering, 38, pp. 621–637. https://doi.org/10.1016/j.jngse.2017.01.014

2. Abrosimov A.A., Shelyago E.V., Yazinina I.V. (2018). Substantiation of a representative volume of reservoir properties data to obtain statistically reliable petrophysical relationships. Zapiski Gornogo instituta = Journal of Mining Institute, 233, pp. 487–491. (In Russ.). https://doi.org/10.31897/pmi.2018.5.487

3. Ahmadi R., Pourfatemi S.M., Ghaffari S. (2017). Exergoeconomic optimization of hybrid system of GT, SOFC and MED implementing genetic algorithm. Desalination, 411, pp. 76–88. https://doi.org/10.1016/j.desal.2017.02.013

4. Akinbinu V.A. (2010). Prediction of fracture gradient from formation pressures and depth using correlation and stepwise multiple regression techniques. Journal of Petroleum Science and Engineering, 72(1–2), pp. 10–17. https://doi.org/10.1016/j.petrol.2010.02.003

5. Chernykh I.A., Galkin V.I., Ponomareva I.N. (2017). Comparative analysis of the methods for defining bottomhole pressure at well operation of Shershnevsky field. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 328(8), pp. 41–47. (In Russ.)

6. D. Childers P.E., X. Wu PhD (2020). Forecasting oil well performance in tight formation using the connected reservoir storage model. Journal of Petroleum Science and Engineering, 195, 107593. https://doi.org/10.1016/j.petrol.2020.107593

7. Davydova A.E., Shchurenko A.A., Dadakin N.M., Shutalev A.D., Kvesko B.B. (2019). Well testing design development in carbonate reservoir. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 330(6), pp. 68–79. (In Russ.). https://doi.org/10.18799/24131830/2019/6/2128

8. Davydova A.E., Shchurenko A.A., Dadakin N.M., Shutalev A.D., Rvesco B.B. Optimization of carbonate reservoir well testing. Vestnik PNIPU. Geologiya. Neftegazovoe i gornoe delo = Bulletin of PNIPU. Geology. Oil and gas and mining, 17(2), pp. 123–135. (In Russ.). DOI: 10.15593/2224-9923/2018.2.3

9. Dragunov A.A., Mukhamadiev R.S., Chernov S.V. (2017). Influence of geodynamic processes on reservoir properties of geological environment (on the example of the Romashkino field). Georesources = Georesursy, 19(4), pp. 319–322. (In Russ.). https://doi.org/10.18599/grs.19.4.3

10. Dyagilev V.F., Lazutin N.K., Baksheev V.N. (2019). Approbation of the assessing methodology for the impact nature of water injection on oil samples using the example of the North-Orekhovsky field. SOCAR Proceedings, 1, pp. 42–51. (In Russ.). DOI: 10.5510/OGP20190100378

11. Elesin A.V., Kadyrova A.Sh., Nikiforov A.I. (2018). Definition of the reservoir permeability field according to pressure measurements on wells with the use of spline function. Georesources = Georesursy, 20(2), pp. 102–107. https://doi.org/10.18599/grs.2018.2.102-107

12. Escobar F.H., Hernandez Y.A., Hernandez C.M. (2007). Pressure transient analysis for long homogeneous reservoirs using TDS technique. Journal of Petroleum Science and Engineering, 58(1–2), pp. 68–82. https://doi.org/10.1016/j.petrol.2006.11.010

13. Galkin S.V., Kochnev A.A., Zotikov V.I. (2019). Estimate of radial drilling technology efficiency for the bashkir operational oilfields objects of Perm Krai. Zapiski Gornogo instituta = Journal of Mining Institute, 238, pp. 410–414. (In Russ.). https://doi.org/10.31897/pmi.2019.4.410

14. Galkin V.I., Ponomareva I.N., Chernykh I.A., Filippov E.V., Chumakov G.N. (2019). Methodology for estimating downhole pressure using multivariate model. Neftyanoe Khozyaystvo = Oil industry, 1, pp. 40–43. (In Russ.). DOI: 10.24887/0028-2448-2019-1-40-43

15. Karmanskiy D.A., Petrakov D.G. (2020). Laboratory modeling of changes in mechanical and flow properties of reservoir rocks at the stages of oil fields development. Vestnik PNIPU. Geologiya. Neftegazovoe i gornoe delo = Bulletin of PNIPU. Geology. Oil and gas and mining, 20(1), pp. 49–59. (In Russ.). DOI: 10.15593/2224-9923/2020.1.5

16. Kochnev A.A., Zotikov V.I., Galkin S.V. (2018). Analysis of the influence of geological technological parameters on the effectiveness of radial drilling technology on the example of operational objects in perm region. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 329(12), pp. 20–29. (In Russ.). https://doi.org/10.18799/24131830/2018/12/16

17. Martyushev D.A., Slushkina A.Yu. (2019). Assessment of informative value in determination of reservoir filtration parameters based on interpretation of pressure stabilization curves. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 330(10), pp. 26–32. (In Russ.). https://doi.org/10.18799/24131830/2019/10/2295

18. Nur Wijaya, James J. Sheng (2020). Probabilistic forecasting and economic evaluation of pressure-drawdown effect in unconventional oil reservoirs under uncertainty of water blockage severity. Journal of Petroleum Science and Engineering, 185, 106646. https://doi.org/10.1016/j.petrol.2019.106646

19. Olalere Oloruntobi, Stephen Butt (2019). Energy-based formation pressure prediction. Journal of Petroleum Science and Engineering, 173, pp. 955–964. https://doi.org/10.1016/j.petrol.2018.10.060

20. Ponomareva I.N., Martyushev D.A., Akhmetova M.I. (2016). Evaluation of the optimal duration of the hydrodynamic studies of low-productivity wells on the example of Ozernoye field. Neftyanoe Khozyaystvo = Oil industry, 1, pp. 60–63. (In Russ.)

21. Rastorguev M.N. (2019). Using discriminant analysis for the interpretation of gas logging data on the example of the Pavlov oil field. Vestnik PNIPU. Geologiya. Neftegazovoe i gornoe delo = Bulletin of PNIPU. Geology. Oil and gas and mining, 19(1), pp. 39–55. (In Russ.) DOI: 10.15593/2224-9923/2019.1.4

22. Saeed Rafieepour, Silvio Baldino, Stefan Z. Miska (2020). Determination of in-situ elastic properties and reservoir boundary conditions. Journal of Natural Gas Science and Engineering, 81, 103397. https://doi.org/10.1016/j.jngse.2020.103397

23. Salam Al-Rbeawi (2018). Integrated analysis of pressure response using pressure-rate convolution and deconvolution techniques for varied flow rate production in fractured formations. Journal of Natural Gas Science and Engineering, 51, pp. 195–209. https://doi.org/10.1016/j.jngse.2018.01.012

24. Valery B., Eslamloueyan R. (2015). Hydrocarbon reservoirs characterization by co-interpretation of pressure and flow rate data of the multi-rate well testing. Journal of Petroleum Science and Engineering, 135, pp. 59–72. https://doi.org/10.1016/j.petrol.2015.08.016

25. Virstyuk A.Yu., Mikshina V.S. (2020). Application of regression analysis to evaluate the efficiency of oil well operating with the paraffin oil. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov = Bulletin of the Tomsk Polytechnic University. Geo Assets Engineering, 331(1), pp. 117–124. (In Russ.). https://doi.org/10.18799/24131830/2020/1/2453