Date of Award


Degree Name

Doctor of Philosophy


Agricultural Sciences

First Advisor



Analytical solutions to well hydraulic problems have restrictive assumptions that often do not match real world conditions. Although numerical models more closely match reality, they either ran too slowly to be practical or lacked accuracy because of coarse grid spacing and large time steps. Advances in computer power over the last few decades now allow for accurate, fast numerical models that handle complex flow systems. The purpose of this dissertation was to develop flexible and accurate numerical modeling codes for the simulation of hydrologic tests. One of these numerical modeling codes, the Slug Test Simulator (STS), was designed for the mechanics of a single well test, or slug test. STS can handle a variety of conditions including unconfined flow, partial penetration, layered heterogeneities, and the presence of a homogeneous well skin like existing codes. This program also extends on the capabilities of earlier codes with its ability to simulate a heterogeneous skin where K can vary in both the radial and vertical directions. STS has a clear user interface, can display graphical results, and allows the user to determine hydraulic conductivity through a trial-and-error curve-matching process. Comparisons of STS to the Cooper-Bredehoeft-Papadopulos analytical solution and the Kansas Geological Survey (KGS) semi-analytical solution produced near-identical curves under a wide variety of conditions. Numerous analytical studies have shown that the well skin is an important factor in the underestimation of hydraulic conductivity in slug tests. STS allows for the exploration of the well skin issue under conditions too complex for analytical models. Model trials revealed two key discoveries: 1) if any layers within the skin have the same hydraulic conductivity as the surrounding formation, flow is concentrated within these conduits and the resultant head response approaches the case when no skin is present; and 2) the two most important properties in determining the overall influence of the skin are specific storage and skin thickness. The first discovery suggests that extensive development activities can essentially eliminate any well skin impacts. Other factors such as partial penetration, the placement of the well screen, and anisotropy play insignificant roles in resultant head responses. Recent research is focusing on alternative direct- push (DP) methodologies to determine hydrologic properties. DP offers advantages over traditional well tests, but may yield inaccurate results if the screen becomes clogged during pushing activities. The Kansas Geological Survey (KGS) developed a new DP technique, the Direct-Push Permeameter (DPP), to overcome this limitation. Existing analytical or numerical models cannot address the specialized nature of DPP tests so a second numerical modeling code, the Direct Push Permeameter Simulator (DPSS), was developed. DPPS was generated by modifying STS so both numerical codes are similar in many ways, particularly with their flexibility and accuracy. The codes differ in how they handle vertical layering, the boundary conditions at the well, and the spreadsheet interfaces. DPPS was able to produce near-identical curves in comparison to the Theis analytical solution. DPPS was also able to reasonably recreate DPP field data conducted at two sites with distinctly different media properties. The GEMS and Nauen sites had an average error of 14.2% and 3.1%, respectively between the field data and DPPS simulations.




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