Skip to main content

Estimation of Production Rate Limits Using Agent-Based Simulation for Oil and Gas Plants Safety

  • Conference paper
  • 1671 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 229))

Abstract

Safe production is one of the most important issues in oil and gas plants. Oil and gas companies lose enormous amounts of money and trust once they experience accidents such as explosions and oil spills. They have to make clear production rate limits to mitigate the human related risks that cause accidents. In this study, we model plant workers using an agent-based simulation to estimate the limits. The proposed model represents that plant workers solve problems with risks, and that the probability of the occurrence of a problem is proportional to three main factors, the production rate, the plant size, and the plant equipment degradation rate. The experimental results show that the proposed model can estimate the limits for different sizes of the three factors. The results imply that the limit estimation made by the proposed model is very crucial for plant operations to mitigate human-related accidents.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. International Energy Agency: Key World Energy Statistics 2012 (2012)

    Google Scholar 

  2. International Energy Agency: World Energy Outlook 2012 (2012)

    Google Scholar 

  3. Paté-Cornell, M.E.: Learning from the piper alpha accident: A postmortem analysis of technical and organizational factors. Risk Anal. 13(2), 215–232 (1993)

    Article  Google Scholar 

  4. Gill, D.A., Picou, J.S., Ritchie, L.A.: The Exxon Valdez and BP oil spills: A comparison of initial social and psychological impacts*. Am. Behav. Sci. 56(1), 3–23 (2012)

    Article  Google Scholar 

  5. Bayerl, P.S., Lauche, K.: Technology effects in distributed team coordination high-interdependency tasks in offshore oil production. Computer Supported Cooperative Work 19(2), 139–173 (2010)

    Article  Google Scholar 

  6. U.S. Department of the Interior, Minerals Management Service, Engineering and Operations Division: Incidents Associated with Oil and Gas Operations, Outer Continental Shelf 2000. OCS Report, MMS 2002-016 (2002)

    Google Scholar 

  7. Sneddon, A., Mearns, K., Flin, R.: Situation awareness and safety in offshore drill crews. Cognition, Technology & Work 8(4), 255–267 (2006)

    Article  Google Scholar 

  8. O’Dea, A., Flin, R.: Site managers and safety leadership in the offshore oil and gas industry. Safety Sci. 37(1), 39–57 (2001)

    Article  Google Scholar 

  9. Pongsakdi, A., Rangsunvigit, P., Siemanond, K., Bagajewicz, M.J.: Financial risk management in the planning of refinery operations. Int. J. of Prod. Econ. 103(1), 64–86 (2006)

    Article  Google Scholar 

  10. Göthe-Lundgren, M., Lundgren, J.T., Persson, J.A.: An optimization model for refinery production scheduling. Int. J. Prod. Econ. 78(3), 255–270 (2002)

    Article  Google Scholar 

  11. Qin, S.J., Badgwell, T.A.: A survey of industrial model predictive control technology. Control Eng. Pract. 11(7), 733–764 (2003)

    Article  Google Scholar 

  12. Meum, P., Tøndel, P., Godhavn, J.M., Aamo, O.: Optimization of smart well production through nonlinear model predictive control. SPE Intelligent Energy Conference and Exhibition, SPE 112100, 1–11 (2008)

    Google Scholar 

  13. Carley, K.M., Svoboda, D.M.: Modeling organizational adaptation as a simulated annealing process. Sociol. Methods & Res. 25(1), 138–168 (1996)

    Article  Google Scholar 

  14. Jin, Y., Levitt, R.E.: The virtual design team: A computational model of project organizations. Computational & Mathematical Organization Theory 2(3), 171–195 (1996)

    Article  Google Scholar 

  15. Malcolm, D.G., Roseboom, J.H., Clark, C.E., Fazar, W.: Application of a technique for research and development program evaluation. Oper. Res. 7(5), 646–669 (1959)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yukihisa Fujita .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fujita, Y., Goh, K.N., Chen, Y.Y., Naono, K. (2014). Estimation of Production Rate Limits Using Agent-Based Simulation for Oil and Gas Plants Safety. In: Kamiński, B., Koloch, G. (eds) Advances in Social Simulation. Advances in Intelligent Systems and Computing, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39829-2_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39829-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39828-5

  • Online ISBN: 978-3-642-39829-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics