Neftyanaya Provintsiya
electronic peer-reviewed scholarly publication
Neftyanaya provintsiya No. 1(37), 2024

Testing the CRM model adaptation based on hydrodynamic modeling data

T.A. Nafikov, M.N. Khanipov
DOI: https://doi.org/10.25689/NP.2024.1.139-152

Abstract


The article describes the experience of testing adaptation quality of an analytical CRM model (Capacity Resistance Model) to the simple oil-development object hydrodynamic simulator data. The simulation object is a three–layer homogeneous oil reservoir with various vertical permeability and homogeneous horizontal permeability. Well stock contains one injector and eight producers arranged in a nine–point waterflooding pattern. The duration of a simulation is 187 steps, the calculation step equals 1 month. Several different simulations of the hydrodynamic model with different well constraints have been carried out, namely: constant and variable injection rate, constant flow rate and constant bottom-hole pressure maintenance constraint. For each simulation case CRM models have been calculated then graphs have been analyzed and conclusions have been made. The purpose of the study is to use synthetic data testing to determine the performance of the CRM model and its potential suitability for real data handling.

Key words:

Capacity Resistance Model, hydrodynamic models, analytical models, mathematical modeling, proxy modeling, oil reservoir, synthetic data, modeling, well constraints, well operation

References

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Authors

T.A. Nafikov, PhD Student, Chair for Oil and Gas Fields Development, Almetyevsk State Oil Institute
2 Lenin st., Almetyevsk, 423450, Russian Federation

M.N. Khanipov, Head of Group for Design and Supervision of Automated Databases, IT Development and Reservoir Modeling Department, TatNIPIneft Institute – PJSC TATNEFT
32 Djalil st., Bugulma, 423200, Russian Federation

For citation:

T.A. Nafikov, M.N. Khanipov Testirovaniye adaptatsii CRM modeli na dannykh gidrodinamicheskogo modelirovaniya [Testing the CRM model adaptation based on hydrodynamic modeling data]. Neftyanaya Provintsiya, No. 1(37), 2024. pp. 139-152. DOI https://doi.org/10.25689/NP.2024.1.139-152. EDN PJIUKP (in Russian)

© Non-governmental organization Volga-Kama Regional Division of the Russian Academy of Natural Science, 2015-2024 All the materials of the journal are available under the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)