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3D effects on 2D resistivity monitoring in earth‐fill dams
Author(s) -
Cho InKy,
Ha IkSoo,
Kim KiSeog,
Ahn HeeYoon,
Lee Seunghee,
Kang HyeJin
Publication year - 2014
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2013065
Subject(s) - electrical resistivity and conductivity , geology , spurious relationship , crest , inversion (geology) , water level , hydrogeology , environmental geology , levee , electrical resistivity tomography , embankment dam , engineering geology , geotechnical engineering , seismology , volcanism , engineering , telmatology , physics , cartography , quantum mechanics , machine learning , computer science , geography , electrical engineering , tectonics
Measuring resistivity is a potentially powerful method of monitoring leakage zones that have developed in a dam, and their expansion over time. Generally, for embankment dams, two‐dimensional (2D) resistivity data have been measured along the dam crest for the detection of leakage zones. However, the three‐dimensional (3D) effects created by specific dam geometry and fluctuations in reservoir water levels significantly distort the 2D resistivity data measured at the dam crest. This study evaluates the 3D effects through 3D resistivity modelling software, which was developed to calculate apparent resistivity data for geometries and material distributions for embankment dams. These modelling results demonstrated that the 3D effect from the dam geometry and variations in water level is significant. Especially, in the case of monitoring, changes in 3D effects from water level fluctuations cause a spurious near‐surface layer when time‐lapse inversion is applied with a cross‐model constraint. To overcome this problem, we introduced a combined reference model constructed from the independent inversion of both time‐lapse data and original reference data. The combined reference model was able to effectively suppress the spurious near‐surface layer and to clearly image the damaged zone when the change in water level was small. However, a time‐lapse inversion using the combined reference model also failed to identify the damaged zone when the change in water level was large. Finally, by using the resistivity monitoring system devised for dam surveillance to a test dam site, resistivity monitoring data were acquired. From the time‐lapse inversion of two data sets showing a large change in water level between two measurements, it was confirmed that the variation of water levels produces the occurrence of a spurious near‐surface layer due to a strong 3D effect.