Improved inverse modeling for flow and transport in subsurface media: Combined parameter and state estimation

Details Improved inverse modeling for flow and transport in subsurface media: Combined parameter and state estimation Improved inverse modeling for flow and transport in subsurface media: Combined parameter and state estimation

Sep 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005georl..3218408v&link_type=abstract

Geophysical Research Letters, Volume 32, Issue 18, CiteID L18408

Statistics

Computation

6

Computational Geophysics: Instruments And Techniques, Global Change: Earth System Modeling (1225), History Of Geophysics: Hydrology

Scientific paper

Current approaches for inverse modeling (IM) to estimate flow and transport properties in subsurface media implicitly assume that uncertainty in the input-output representation of the model arises from uncertainty in the parameter estimates. However, uncertainties in the modeling procedure stem not only from uncertainties in the parameter estimates, but also from measurement errors, from incomplete knowledge of subsurface heterogeneity, and from model structural errors arising from the aggregation of spatially distributed real-world processes in a mathematical model. In this paper we present an improved concept for IM of subsurface flow and transport. Studies using interwell reactive tracer test data demonstrate that this new method, called Simultaneous Optimization and Data Assimilation, results in parameter estimates and model prediction uncertainty bounds which more closely mimic the properties of the subsurface. Most important is the finding that explicit treatment of input, output and model structural errors during IM, significantly alters the optimal values of the model parameters.

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