HR: 0830h
AN: H21E-0893    [PDF]
TI: Improvements in Groundwater Flow Modeling Through the Integration of Resistivity Logs and Hydraulic Conductivity
AU: Rahman, A
AF: Dept. of Civil and Environmental Engineering, Louisiana State University 3418D CEBA, Baton Rouge, LA 70803 United States
AU: White, C D
EM: cdwhite@lsu.edu
AF: Dept of Petroleum Engineering, Louisiana State University, Baton Rouge, LA 70803 United States
AU: * Willson, C S
EM: cwillson@lsu.edu
AF: Dept. of Civil and Environmental Engineering, Louisiana State University 3418D CEBA, Baton Rouge, LA 70803 United States
AB: In this study cokriging is used to estimate hydraulic conductivity by using spatial cross correlation between hydraulic conductivity and borehole geophysical data (a transform of the formation factor). Experimental pseudo cross variograms are used instead of a crossvariogram because there are few locations where conductivity and formation data are both measured. Uncertainty in the estimates of the experimental variogram is investigated using unconditional sequential Gaussian realizations. Confidence intervals for the experimental variogram values have been calculated assuming variogram sills are either normally, lognormally, or $chi^{2}$ distributed. Variogram models that show highest and lowest continuity within the 95% confidence limit are used for cokriging. The generated hydraulic conductivity field is then used in a high-resolution groundwater model created using telescopic mesh refinement (TMR) from a regional flow model of the Chicot Aquifer in southwestern Louisiana. Results are analyzed to assess variogram uncertainty on the groundwater flow model. Spatial images and flow predictions using univariate models based on sparse conductivity data are compared with coregionalized models using both conductivity and resistivity data, and the effects on model accuracy and robustness are discussed.
DE: 1829 Groundwater hydrology
DE: 1832 Groundwater transport
SC: Hydrology [H]
MN: 2003 Fall Meeting