Published June 18, 2006
| Version v1
Conference paper
Open
Subsurface Characterization Using Geophysical and Geohydrological Data Fusion
Description
We are introducing a novel technology applicable to the robust
interpretation of the spatial distribution of hydraulic conductivity in
heterogenous formations. The evidence theory approach is based on a
combination of directly measured hydrogeological and geophysical data
together with expert opinion. The approach first utilizes fuzzy-set based
approximate reasoning to quantify subjective expert opinion, especially
when data are scarce, to create a fuzzy prior characterization of the
hydraulic conductivity field. Subjective information includes, but is not
limited to opinions of groundwater professionals regarding the
relationship between soil type and grain size or on the grain size to
hydraulic conductivity relationship. Utilization of qualitative insights
into the effects of geological processes as interpreted by the groundwater
professional on hydraulic conductivity properties at a site is also a good
example. Secondly, we propose to provide a new framework for integrating
available kriged borehole data as well as geophysical information with the
prior estimated conductivity field. The resulting evidence theory based
approach has its core strengths in 1) enabling the simultaneous use of
probabilistic uncertainty and other (non-additive) representations of
uncertainty (e.g., fuzzy or possibilistic), 2) integrating expert opinion
with objective information, 3) solving the delicate problem of choosing an
appropriate prior estimate of hydraulic conductivity for the conditioning
process, and 4) enabling a complementary (rather than sequential) use of
geophysical data during the characterization process. The framework
described herein allows a sensitivity analysis of the resultant
characterization with respect to available data which makes it possible to
assess the value (in the sense of consistency or conflict) of information.
A site application demonstrates the approach.