| dc.description.abstract | The multilevel slug test (MLST) is useful to characterize aquifer hydraulic conductivity K and aquifer storativity S while is under the influence of the skin effect. In general, there are two distinct approaches in modeling the skin effect. One assumes the skin zone to be an annular porous medium surrounding the well with finite thickness rs. Its Ks and Ss are different from K and S, respectively. The other assumes rs to be infinitesimal while neglecting Ss, wherein the skin effect is dealt with by using an effective well radius re that exponentially decays with the skin factor Sk. Technically, Sk can be independently evaluated using a pumping test, leaving only two parameters K and S in the infinitesimal-thickness approach. As being mathematically much simpler than the finite-thickness approach and involving less unknown parameters, the infinitesimal-thickness approach is more practical for data analysis. The purpose of this research is to investigate the conditions under which these two distinct approaches can yield similar results. In order to achieve this goal we compare two different MLST models, a finite-thickness model (FTM), and an effective well radius model (ERM) for both the confined and unconfined aquifers. When Ss≦7×10－６ m－１, the FTM meets the assumption of neglecting skin zone storativity in the ERM. For confined conditions, if the partial penetration ratio exceeds 0.9 (as for positive skin) and is greater than 0.6 (as for negative skin), the FTM and ERM can produce similar results, regardless the values of the aspect ratio , dimensionless skin thickness s, the skin factor Sk, and the anisotropy ratio . When <0.4, for both confined and unconfined conditions, the conditions for FTM and ERM being the same dependent on various combinations of the parameters of Sk, ,s . Because of the MLST is usually less than 0.6, the data analysis using FTM and ERM will produce different parameter estimates. As the FTM involves three skin zone parameters, rs, Ks and Ss, which are of little practical interest, and the data analysis method using the FTM is more complicated, we recommend that the ERM be used for analyzing MLST field data. | en_US |