Application of advanced CRMP for reservoir pressure mapping

Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy


Release:

2021. Vol. 7. № 4 (28)

Title: 
Application of advanced CRMP for reservoir pressure mapping


For citation: Bekman A. D., Zelenin D. V. 2021. “Application of advanced CRMP for reservoir pressure mapping”. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, vol. 7, no. 4 (28), pp. 163-180. DOI: 10.21684/2411-7978-2021-7-4-163-180

About the authors:

Alexander D. Bekman, Cand. Sci. (Phys.-Math.), Chief Project Engineer, Tyumen Petroleum Research Center; ORCID: 0000-0002-5907-523Xadbekman@rosneft.ru

Dmitry V. Zelenin, Senior Expert, Tyumen Petroleum Research Center; eLibrary AuthorID, ORCID: 0000-0002-5918-2377dvzelenin@rosneft.ru

Abstract:

The article discusses the issue of reservoir pressure mapping based on analytical producer-based representation of capacitance-resistance model (CRMP). The major hindrance of previous methods is in reconstruction of reservoir pressure dynamics in points where wells are located. Classic CRMP only allows performing measurement of reservoir pressure in the vicinity of producer wells. In order to reconstruct reservoir pressure dynamics near injector wells, the authors suggest application of advanced producer-based representation of capacitance-resistance model + tube model (CRMP-TM). As a result of adaptation of such model, influence of producer and injector wells is adjusted. Reservoir pressure in the vicinity of injector wells is determined while taking into account influence and flow rate obtained from traditional CRMP. The map of reservoir pressure is compiled based on solving Laplace’s equation. The obtained values of pressure by wells are considered as limiting conditions. The given article also demonstrates the results of numerical experiments conducted with application of hydrodynamic simulator. CRMP and CRMP-TM models were built on the basis of well performance indicators calculated on the hydrodynamic model (HDM). The reservoir pressure maps obtained in this way were compared with the maps obtained from the hydrodynamic model. As a result of numerical experiments, adequate consistency of model and actual reservoir pressure dynamics as well as reservoir pressure maps for the last time interval of the adjusting period were obtained.

References:

  1. Aziz Kh., Settari E. 1982. Mathematical Modelling of Reservoir-Type Systems. Moscow: Nedra. 408 p. [In Russian]

  2. Bekman A. D. 2021. Data for Verifying the Performance of the CRMP-TM. Accessed 13 October 2021. https://github.com/MaxFloat/CRMP-TM_verification [In Russian]

  3. Bekman A. D., Stepanov S. V., Ruchkin A. A., Zelenin D. V. 2019. “A new algorithm for finding CRM-model coefficients”. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, vol. 5, no 3, pp. 164-185. DOI: 10.21684/2411-7978-2019-5-3-164-185 [In Russian]

  4. Kosyakov V. P., Gubaidullin A. A., Legostaev D. Yu. 2019. “The method for modeling the development of a gas field on the basis of a hierarchy of mathematical models”. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, vol. 5, no 3, pp. 69-82. DOI: 10.21684/2411-7978-2019-5-3-69-82 [In Russian]

  5. Pospelova T. A., Zelenin D. V., Zhukov M. S., Bekman A. D., Ruchkin A. A. 2020. “Waterflooding optimization based on CRM”. Scientific and Technical Journal “Oilfield Business”, no. 7 (619), pp. 5-10. [In Russian]

  6. Pospelova T. A., Zelenin D. V., Ruchkin A. A., Bekman A. D. 2020. “Application of CRM for efficiency analysis of waterflooding”. Oil Province, no. 1 (21), pp. 97-108. DOI: 10.25689/NP.2020.1.97-108 [In Russian]

  7. Stepanov S. V. 2005. “Adaptation of hydrodynamic model of petroleum deposit based on solving the variational problems”. Mathematical Modelling, vol. 17, no. 12, pp. 110‑118. [In Russian]

  8. 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, vol. 11, no. 12. Accessed 13 October 2021. https://www.mdpi.com/1996-1073/11/12/3368/html

  9. Sayarpour M. 2008. “Development and application of capacitance-resistive models to Water/CO2 floods.” Dr. Sci. (Philos.) diss. The University of Texas at Austin.