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Cluster Computing

, Volume 8, Issue 4, pp 255–269 | Cite as

An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement

  • Wolfgang Bangerth
  • Hector Klie
  • Vincent Matossian
  • Manish Parashar
  • Mary F. Wheeler
Article

Abstract

The adequate location of wells in oil and environmental applications has a significant economic impact on reservoir management. However, the determination of optimal well locations is both challenging and computationally expensive. The overall goal of this research is to use the emerging Grid infrastructure to realize an autonomic self-optimizing reservoir framework. In this paper, we present a policy-driven peer-to-peer Grid middleware substrate to enable the use of the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm, coupled with the Integrated Parallel Accurate Reservoir Simulator (IPARS) and an economic model to find the optimal solution for the well placement problem.

Keywords

Grid computing autonomic Grid middleware stochastic optimization optimal well placement reservoir management 

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Wolfgang Bangerth
    • 1
  • Hector Klie
    • 1
  • Vincent Matossian
    • 2
  • Manish Parashar
    • 2
  • Mary F. Wheeler
    • 1
  1. 1.Center for Subsurface ModelingThe University of Texas at AustinAustin
  2. 2.The Applied Software Systems LaboratoryRutgers UniversityPiscataway

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