An Interactive Bayesian Geostatistical Inverse Protocol for Hydraulic Tomography

Abstract

Hydraulic tomography is a powerful technique for characterizing heterogeneous hydrogeologic parameters. An explicit trade-off between characterization based on measurement misfit and subjective characterization using prior information is presented. We apply a Bayesian geostatistical inverse approach that is well suited to accommodate a flexible model with the level of complexity driven by the data and explicitly considering uncertainty. Prior information is incorporated through the selection of a parameter covariance model characterizing continuity and providing stability. Often, discontinuities in the parameter field, typically caused by geologic contacts between contrasting lithologic units, necessitate subdivision into zones across which there is no correlation among hydraulic parameters. We propose an interactive protocol in which zonation candidates are implied from the data and are evaluated using cross validation and expert knowledge. Uncertainty introduced by limited knowledge of dynamic regional conditions is mitigated by using drawdown rather than native head values. An adjoint state formulation of MODFLOW-2000 is used to calculate sensitivities which are used both for the solution to the inverse problem and to guide protocol decisions. The protocol is tested using synthetic two-dimensional steady state examples in which the wells are located at the edge of the region of interest.

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 2008
Accession Number
ADA573849

Entities

People

  • Michael N. Fienen
  • Peter K. Kitanidis
  • Tom Clemo

Organizations

  • Boise State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Continuity
  • Covariance
  • Data Science
  • Discontinuities
  • Environmental Restoration And Remediation
  • Groundwater
  • Information Science
  • Inverse Problems
  • Measurement
  • Monte Carlo Method
  • Steady State
  • Surveys
  • Test Methods
  • Three Dimensional
  • Two Dimensional
  • Water Resources

Readers

  • Acoustical Oceanography.
  • Geotechnical Engineering.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms