Abstract

This study offers a reinterpretation of archive aquifer tests, predominantly on the basis of recovery data, from an original datasheet of thermal water wells located in carbonate and sandstone aquifer units in the vicinity of Budapest, Hungary. The study compares the hydraulic conductivity (K) and specific storage (Ss) values derived in the first instance from an aquifer test evaluation. This included an initial application of the classical analytical Cooper and Jacob method. Subsequently, the visual two-zone (VTZ) numerical method was applied, then third, a more complex model, namely, WT software. It was found that the simple analytical solution is not able to represent the field conditions accurately, while in the course of the application of the VTZ model, it proved possible to alter the various hydraulic parameters within reasonable limits to fit the field data. In the case of the VTZ model, the researcher is required to calculate the accuracy of the fitted model separately, while with the WT model, this is automatic, the software seeks out the best fit. In addition to VTZ parameters, the WT model can efficiently incorporate data on up to 500 model layers, water level, and pressure. The optimization of the parameters may be achieved by automatic calibration, improving the accuracy of the numerical results. Recovery tests for 12 wells were numerically simulated to obtain values for vertical and horizontal hydraulic conductivity and specific storage for Triassic and Eocene fractured carbonate and the Upper-Miocene-Pliocene granular sandstone aquifer units. When an analytical solution is applied, only average values could be obtained. The conclusion reached was that the results of the analytical solution can be improved by the use of numerical methods. These methods are able to incorporate basic information on well design, aquifer material and the hydrogeological environment in the course of the evaluation. The revision of the archive recovery data using numerical methods may assist in the quest for better data for numerical flow and transport simulations without the need to perform new tests. In addition, the methods employed here can explain cases in which the original analytical interpretations proved unable to yield reliable data and predictions.

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