Conditioning steady state mean stochastic flow equations on head and hydraulic conductivity measurement

A. F. Hernandez, Shlomo P Neuman, A. Guadagnini, J. Carrera

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.

Original languageEnglish (US)
Pages (from-to)158-162
Number of pages5
JournalActa Universitatis Carolinae, Geologica
Volume46
Issue number2-3
StatePublished - 2002

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conditioning
hydraulic conductivity
heterogeneous medium
hydraulic head
prediction
kriging
conductivity
method
parameter estimation

ASJC Scopus subject areas

  • Geology

Cite this

Conditioning steady state mean stochastic flow equations on head and hydraulic conductivity measurement. / Hernandez, A. F.; Neuman, Shlomo P; Guadagnini, A.; Carrera, J.

In: Acta Universitatis Carolinae, Geologica, Vol. 46, No. 2-3, 2002, p. 158-162.

Research output: Contribution to journalArticle

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