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Computational challenges in the search for and production of hydrocarbons

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Scientific Modeling and Simulations

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 68))

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Abstract

The exploration and production of oil and natural gas facing unprecedented demands for a secure energy supply worldwide is continuing a long trend to develop and adopt new technologies to help meet this challenge. For many oilfield technologies mathematical modeling and simulation have played a truly enabling role throughout their development and eventually their commercial adoption. Looking ahead, the vision of data-driven “intelligent” oilfields designed and operated using simulations to reach higher recovery factors is becoming a reality. Very little of this vision would be possible let alone make sense without the capability to move information across several simulation domains. We will examine several successes of modeling and simulation as well as current limitations which need to be addressed by new developments in theory, modeling, algorithms and computer hardware. Finally, we will mention several fundamental issues affecting oil recovery for which increased understanding is needed from new experimental methods coupled to simulation.

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Authors and Affiliations

  1. Schlumberger-Doll Research, One Hampshire St, 02141, Cambridge, MA, USA

    John Ullo

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  1. John Ullo
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Correspondence to John Ullo .

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Editors and Affiliations

  1. Department of Nuclear Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139-4307, USA

    Sidney Yip

  2. Lawrence Livermore National Laboratory, University of California, 7000 East Avenue, P.O. Box 808, CA, Livermore, 94551, USA

    Tomás Diaz de la Rubia

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Ullo, J. (2008). Computational challenges in the search for and production of hydrocarbons. In: Yip, S., de la Rubia, T.D. (eds) Scientific Modeling and Simulations. Lecture Notes in Computational Science and Engineering, vol 68. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9741-6_17

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