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Increasing the Reliability of Well Interaction Modeling for the Analysis of the Efficiency of the Flooding System

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Mathematical Models and Computer Simulations Aims and scope

Abstract

At present, to analyze the efficiency of the oil field flooding system, proxy models of the capacitance–resistive model (CRM) family are actively used: mathematical models of the material balance formulated in the framework of the electrodynamic analogy. However, with a large number of production and injection wells, the accuracy of modeling decreases due to the set of local minima of the target function. One of the reasons for this ambiguity of the solution is the lack of a priori information on which injection wells really affect a particular production well. The mask of mutual influence (interaction, interference) is determined, which makes it possible to significantly reduce the number of determined mutual influence coefficients. A computational algorithm is proposed in which, instead of solving a multiextremal problem, a sequence of problems with a quadratic target function and convex constraints on variables in the form of simple inequalities is solved. An example of the approbation of the proposed method is given.

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Authors and Affiliations

  1. Ural Federal University, Yekaterinburg, Russia

    A. N. Tyrsin

  2. Science and Engineering Center “Reliability and Resource of Large Systems and Machines” Ural Branch, Russian Academy of Sciences, Yekaterinburg, Russia

    A. N. Tyrsin

  3. OOO Tyumen Oil Research Center, Tyumen, Russia

    S. V. Stepanov, A. A. Ruchkin & A. D. Beckman

Authors
  1. A. N. Tyrsin
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  2. S. V. Stepanov
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  3. A. A. Ruchkin
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  4. A. D. Beckman
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Correspondence to A. N. Tyrsin, S. V. Stepanov, A. A. Ruchkin or A. D. Beckman.

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Tyrsin, A.N., Stepanov, S.V., Ruchkin, A.A. et al. Increasing the Reliability of Well Interaction Modeling for the Analysis of the Efficiency of the Flooding System. Math Models Comput Simul 15, 1092–1103 (2023). https://doi.org/10.1134/S2070048223060170

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  • DOI: https://doi.org/10.1134/S2070048223060170

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