Risk Analysis

  • Thomas HantschelEmail author
  • Armin I. Kauerauf

In previous chapters two assumptions were made about data needed for successful simulation runs. It was first proposed that necessary data is completely available and second that it is good quality. So it was implicitly concluded that each model is unique. In practice, this is usually not the case. Data sets have gaps and the data values often have wide error bars. These uncertainties lead to the following three types of questions.


Risk Analysis Monte Carlo Simulation Response Surface Markov Chain Monte Carlo Uncertainty Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Integrated Exploration Systems GmbH A Schlumberger CompanyAachenGermany

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