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Multi-layered Satisficing Decision Making in Oil and Gas Production Platforms

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Advances on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2013)

Abstract

From a control perspective, offshore oil and gas production is very challenging due to the many and potentially conflicting production objectives that arise from the intrinsic complexity of the oil and gas domain. In this paper, we show how a multi-layered multi-agent system can be used to implement a satisficing decision-making process for allocation of production resources. Through simulations using real-world production data, we illustrate that this satisficing decision-making process performs better than existing control systems applied on marginal fields, even though satisficing decision making often only provides near-optimal solutions.

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References

  1. NORSOK Standard I-002: Safety and automation system (SAS). Rev. 2 (2001)

    Google Scholar 

  2. Bonavita, N.: Performance Excellence in the Upstream Industry. In: 10th Mediterranean Petroleum Conference, Tripoli, Libya (2008)

    Google Scholar 

  3. Mohaghegh, S.D.: Recent Development in Application of Artificial Intelligence in Petroleum Engineering. Journal of Petroleum Science and Engineering, 239–260 (2005)

    Google Scholar 

  4. Bieker, H.P., Slupphaug, O., Johansen, T.A.: Real-Time Production Optimization of Offshore Oil and Gas Production Systems - A Technology Survey. In: SPE Intelligent Energy Conference and Exhibition, Amsterdam, NL (2006)

    Google Scholar 

  5. Ølmheim, J., Landre, E., Spillum, Ø., Hepsø, V.: Decision Support and Monitoring Using Autonomous Systems. In: SPE Intelligent Energy Conference and Exhibition, Utrecht, NL (2010)

    Google Scholar 

  6. Wartmann, M.R., Gunnerud, V., Foss, B.A., Ydstie, B.E.: Distributed optimization and control of offshore oil production: The intelligent platform. In: FOCAPO 2008, Boston, USA (2008)

    Google Scholar 

  7. Jennings, N.R., Mamdani, E.H., Corera, J.M., Laresgoiti, I., Perriolat, F., Skarek, P., Varga, L.Z.: Using ARCHON to develop real-word DAI applications. IEEE Expert 11(6), 64–70 (1996)

    Article  Google Scholar 

  8. Demazeau, Y.: From Cognitive Interactions to Collective Behaviour in Agent-Based Systems. In: 1st European Conference on Cognitive Science, Saint-Malo, France, pp. 117–132 (1995)

    Google Scholar 

  9. Boissier, O., Demazeau, Y.: ASIC: An Architecture for Social and Individual Control and its Application to Computer Vision. In: Perram, J., Müller, J.P. (eds.) MAAMAW 1994. LNCS (LNAI), vol. 1069, pp. 135–149. Springer, Heidelberg (1996)

    Google Scholar 

  10. Chappin, E.J.L., Dijkema, G.P.J., van Dam, K.H., Lukszo, Z.: Modelling strategic and operational decision-making—an agent-based model of electricity producers. In: The 2007 European Simulation and Modelling Conference, pp. 356–363 (2007)

    Google Scholar 

  11. Barbuceanu, M., Fox, M.S.: The architecture of an agent based infrastructure for agile manufacturing. In: Proceedings of IJCAI (1995)

    Google Scholar 

  12. Sørensen, J.C., Jørgensen, B.N., Klein, M., Demazeau, Y.: An agent-based extensible climate control system for sustainable greenhouse production. In: Kinny, D., Hsu, J.Y.-j., Governatori, G., Ghose, A.K. (eds.) PRIMA 2011. LNCS (LNAI), vol. 7047, pp. 218–233. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Simon, H.A.: Rational choice and the structure of the environment. Psychological Review 63(2), 129–138 (1956)

    Article  Google Scholar 

  14. Definition source, http://www.businessdictionary.com/definition/satisficing.html

  15. Jackson, M.: Problem Frames: Analysing & Structuring Software Development Problems. Addison-Wesley (2001) ISBN-10 0-201-59627-X

    Google Scholar 

  16. Jackson, M.: The World and the Machine. In: Proceedings of the 17th International Conference on Software Engineering, pp. 283–292 (1995)

    Google Scholar 

  17. Mikkelsen, L.L., Jørgensen, B.N.: Towards Next Generation of Smart Fields Using Intelligent Online Multi-Objective Control. In: POSE 2012, Doha, Qatar, SPE 156946 (2012)

    Google Scholar 

  18. Mikkelsen, L.L., Jørgensen, B.N.: Applying Multi-agent Systems to Multi-objective Simulation and Control for Offshore Oil and Gas Production. In: RACS 2012, San Antonio, Texas, USA, pp. 376–382 (2012)

    Google Scholar 

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Lindegaard Mikkelsen, L., Demazeau, Y., Jørgensen, B.N. (2013). Multi-layered Satisficing Decision Making in Oil and Gas Production Platforms. In: Demazeau, Y., Ishida, T., Corchado, J.M., Bajo, J. (eds) Advances on Practical Applications of Agents and Multi-Agent Systems. PAAMS 2013. Lecture Notes in Computer Science(), vol 7879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38073-0_15

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  • DOI: https://doi.org/10.1007/978-3-642-38073-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38072-3

  • Online ISBN: 978-3-642-38073-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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