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The least squares inversion of high-density resistivity method ratio parameter based on smooth constraint |
Cheng-Gong LIU1, Sheng JIN1,2, Wen-Bo WEI1,2, Jian-En JING1, Gao-Feng YE1, Yao-Tian YIN1 |
1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China 2. Key Laboratory of Underground Information Detection Technology and Instruments, Ministry of Education, Beijing 100083,China |
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Abstract The detection accuracy of the array and the study of data processing methods about the three-potential observation system always constitute a hot spot for geophysicists, and there are also many controversies. In this paper, forward modeling results are used to discuss the detecting accuracy of three devices under several possible geological conditions in karst area. It is found that β array and γ array are significantly more precise than wenner α array; then, the ratio parameter (T) is composed of forward’s result. With least-squares inversion on the data of T, the authors found that the result of T’s least-squares inversion is consistent with the inverse result of apparent resistivity, and the result of inversion result is better than the T contour map in an area where the noise is large. For the result of the T’s least-squares inversion, it can be used as a basis for judging the anomalous body characteristics and the inverse result of apparent resistivity, and it can also be used to make up the effect of noise on a single device. Taking the hydrogeological survey of a certain place in Yima as an example, the authors found that the result of the T’ least-squares inversion in the low-water-resistance region is small, the abnormal bodies’ boundaries are accurate, and the structural features are obvious. It is shown that the result of the T least-squares inversion is very useful for data processing and interpretation, and therefore researchers should pay attention to it in future.
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Received: 03 April 2018
Published: 10 April 2019
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Schematic diagram of the arrangement of the electrodes of the Winner α, β, γ devices
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Low-resistance model profile and parametric profile a—low-resistance geological model section; b—sectional view of resistivity of the alpha device; c—sectional view of the resistivity of the beta device;d—sectional view of the resistivity of the gamma device; e— ratio parameter (T) pseudo sectional view; f—ratio parameter (T) sectional view
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High-resistance model profile and parametric profile a—high-resistance geological model section;b—sectional view of resistivity of the alpha device;c—sectional view of the resistivity of the beta device;d—sectional view of the resistivity of the gamma device ;e—ratio parameter (T) pseudo sectional view;f—ratio parameter (T) sectional view
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Complex model profile and parameter profile a—complex electrical geological model section; b—sectional view of resistivity of the alpha device;c—sectional view of the resistivity of the beta device; d—sectional view of the resistivity of the gamma device;e—ratio parameter (T) pseudo sectional view; f—ratio parameter (T) sectional view
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Sectional view of measured section parameters a—sectional view of resistivity of the alpha device; b—sectional view of the resistivity of the beta device;c—sectional view of the resistivity of the gamma device; d—ratio parameter (T) pseudo sectional view; e—ratio parameter (T) sectional view
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