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Case-Based Reasoning and Ontology-Based Approach to Selecting Equipment Solutions in Oilfield Engineering

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Artificial Intelligence in Models, Methods and Applications (AIES 2022)

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 457))

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Abstract

Increased difficulty of engineering problems require new approaches, which would combine automation and intellectual support in decision-making. Oil and gas engineering is a complex combination of interconnected areas from producing oil to supplying it to consumers. A key milestone in developing an oil and gas asset is conceptual engineering stage, which includes selecting equipment that has optimal characteristics to meet requirements and operating conditions, which ultimately defines capital investments in the overall cost structure. The article presents an algorithm for automatic configuration of oil and gas equipment, which uses a case-based approach and an ontology model that can support decision-making in field development conceptual design. Using the Protégé ontology editor, the authors created an ontology of standard infrastructure solutions based on oil and gas assets’ data, which includes hierarchies of classes and instances. The list of pad facilities formed using the SPARQL Query language has proved efficient for automated search of necessary information when solving engineering problems.

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Author information

Authors and Affiliations

  1. Systems Engineering Center, Polytechnic School, University of Tyumen, Tyumen, 625003, Russia

    Igor Glukhikh, Mikhail Pisarev, Dmitry Liss, Anastasia Shestakova & Kristina Nonieva

Authors
  1. Igor Glukhikh
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  2. Mikhail Pisarev
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  3. Dmitry Liss
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  4. Anastasia Shestakova
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  5. Kristina Nonieva
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Corresponding author

Correspondence to Kristina Nonieva .

Editor information

Editors and Affiliations

  1. Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Olga Dolinina

  2. Saint Petersburg, Russia

    Igor Bessmertny

  3. Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexander Brovko

  4. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  5. Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Vitaly Pechenkin

  6. Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexey Lvov

  7. Technical Science, Novosibirsk Institute of the Software Systems, Novosibirsk Oblast, Russia

    Vadim Zhmud

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Glukhikh, I., Pisarev, M., Liss, D., Shestakova, A., Nonieva, K. (2023). Case-Based Reasoning and Ontology-Based Approach to Selecting Equipment Solutions in Oilfield Engineering. In: Dolinina, O., et al. Artificial Intelligence in Models, Methods and Applications. AIES 2022. Studies in Systems, Decision and Control, vol 457. Springer, Cham. https://doi.org/10.1007/978-3-031-22938-1_10

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