HR: 11:25h
AN: H32B-05 INVITED     [Abstracts]
TI: Joint Inversion at the Boise Hydrogeophysical Research Site
AU: Barrash, W
EM: wbarrash@cgiss.boisestate.edu
AF: Boise State University, CGISS/Department of Geosciences 1910 University Drive, Boise, ID 83725, United States
AU: * Malama, B
EM: bmalama@cgiss.boisestate.edu
AF: Boise State University, CGISS/Department of Geosciences 1910 University Drive, Boise, ID 83725, United States
AU: Routh, P
EM: routh@cgiss.boisestate.edu
AF: Boise State University, CGISS/Department of Geosciences 1910 University Drive, Boise, ID 83725, United States
AU: Johnson, T
EM: timothy.johnson@inl.gov
AF: Idaho National Laboratory, Measurement and Modeling Group P.O. Box 1625, Idaho Falls, ID 83425, United States
AU: Clemo, T
EM: tomc@cgiss.boisestate.edu
AF: Boise State University, CGISS/Department of Geosciences 1910 University Drive, Boise, ID 83725, United States
AB: The Boise Hydrogeophysical Research Site (BHRS) is a research wellfield or field-scale test facility developed in a shallow, coarse, fluvial unconfined aquifer with the objectives of developing cost-effective, non-invasive methods for quantitative characterization and imaging in heterogeneous aquifers using hydrologic and geophysical techniques. The design of the wells and the wellfield provide for a wide range of single-well, cross- hole, multiwell and multilevel hydrologic, geophysical, and combined hydrologic-geophysical experiments. Recent efforts have been focused largely on: (a) establishing the 3D distributions of geologic, hydrologic, and geophysical parameters and (b) developing subsurface measurement and imaging methods including time- lapse tomographic imaging methods. Multiple lines of evidence from these efforts indicate that the hydrostratigraphic framework of the BHRS is a hierarchical system with at least three scales of sedimentary organization including layers and lenses; this framework is recognized with geologic, hydrologic, radar, seismic, and EM methods and tracer tests. Data from these characterization efforts and experiments can be used as the basis for joint inversion of multiple types of data to return the "known" 3D K distribution and also to improve subsurface imaging by including prior information in addition to data collected during tomographic or time-lapse imaging experiments. We present a joint inversion framework for determining the 3D hydraulic conductivity (K) distribution using site K data and geophysical data. Given the heterogeneous nature of the system, K is treated as a random field and the moment equation approach is used for the solution of the stochastic forward flow problem. The inverse problem is posed in the Bayesian framework which allows for a straightforward inclusion of prior information.
UR: http:cgiss.boisestate.edu/hydrogeophysical_research_site.htm
DE: 1829 Groundwater hydrology
DE: 1835 Hydrogeophysics
DE: 1894 Instruments and techniques: modeling
DE: 3235 Persistence, memory, correlations, clustering (3265, 7857)
DE: 3260 Inverse theory
SC: Hydrology [H]
MN: 2007 Joint Assembly