Title

Analytical Modeling of Fully Penetrating Pumping Tests at the Boise Hydrogeophysical Research Site for Aquifer Parameters and Wellbore Skin

Publication Date

11-2006

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Geology

Department

Geosciences

Major Advisor

Warren Barrash

Abstract

Pumping tests are used to determine important aquifer parameters such as hydraulic conductivity (K), specific storage (Ss) and specific yield (Sy). Knowledge of these parameters is important for quantitative analysis of groundwater systems in order to address hydrogeologic issues such as groundwater supply for municipalities and irrigation projects, contaminant transport and remediation, and geotechnical projects. In this study, aquifer parameters were estimated in an unconfmed fluvial aquifer at a research wellfield, the Boise Hydrogeophysical Research Site (BHRS), by using WTAQ (Moench, 1995, 1997), an analytical model, to analyze a series of fully-penetrating pumping tests that were conducted in 1999. The pumping tests generally consisted of one pumping well and five observation wells with pressure transducers used to measure the drawdown in the pumping and observation wells. From these tests, data from 73 pumping well-observation well pairs were analyzed using an analytical model to determine aquifer parameters (K, Ss, and Sy). Drawdown curves were generated with an analytical model using a forward modeling process to match the observed drawdown data for a given pumping and observation well pair. In addition, wellbore skin at both the pumping and observation wells was included in the analytical model to account for observed head losses associated with the wells.

A sensitivity analysis was performed to evaluate if the parameter values determined by the forward modeling were tightly constrained. This quality control check was accomplished by fixing a given parameter (skin hydraulic conductivity of the observation well, Ks_OBS; aquifer thickness, b; Ss; or Sy) at the high or low end of the range of values determined by the forward modeling. The other parameters were then adjusted to achieve a curve match between the drawdown data and the analytical model predicted drawdown with time. The goodness of fit on the initial forward modeling curve matches and the sensitivity analysis curve matches were compared by performing a sum of squared error (SSE) analysis. The goodness of fit between the initial forward modeling curve matches and the sensitivity analysis curve matches were found to be similar for all parameters tested in the sensitivity analysis except Ks_Q. The SSE values for the sensitivity analysis when K, Q was fixed at the low end of the range were two to three orders of magnitude higher than the SSE values for initial forward modeling curve matches. The sensitivity analysis for Ks_Q resulted in curve matches with SSE values that were one order of magnitude greater than the initial forward modeling curve matches when Ks_Q was fixed at higher values. That is, Ks_Q is the most sensitive, or most tightly constrained, parameter.

Based on results from the analytical modeling of the fully penetrating pumping tests, the mean radial hydraulic conductivity (Kr) of the unconfined aquifer at the BHRS was determined to be 0.076 cm/sec and Kr ranged from 0.051 cm/sec to 0.13 cm/sec with greater values generally occurring in the western half of the BHRS where the sand channel is located. Areal plots of the ratio of vertical hydraulic conductivity (Kz) to Kr were constructed to assess the distribution of anisotropy which was determined to exist in 25 well pairs (34%). No clear areal distribution pattern of K anisotropy was evident at the BHRS. The arithmetic mean determined for Ss from the forward modeling was 4.1 x 10-5 m-1, with values ranging from 3.3 x 10-5 to 1.3 x 10-4 m-1. The arithmetic mean for Sy values determined from the forward modeling was 0.036, with values ranging from 0.013 to 0.070. A systematic difference between Ks_Q and Ks_OBS was evident from the modeling. The Ks_OBS was, with few exceptions, 1.5 to 5 times larger than the Ks_Q.

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