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Modeling pressure and saturation distribution in a CO 2 storage project using a Surrogate Reservoir Model (SRM)

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  • Alireza Shahkarami
  • Shahab Mohaghegh
  • Vida Gholami
  • Alireza Haghighat
  • Daniel Moreno

Abstract

Capturing carbon dioxide (CO 2 ) from large point sources and depositing it in a geological formation is an efficient way of decreasing CO 2 concentration in the atmosphere. A comprehensive study is required to perform a safe and efficient CO 2 capture and storage (CCS) project. The study includes different steps, such as selecting proper underground storage and keeping track of CO 2 behavior in the storage environment. Numerical reservoir simulators are the conventional tools used to implement such an analysis. The intricacy of simulating multiphase flow, having a large number of time steps required to study injection and post‐injection periods of CO 2 sequestration, a highly heterogeneous reservoir, a large number of wells, etc., will lead to a complicated reservoir model. A single realization for such a reservoir takes hours to run. Additionally, a thorough understanding of the CO 2 sequestration process requires multiple realizations of the reservoir model. Consequently, using a conventional numerical simulator makes the computational cost of the analysis too high to be practical. In this paper, we examine the application of a relatively new technology, the Surrogate Reservoir Model (SRM), as an alternative tool to solve the aforementioned problems. SRM is a replica of full‐field reservoir simulation models. It can generate outputs in a very short time with reasonable accuracy. These characteristics make SRM a unique tool in CO 2 sequestration modeling. This paper proposes developing an SRM for a CO 2 sequestration project ongoing in the SACROC unit to model pressure behavior and phase saturation distributions during different time steps of the CO 2 storage process.

Suggested Citation

  • Alireza Shahkarami & Shahab Mohaghegh & Vida Gholami & Alireza Haghighat & Daniel Moreno, 2014. "Modeling pressure and saturation distribution in a CO 2 storage project using a Surrogate Reservoir Model (SRM)," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 4(3), pages 289-315, June.
  • Handle: RePEc:wly:greenh:v:4:y:2014:i:3:p:289-315
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    File URL: http://hdl.handle.net/10.1002/ghg.1414
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    Cited by:

    1. Menad Nait Amar & Noureddine Zeraibi & Ashkan Jahanbani Ghahfarokhi, 2020. "Applying hybrid support vector regression and genetic algorithm to water alternating CO2 gas EOR," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(3), pages 613-630, June.

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