HR: 14:00h
AN: NS33A-01 INVITED     [Abstracts]
TI: The Role of Uncertainty and Scale in Rock Physics Transforms on Sequential and Integrated Data Fusion Methods
AU: * Moysey, S
EM: smoysey@clemson.edu
AF: Clemson University, School of the Environment 340 Brackett Hall, Clemson, SC 29634, United States
AB: Geophysical data are increasingly being used to address complex problems across disciplinary boundaries. Rock physics provides a bridge across these boundaries by relating the properties that control geophysical measurements, e.g., electrical conductivity, to properties that are of fundamental interest to a discipline specialist, e.g., solute concentration. However, as geophysical applications become increasingly sophisticated so do the issues that complicate data fusion, such as discrepancies between scales of interest and uncertainty due to geologic heterogeneity. Therefore, understanding the impact of uncertainty and scale on rock physics transforms is a critical problem. Recent advances have been made to account for the upscaling of rock physics relationships in heterogeneous environments, e.g., Full Inverse Statistical Calibration (FISt). In the FISt approach it is possible to cast rock physics relationships within a stochastic framework, thereby allowing one to investigate how different factors, such as prior geologic models, measurement non-linearity, and process uncertainty, ultimately impact this transform. By breaking down a rock physics relationship into these different components it is also possible to make informed decisions regarding the appropriate transform to be used in alternate approaches to geophysical data integration, such as sequential versus integrated approaches to data fusion. In the sequential approach geophysical data are collected, inverted to a geophysical image, and then transformed to, for example, hydrologic properties that can subsequently be used as constraints in hydrologic estimation problems. In this case, scale discrepancies related to model resolution are a critical issue in selecting the appropriate rock physics relationship. In contrast, the integrated approach to data fusion avoids the geophysical imaging step by linking the geophysical data directly to hydrologic properties through process-based models. Therefore, the scale of concern is that of the measurement resolution rather than model resolution. Ultimately, rock physics relationships are critical to the design of any data fusion algorithm and should be carefully selected to account for the issues specific to the particular estimation problem under consideration.
DE: 0520 Data analysis: algorithms and implementation
DE: 1835 Hydrogeophysics
DE: 3275 Uncertainty quantification (1873)
DE: 5100 PHYSICAL PROPERTIES OF ROCKS
SC: Near-Surface Geophysics [NS]
MN: 2007 Joint Assembly