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Abstract

Summary

In well location optimization, the appropriate selection of initial guess for the optimization algorithms can reduce the required number of simulation runs. In this research, the idea of well location optimization based on pressure gradient distribution in the reservoir for CO2 injection is presented. Targets are those with low absolute pressure gradients leading to the areas minimally influenced by the existing injection wells.

The pressure profile of a steady-state case is applied to define the objective function based on the pressure gradient and superposition principle. The numerical active set method is implemented for the optimization algorithm as it can include the effect of multiple wells and linear boundaries. In a simple reservoir of fixed properties, this corresponds to the optimum well location for injection or production, whereas in a reservoir with variable properties, the result is an initial guess for the optimization process. The optimization algorithm is addressed for two scenarios including two and four CO2 injection wells.

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/content/papers/10.3997/2214-4609.202021034
2020-11-16
2024-04-28

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References

  1. Cameron, David A., and Louis J.Durlofsky
    . [2012]. Optimization of Well Placement, CO2 Injection Rates, and Brine Cycling for Geological Carbon Sequestration.International Journal of Greenhouse Gas Control10: 100–112. https://doi.org/10.1016/j.ijggc.2012.06.003.
     [Google Scholar]
  2. Dake, L.P.
    [1998]. Fundamentals of Reservoir Engineering. 17th ed. Amsterdam: Elsevier.
     [Google Scholar]
  3. Everdingen, A.F. Van, and W.Hurst
    . [1949]. The Application of the Laplace Transformation to Flow Problems in Reservoirs.Journal of Petroleum Technology1(12): 305–24. https://doi.org/10.2118/949305-g.
     [Google Scholar]
  4. Fanchi, John R.
    [2010]. Integrated Reservoir Asset Management Principles and Best Practices.
     [Google Scholar]
  5. Goda, Takashi, and KozoSato
    . [2013]. Global Optimization of Injection Well Placement toward Higher Safety of CO2 Geological Storage.Energy Procedia37: 4583–90. https://doi.org/10.1016/j.egypro.2013.06.366.
     [Google Scholar]
  6. Griva, Igor, Stephen G.Nash, and ArielaSofer
    . [2009]. Linear and Nonlinear Optimization.Linear and Nonlinear Optimization. https://doi.org/10.1137/1.9780898717730.
     [Google Scholar]
  7. Humphries, Thomas D., Ronald D.Haynes, and Lesley A.James
    . [2014]. Simultaneous and Sequential Approaches to Joint Optimization of Well Placement and Control.Computational Geosciences18 (3–4): 433–48. https://doi.org/10.1007/s10596-013-9375-x.
     [Google Scholar]
  8. Islam, Jahedul, Pandian M.Vasant, Berihun MamoNegash, Moacyr BartholomeuLaruccia, MyoMyint, and JunzoWatada
    . [2020]. A Holistic Review on Artificial Intelligence Techniques for Well Placement Optimization Problem.Advances in Engineering Software141 (December 2019): 102767. https://doi.org/10.1016/j.advengsoft.2019.102767.
     [Google Scholar]
  9. Jun, Changhyeok, MinKim, and HyundonShin
    . [2019]. Optimization of Well Placement and Operating Conditions for Various Well Patterns in CO2 Sequestration in the Pohang Basin, Korea.International Journal of Greenhouse Gas Control90 (August): 102810. https://doi.org/10.1016/j.ijggc.2019.102810.
     [Google Scholar]
  10. Onwunalu, Jérôme E., and Louis J.Durlofsky
    . [2010]. Application of a Particle Swarm Optimization Algorithm for Determining Optimum Well Location and Type.Computational Geosciences14(1): 183–98. https://doi.org/10.1007/s10596-009-9142-1.
     [Google Scholar]
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Well Placement Optimization Based on Pressure Gradient Distribution; Applicable to CO2 Sequestration
Conference Proceedings 2020, 1 (2020); https://doi.org/10.3997/2214-4609.202021034
/content/papers/10.3997/2214-4609.202021034
/content/papers/10.3997/2214-4609.202021034
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