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Smart Optimization of Proactive Control of Petroleum Reservoir

In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Hybrid Conference, Zagreb, Croatia, 9-10 September 2021

Author

Listed:
  • Kuk, Edyta
  • Kuk, Michał
  • Janiga, Damian
  • Wojnarowski, Paweł
  • Stopa, Jerzy

Abstract

Artificial Intelligence plays an increasingly important role in many industrial applications as it has great potential for solving complex engineering problems. One of such applications is the optimization of petroleum reservoirs production. It is crucial to produce hydrocarbons efficiently as their geological resources are limited. From an economic point of view, optimization of hydrocarbon well control is an important factor as it affects the whole market. The solution proposed in this paper is based on state-of-the-art artificial intelligence methods, optimal control, and decision tree theory. The proposed idea is to apply a novel temporal clustering algorithm utilizing an autoencoder for temporal dimensionality reduction and a temporal clustering layer for cluster assignment, to cluster wells into groups depending on the production situation that occurs in the vicinity of the well, which allows reacting proactively. Then the optimal control of wells belonging to specific groups is determined using an auto-adaptive decision tree whose parameters are optimized using a novel sequential model-based algorithm configuration method. Optimization of petroleum reservoirs production translates directly into several economic benefits: reduction in operation costs, increase in the production effectiveness and increase in overall income without any extra expenditure as only control is changed.

Suggested Citation

  • Kuk, Edyta & Kuk, Michał & Janiga, Damian & Wojnarowski, Paweł & Stopa, Jerzy, 2021. "Smart Optimization of Proactive Control of Petroleum Reservoir," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2021), Hybrid Conference, Zagreb, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Hybrid Conference, Zagreb, Croatia, 9-10 September 2021, pages 297-306, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
  • Handle: RePEc:zbw:entr21:262256
    DOI: 10.54820/ASQF9458
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    References listed on IDEAS

    as
    1. Michał Kuk & Edyta Kuk & Damian Janiga & Paweł Wojnarowski & Jerzy Stopa, 2020. "Optimization Wells Placement Policy for Enhanced CO 2 Storage Capacity in Mature Oil Reservoirs," Energies, MDPI, vol. 13(16), pages 1-20, August.
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    More about this item

    Keywords

    hydrocarbon wells production; control optimization; artificial intelligence; temporal clustering; auto-adaptive decision tree;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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