Heterogeneity of permeability in fractured media is a hot research topic in hydrogeology. Numerous approaches have been proposed to characterize heterogeneity in the last several decades. However, little attention has been paid to correlate permeability heterogeneity with geological information. In the present study, several causes of permeability heterogeneity, that is, lithology, tectonism, and depth, are identified. The unit absorption values （denoted as ω）, which are results obtained from the packer test, are employed to represent permeability. The variability of permeability in sandstone-mudstone is so significant that the value of unit absorptions span 3-4 orders of magnitude at any depth with several test sections. By declustering, it has been found that under a similar tectonic history, the means of permeability differ greatly at different formations as a result of different mudrock contents. It has also been found that in the same formation, permeability can be significantly increased as a result of faulting. The well-known phenomenon, the decrease in permeability with depth, is found to be caused by the fractures in the rock mass, and the relationship between permeability and depth can be established in the form of logoω-logd. After subtracting the trend of ω with absolute depth, the mean of the residual value at each relative depth can be well correlated with the distribution of mudstone. The methods proposed in this paper can be utilized to research in similar study areas.
On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.
