The Use of Specific Capacity to Assess Transmissivity in Fractured‐Rock Aquifers

Abstract

AbstractTransmissivity is often estimated from specific capacity data because of the expense of conducting standard aquifer tests to obtain transmissivity and the relative availability of specific capacity data. Most often, analytic expressions relating specific capacity to transmissivity derived by Thomasson and others (1960), Theis (1963), or Brown (1963) are used in this analysis. Razack and Huntley (1991) demonstrate that turbulent well loss produces poor correlation between measured transmissivities and those estimated from specific capacity from the above relations. This study focuses on a comparison between transmissivity and specific capacity of wells completed as open boreholes in fractured‐rock aquifers, where turbulent well loss may be less important.The analytic solutions typically used to predict transmissivity from specific capacity in alluvial aquifers do not agree well with the measured transmissivities in fractured‐rock aquifers. Measured transmissivities are less than those estimated from the theoretical solutions based on specific capacity. Some of the variation may be due to shorter testing periods for this data set, the difference between storage coefficients in fractured‐rock and alluvial aquifers, or aquifer anisotropy. Correction for these factors alone, however, does not markedly improve the correlation between theoretical and observed specific capacity/trans‐missivity relations. Transmissivities derived using the vertical fracture model of Gringarten and Witherspoon (1972), however, correlate very well with the observed specific capacities. Empirical relations between the log of transmissivity and the log of specific capacity for the fractured‐rock data set suggest they are linearly related (correlation coefficient of 0.89), but the width of 90% prediction interval is about 1.1 log cycles, indicating that the range of probable transmissivities corresponding to a single specific capacity was more than one order of magnitude.