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An approach to forecast production profiles, oil-gas ratio and water contamination probabilistic assessment

https://doi.org/10.37493/2308-4758.2024.3.7

Abstract

An approach to probabilistic assessment of field development forecast parameters for gas-condensate reservoir using multi­variant simulation was studied. The necessity of such decision may be explained by the aim to level the influence of large number of uncertainties which occur during the work with res­ervoir simulation models. «tNavigator» software was used as the main instrument since it provides wide functionality in the sphere of interest. The variants of variables implementation were studied, the review of experimental designs and optimiza­tion algorithms was done. At the first step, the simulation model was history matched using Differential Evolution algorithm, since its initial version had problems with phase withdrawals and pressure dynamics. Corresponding history matching qual­ity was controlled by specially generated objective function val­ues. At the second step a series of production forecasts based on the best history matching cases was calculated; cumulative distribution functions for field development parameters under consideration were received to get the necessary probabilistic assessment. As a result, the workflow for values of interest get­ting was provided; also, the variants of further modifications for studied approach were formulated: the number of simulation runs can be decreased through the choice of three base vari­ants and use of multi-dimensional scaling which provides the opportunity for realizations of equal probability clustering with further choice of representative cases.

About the Authors

D. V. Balin
Industrial University of Tyumen
Russian Federation

Daniil V. Balin — Postgraduate student

38, Volodarskogo St., Tyumen, 625000



O. V. Balina
Industrial University of Tyumen
Russian Federation

Olga V. Balina — PhD in Technical Sciences, Associate Professor, Associate Professor

38, Volodarskogo St., Tyumen, 625000



E. I. Mamchistova
Industrial University of Tyumen
Russian Federation

Elena I. Mamchistova — PhD in Technical Sciences, Associate Professor, Pro­fessor

38, Volodarskogo St., Tyumen, 625000



References

1. Kozyrev ND,VishnyakovAYu,Putilov IS.Assessment of the uncertainty parameters influence on the development indicators forecasting. Nedropolzovanie = Subsoil use. 2020;20(4):356-368. (In Russ.). https://doi.org/10.15593/2712-8008/2020.4.5

2. Andronov SA, Gorenkova EA, Gomonov AA, Maksimenko IA. Approaches to selection of realizations in probabilistic modeling of geological model and analysis of influence on forecast production profile. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2023;8(4):25-32. (In Russ.). https://doi.org/10.51890/2587-7399-2023-8-4-25-32

3. Shisahev GYu, Matveev IV, Erenyan GA. Geologically justified assisted history matching of flow models using real field as an example. Neftyanoe hozyajstvo = Oil industry. 2020;6:58-61. (In Russ.).

4. Syrtlanov V, Golovatskiy Y, Ishimov I, Mezhnova N. Assisted history matching for reservoir simulation models. SPE Russian Petroleum Technology Conference. Moscow, Russia. October 2019. https://doi.org/10.2118/196878-MS

5. Smetkina MA, Melkishev OA, Prisyaznyuk МA. Refining the values of permeability when adapting the hydrodynamic model. Nedropolzovanie = Subsoil use. 2020;20(3):223-230. (In Russ.) https://doi.org/10.15593/2712-8008/2020.3.3

6. tNavigator 24.2. AHM and Uncertainty. User guide. July 2024.

7. Makarichev YuA, Ivannikov YuN. Methods of experimental design and data processing: technical manual. Samara: Samara State Technical University; 2016. 131 p. (In Russ.).

8. Simonov MV, PeniginAV, MargaritAS, Pustovskikh АA, Smirnov NA, Sitnikov AN. Methodology of surrogate Models (MetaModels) and their prospects for solving petroleum engineering challenges. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2019;2(12):49-53. (In Russ.).

9. Mohamed L, Christie M., Demyanov V. History Matching and Uncertainty Quantification: Multiobjective Particle Swarm Optimisation Approach. SPE 143067. Vienna, Austria, 23-26 May 2011.

10. Nelder JA, Mead R. A simplex method for function minimization. Comput. J. 1965;7:308.

11. Kathrada M. Uncertainty evaluation of reservoir simulation models using particle swarms and hierarchical clustering. Doctoral dissertation. Heriot-Watt University; 2009. 221 p.

12. Amirian E, Fedutenko E, Yang C, Chen Z, Nghiem L. Artificial neural network modeling and forecasting of oil reservoir opperformance. Springer. Cham. 2018.

13. Evensen G. Data assimilation: The ensemble Kalman filter. Springer, NY; 2007.

14. Pospelova ТА. The development of methods of well work regulation based of digital technologies: author’s summary of dissertation of doctor of technical sciences. Tyumen: Industrial University of Tyumen; 2021. 48 p.

15. Emil C. Santhosh, Jitendra S. Sangwai. A hybrid differential evolution algorithm approach towards assisted history matching and uncertainty quantification for reservoir models. Journal of Petroleum Science and Engineering. 2016;142:21-35.

16. Jianwei Gu, Wei Liu, Kai Zhang, Liang Zhai, Yigen Zhang, Fuzhen Chen. Reservoir production optimization based on surrogate model and differential evolution algorithm. Journal of Petroleum Science and Engineering. 2021;205:108879.

17. Hajizadeh Y, Christie M, Demyanov V. Application of differential evolution as a new method for automatic history matching. https://doi.org/10.2118/127251-MS

18. Stepanov SV, Bekman AD, Ruchkin AA, Pospelova TA Oil field development support using CRM models. Tyumen: IPC “Express”; 2021. 300 p. (In Russ.).

19. Spirina EA, Davydov IV, Sazonov DN, Taranin RM, Kamaletdinov RH. Express assessment of the choice of optimal parameters of the development system under the conditions of geological uncertainty. PRONEFT. Proffesionalno o nefti = PRONEFT. Professionally about oil. 2023;8(2):165-175. (In Russ.). https://doi.org/10.51890/2587-7399-2023-8-2-165-175

20. Kanevskaya RD. Mathematical modelling of hydrodynamic processes of hydrocarbon fields development. Moscow-Izhevsk: Institute of computer research; 2002. 140 p. (In Russ.)


Review

For citations:


Balin D.V., Balina O.V., Mamchistova E.I. An approach to forecast production profiles, oil-gas ratio and water contamination probabilistic assessment. Science. Innovations. Technologies. 2024;(3):139-156. (In Russ.) https://doi.org/10.37493/2308-4758.2024.3.7

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ISSN 2308-4758 (Print)