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Abstract

Summary

The Integrated Capacitance Resistive Model (ICRM), a linearized form of Capacitance Resistive Models (CRM), has been commonly used to match liquid production history and estimate interwell connectivity (IWC) in waterflooded reservoirs. Although this model fits cumulative production data accurately, it usually fails to estimate correct values of total production, where backward subtraction of cumulative production delivers highly overestimated or underestimated total production rates. To address this issue, a multi-objective optimization approach is employed to minimize the error between both cumulative and total production data through two consecutive constrained objective functions. This paper validates the modified ICRM in a homogeneous synthetic reservoir to show how the new approach can successfully characterize the waterflooded reservoirs and forecast future production performance. The proposed data-driven approach has been tested on damaged formations to investigate the impact of skin factor, as a key component of formation damage, on the dynamic communication between wells. A correlation is proposed to explain the mathematical and physical relationship between formation damage and interwell connectivity of production wells.

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/content/papers/10.3997/2214-4609.202010012
2020-12-08
2024-04-26

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References

  1. AlejandroAlbertoni, and Larry W.Lake
    , 2002. “Inferring interwell connectivity from well-rate fluctuations in waterfloods.” SPE/DOE Improved Oil Recovery Symposium.
     [Google Scholar]
  2. Ali AYousef, Larry WayneLake, and Jerry LJensen
    . 2006. “Analysis and interpretation of interwell connectivity from production and injection rate fluctuations using a capacitance model.” SPE/DOE Symposium on Improved Oil Recovery.
     [Google Scholar]
  3. CenkTemizel, MohammadSalehian, MuratCinar, Ihsan MuratGok, and Mohamad Y.Alklih
    . 2018. “A Theoretical and Practical Comparison of Capacitance-Resistance Modeling with Application to Mature Fields.” SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition. Society of Petroleum Engineers.
     [Google Scholar]
  4. CMG, IMEX
    . 2017. “Advanced OI/Gas Reservoir Simulator version 2017 User’s Guide.” Computer Modelling Group LTD.
     [Google Scholar]
  5. Kim, Jong Suk
    . 2011. “Development of linear capacitance-resistance models for characterizing waterflooded reservoirs.”, M.Sc. Dissertation, University of Texas at Austin.
     [Google Scholar]
  6. MohammadSalehian, and MuratÇınar
    , 2019. “Reservoir characterization using dynamic capacitance– resistance model with application to shut-in and horizontal wells”. Journal of Petroleum Exploration and Production Technology, pp.1–20.
     [Google Scholar]
  7. MohammadSalehian, CenkTemizel, Ihsan MuratGok, MuratCinar, and Mohamed YousefAlklih
    . 2018. “Reservoir Management Through Characterization of Smart Fields Using Capacitance-Resistance Models”. Abu Dhabi International Petroleum Exhibition & Conference. Society of Petroleum Engineers.
     [Google Scholar]
  8. SevdaNorouzi, RasaSoleimani, Mehrdad VasheghaniFarahani, and Mohammad RezaRasaei
    , 2019. Pore-Scale Simulation of Capillary Force Effect in Water-Oil Immiscible Displacement Process in Porous Media. In 81st EAGE Conference and Exhibition 2019.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202010012
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Waterflood Analysis in Damaged Formations Using a Multi-Objective Capacitance Resistance Model
Conference Proceedings 2020, 1 (2020); https://doi.org/10.3997/2214-4609.202010012
/content/papers/10.3997/2214-4609.202010012
/content/papers/10.3997/2214-4609.202010012
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