TY - JOUR
T1 - A Numerical Study of Slug Tests in a Three-Dimensional Heterogeneous Porous Aquifer Considering Well Inertial Effects
AU - Liu, Quan
AU - Hu, Linwei
AU - Bayer, Peter
AU - Xing, Yixuan
AU - Qiu, Pengxiang
AU - Ptak, Thomas
AU - Hu, Rui
N1 - Publisher Copyright:
©2020. American Geophysical Union. All Rights Reserved.
PY - 2020/11
Y1 - 2020/11
N2 - The slug test is a common field technique for obtaining local hydraulic parameters near wells, applied, for example, for the hydrogeological investigation at contaminated sites. Although many slug test models have been developed for interpretation of measurements, only a few of them have considered heterogeneous conditions, and water column inertial effects are usually neglected. In this paper, we propose a novel three-dimensional slug test model (3DHIM) for application in heterogeneous aquifers, considering inertial effects associated with skin effects and linear friction forces. After comparison with existing analytical and numerical solutions of slug tests, the model is applied to an aquifer analog to simulate a series of slug tests. The results from single-well slug tests show that the well geometry (i.e., the well radius, well depth, and screen length) has an impact on the water level response. For cross-well slug tests, the results indicate that the water level fluctuations not only include information on the hydraulic signal propagation process in the aquifer but also on well characteristics, such as wellbore storage and inertial effects. These effects cause a phase shift and amplitude change of the water level fluctuation. As the observation and test wells have a good hydraulic connection and similar well geometry, the water level amplitude could be amplified relative to aquifer pressure at the measured position. Therefore, we suggest considering wellbore storage and in-well inertial effects in slug test-based subsurface investigations, otherwise the parameter estimates based on well water levels may include errors, particularly in highly permeable layers.
AB - The slug test is a common field technique for obtaining local hydraulic parameters near wells, applied, for example, for the hydrogeological investigation at contaminated sites. Although many slug test models have been developed for interpretation of measurements, only a few of them have considered heterogeneous conditions, and water column inertial effects are usually neglected. In this paper, we propose a novel three-dimensional slug test model (3DHIM) for application in heterogeneous aquifers, considering inertial effects associated with skin effects and linear friction forces. After comparison with existing analytical and numerical solutions of slug tests, the model is applied to an aquifer analog to simulate a series of slug tests. The results from single-well slug tests show that the well geometry (i.e., the well radius, well depth, and screen length) has an impact on the water level response. For cross-well slug tests, the results indicate that the water level fluctuations not only include information on the hydraulic signal propagation process in the aquifer but also on well characteristics, such as wellbore storage and inertial effects. These effects cause a phase shift and amplitude change of the water level fluctuation. As the observation and test wells have a good hydraulic connection and similar well geometry, the water level amplitude could be amplified relative to aquifer pressure at the measured position. Therefore, we suggest considering wellbore storage and in-well inertial effects in slug test-based subsurface investigations, otherwise the parameter estimates based on well water levels may include errors, particularly in highly permeable layers.
KW - friction losses
KW - heterogeneous aquifer
KW - inertial effect
KW - outcrop analog
KW - slug test
KW - well-aquifer coupling model
UR - https://www.scopus.com/pages/publications/85096486940
U2 - 10.1029/2020WR027155
DO - 10.1029/2020WR027155
M3 - 文章
AN - SCOPUS:85096486940
SN - 0043-1397
VL - 56
JO - Water Resources Research
JF - Water Resources Research
IS - 11
M1 - e2020WR027155
ER -