• Journal of Soil and Groundwater Environment
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• v.12 no.3
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• pp.36-43
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• 2007

In the case of single well pumping tests the storativities are generally overestimated. To compensate these errors, the effective wellbore radius should be introduced as a distance to an imaginary observation well in the time-drawdown analysis. Effective wellbore radius can be calculated through step drawdown tests or using skin factor equation. But both are of trial-and-error methods guessing real storativity values and, therefor, are difficult to apply to the field conditions. An equation was developed to estimate effective wellbore radius from storativity values obtained from pumping well data. For this study, a total of 136 time-drawdown data set were used to derive the equation. The effective wellbore radius were estimated first by changing them till the storativity values obtained from the pumping-well data match the ones based on the observation-well data. Then the equation was regressed from the relation between effective wellbore radius and the storativity values obtained from the pumping-well data. It is believed that the equation would be useful in estimating effective wellbore radius from the single well tests.

• The Journal of Engineering Geology
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• v.19 no.1
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• pp.71-79
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• 2009

Step-drawdown tests were conducted at four pumping Wells, two in porous media and two in fractured rocks, respectively. In general, P = 2.0 suggested by Jacob (1947) is applied to porous media and fractured rocks in terms of drawdowns of step-drawdown test. In an attempt to review problems of linear model (Jacob's graphic method) in interpreting the step-draw down test, the outcomes of well parameters (aquifer loss coefficient (B), well loss coefficient (C) and well loss exponent (P)) calculated from linear and nonlinear model (Labadie and Helweg's least-squares method) were compared and analyzed. The values of C and P calculated from linear and nonlinear models differed according to permeability of aquifer and the conditions of pumping well. The value C obtained from nonlinear models in porous media and fractured rocks is about $10^0{\sim}10^{-2}$ and $10^{-3}{\sim}10^{-6}$ times lower than in their linear models, respectively. The value P of porous media obtained from nonlinear model ranged from 2.123 to 2.775, while it ranged from 3.459 to 5.635 for fractured rocks. In case of nonlinear model, well loss highly depends on the value P. At this time, well efficiencies calculated from linear and nonlinear models were $1.56{\sim}14.89%$ for porous media and $8.73{\sim}24.71%$ for fractured rocks, showing a significant error according to chosen models. In nonlinear model, it was found that the regression analysis using the least squares method was very useful to interpret step-drawdown test in all aquifer.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.405-416
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• 2017

This study evaluated a model unconfined aquifer comprising a sand or gravel layer, a filter layer, a pumping well, and an observation well. The model was employed in step drawdown tests and then used to assess the permeability of each test tank. The optimal yield and well efficiency were then calculated. Evaluation of yield by step in sand layer filters of equal thickness gave optimized watering rates of 22.03 L/min in the double filter and 19.71 L/min in the single filter. The double filter's yield was 115.0% that of the single filter. A comparison of double and single filters, each 10 cm thick, showed the double filter to have a maximum yield of 182.7%. Yields for the gravel layer were 73.56 L/min for a double filter and 65.47 L/min for a single filter of the same thickness; the former value is 112.3% of that of the latter. Comparison of double and single filters with 10-cm-thick gravel layers revealed that the double filter had a maximum yield of 160.9%. Results for sand wells showed the double filter to have a maximum efficiency of 70.4% and the single filter to have a minimum efficiency of 37.1%. Gravel-layer well efficiencies were >66.5% for both double and single filters (each 30 cm thick), but only 22.5% for a 10-cm-thick single filter. This study confirms that permeability improved as the filter material became thicker; it also shows that a double filter has a higher yield and well efficiency than a single filter. These results can be applied to the practical design of wells.

• The Journal of Engineering Geology
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• v.28 no.1
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• pp.101-115
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• 2018

This study was carried out to evaluate the effects of various filter conditions on unconfined aquifer (alluvial aquifer). We made model test device which has filter layer, pumping well and observation well which consist of sand layer and gravel layer to test. Step drawdown test and long term pumping tests were carried out using the device. The permeability characteristics of each test group were confirmed and the optimal yield was calculated. As a result of comparing the optimal yield of double filter and single filter in sand, dual-filter SD-300 was valued at 216.8 % higher final optimal yield than single-filter SS-300. Comparing the dual filter SD-300 and the single filter SS-100 with a thin filter layer, dual-filter SD-300 was valued at 709.2% higher final optimal yield than single-filter SS-300. As a result of analysis of optimal yield change over time, It was confirmed that the ratio of optimal yield of single filter and dual filter increase over time. In order to evaluate the long-term change in water intake efficiency, we considered the point at which the initial optimal yield was reduced by 50%. The dual filter SD-300 is about 351.1% higher than SS-300, which is the same thickness filter, and about 579.0% higher than SS-100. From these results, Assuming that the point at which the initial quantity of water intake is reduced to 50% is the well life, double filters are expected to increase their lifespan by about 3.5 times over single filters of the same thickness and by about 5.8 times over typical single filter. These results can be used to design wells to river bank filtration or filtered seawater. In addition, it is possible to clarify the effect of the double filter through the comparison with the future field test results.