iTOUGH2: From parameter estimation to model structure identification

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iTOUGH2 provides inverse modeling capabilities for the TOUGH2 family of nonisothermal multiphase flow simulators. It can be used for a formalized sensitivity analysis, parameter estimation by automatic model calibration, and uncertainty propagation analyses. While iTOUGH2 has been successfully applied for the estimation of a variety of parameters based on different data types, it is recognized that errors in the conceptual model have a great impact on both the estimated parameters and the subsequent model predictions. Identification of the most suitable model structure is therefore one of the most important and most difficult tasks. Within the iTOUGH2 framework, model identification can ... continued below

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Finsterle, Stefan May 12, 2003.

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iTOUGH2 provides inverse modeling capabilities for the TOUGH2 family of nonisothermal multiphase flow simulators. It can be used for a formalized sensitivity analysis, parameter estimation by automatic model calibration, and uncertainty propagation analyses. While iTOUGH2 has been successfully applied for the estimation of a variety of parameters based on different data types, it is recognized that errors in the conceptual model have a great impact on both the estimated parameters and the subsequent model predictions. Identification of the most suitable model structure is therefore one of the most important and most difficult tasks. Within the iTOUGH2 framework, model identification can be partly addressed through appropriate parameterization of alternative conceptual-model elements. In addition, statistical measures are provided that help rank the performance of different conceptual models. We present a number of features added to the code that allow for a better parameterization of conceptual model elements, specifically heterogeneity. We discuss how these new features can be used to support the identification of key model structure elements and their impact on model predictions.

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OSTI as DE00813379

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  • TOUGH Symposium 2003, Berkeley, CA (US), 05/12/2003--05/14/2003

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  • Report No.: LBNL--52495
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 813379
  • Archival Resource Key: ark:/67531/metadc734159

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  • May 12, 2003

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  • Oct. 18, 2015, 6:40 p.m.

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  • April 4, 2016, 1:25 p.m.

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Finsterle, Stefan. iTOUGH2: From parameter estimation to model structure identification, article, May 12, 2003; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc734159/: accessed September 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.