|
Abstract.
The forecasting of oil production rates is one of the most important problems of reservoir engineering, and the efficiency of flooding management, as well as the development of the field as a whole, directly depends on the quality of its solution. Traditionally used 3D hydrodynamic models often do not allow obtaining modeling results promptly, and the quality of forecasts significantly depends on the adequacy of the geological model used (which is usually constructed using highly uncertain data) to the actual development object. As a result, there is a demand among reservoir engineers for simpler forecasting tools, an example of which is capacitance-resistivity modeling (CRM), as a special case of material balance models. Along with traditional CRM models applicable only to water and oil production, some modifications of such models have been described that also allow to take into account the influence of gas as a separate phase. Such models can improve the accuracy of connectivity factors estimations and such important parameters as compensation and the injection efficiency of each injector. However, methods for obtaining of oil flow rate forecasts using such models are not obvious. This article proposes one of the possible methods that allows to improve the accuracy of oil production forecasts obtained using CRM modeling by taking into account the of free gas production rates.
Keywords:
Capacitance-Resistance Models, CRM, material balance models, hydrodynamic modeling, gas-oil ratio, sub-gas zones.
DOI 10.14357/20718632250110
EDN XXTFDA
PP. 106-115.
References
1. Stepanov S.V., Sokolov S.V., Ruchkin A.A., Stepanov A.V., Knyazev A.V., Korytov A.V. Considerations on mathematical modeling of producer-injector interference // Tyumen state university herald. Physical and mathematical modeling. Oil, gas, energy. 2018. Vol 4. № 3. p. 146-164. [In Russian]. 2. Holanda R.W., Gildin E., Jensen J.L., Lake L.W., Kabir C. S. 2018. A State-of-the-Art Literature Review on Capacitance Resistance Models for Reservoir Characterization and Performance Forecasting // Energies, 2018. URL: https://www.mdpi.com/1996-1073/11/12/3368/html. 3. Bekman A. D., Stepanov S.V., Ruchkin A.A., Zelenin D.V. A new algorithm for finding crm-model coefficients CRM // Tyumen state university herald. Physical and mathematical modeling. Oil, gas, energy. 2019. Vol 5. № 3. p. 164-185. DOI: 10.21684/2411-7978-2019-5-3-164-185. [In Russian]. 4. Holanda, Rafael Wanderley, Gildin, Eduardo and Jerry L. Jensen. Improved Waterflood Analysis Using the Capacitance-Resistance Model Within a Control Systems Framework // Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Quito, Ecuador, November 2015. doi: https://doi.org/10.2118/177106-MS. 5. Sayarpour M. Development and Application of Capacitance-Resistive Models to Water/CO2 Floods. Ph.D // Dissertation, 2008. 6. Alghamdi, Ahmed, Hiba, Moaz, Aly, Moustafa, and Abeeb Awotunde A Critical Review of Capacitance-Resistance Models // Paper presented at the SPE Russian Petroleum Technology Conference, Virtual, October 2021. doi: https://doi.org/10.2118/206555-MS. 7. Stepanov S.V. Stepanov A.V., Eletskiy S.V. Numerical-analytical approach towards salvation of the problem relating to on-line prediction of an oil well operation in conditions of a gas cone formation // Neftepromyslovoe delo. 2013. № 2. p. 53-58. [In Russian]. 8. Afanaskin I.V., Kolevatov A.A., Glushakov A.A., Yalov P.V. Consideration of non-linear deformation of the void space in the crm-model when analyzing the development of a gas deposit for depletion // Geologiya, geofizika i razrabotka neftyanykh i gazovykh mestorozhdeniy. – 2023. – № 2(374). – p. 59-65. – DOI 10.33285/2413-5011-2023-2(374)-59-65. – EDN STXKDX. [In Russian]. 9. 21. Baykov I.V., Kashnikov O.Yu., Gatin R.I., Khanov A.V., Dan'ko M.Y. Forecasting the operation of wells in the bazhenov formation based on a modified dynamic material balance model // PRONEFT'. Professional'no o nefti. 2021; 6(4), pp:106–115. https://doi.org/10.51890/2587-7399-2021-6-4-106-115. [In Russian]. 10. Bekman A.D., Ruchkin A.A. Method for assessing well interference at under-gas cap zone using CRM material balance model // Tyumen state university herald. Physical and mathematical modeling. Oil, gas, energy. – 2024. – Vol. 10. № 1 (37). С. 155–173. https://doi.org/10.21684/2411-7978-2024-10-1-155-173 11. Bekman A.D., Pospelova T.A., Zelenin D.V. A new approach to water cut forecasting based on results of capacitance resistance // Tyumen state university herald. Physical and mathematical modeling. Oil, gas, energy. - 2020. - Vol. 6, № 1 (21). - p. 192-207. - DOI: 10.21684/2411-7978-2020-6-1-192-207/
|