Stochastic estimation of hydraulic transmissivity fields using flow connectivity indicator data

Most methods for hydraulic test interpretation rely on a number of simplified assumptions regarding the homogeneity and isotropy of the underlying porous media. This way, the actual heterogeneity of any natural parameter, such as transmissivity ( T ), is transferred to the corresponding estimates in a way heavily dependent on the interpretation method used. An example is a long‐term pumping test interpreted by means of the Cooper‐Jacob method, which implicitly assumes a homogeneous isotropic confined aquifer. The estimates obtained from this method are not local values, but still have a clear physical meaning; the estimated T represents a regional‐scale effective value, while the log‐ratio of the normalized estimated storage coefficient, indicated by ω ′ , is an indicator of flow connectivity, representative of the scale given by the distance between the pumping and the observation wells. In this work we propose a methodology to use ω ′ , together with sampled local measurements of transmissivity at selected points, to map the expected value of local T values using a technique based on cokriging. Since the interpolation involves two variables measured at different support scales, a critical point is the estimation of the covariance and crosscovariance matrices. The method is applied to a synthetic field displaying statistical anisotropy, showing that the inclusion of connectivity indicators in the estimation method provide maps that effectively display preferential flow pathways, with direct consequences in solute transport.