Processing for near-source potential resistivity based on the parallel electrical method

• Autorzy: Hu Zean , Wu Rongxin , Cao Jianfu , Wang Xiaoyu

Identyfikatory

DOI

10.1007/s11600-022-00884-7

• Języki publikacji: EN

Abstrakty

EN

The parallel electrical method (PEM), which enhances the field-work efficiency by offering flexible data acquisition and processing a large amount of geoelectric field data, is mainly used to extract the high-density resistivity data. However, the method is unable to process nearly 75% of the data and hampered by noise interference. We proposed a novel method to calculate the apparent resistivity based on the near-source potential in the PEM system using the following algorithms: (1) selecting the measurement electrode nearest to the power source as the reference and keeping the AM interval as an invariant electrode distance, (2) calculating the potential difference between the measurement electrode and the first near-source electrode, (3) stepwise calculating the potential differences between other measurement electrodes and their corresponding near-source electrodes, and (4) calculating all the apparent resistivities at different positions. We further verified the effectiveness of near-source potential method to calculate resistivity based on the theoretical calculation and identified that it has higher calculation accuracy and stability. Compared to the maximum Pole-dipole deviation of 59.4%, the maximum deviation of the near-source potential resistivity is only 2.2%. The field experimental results showed that the near-source potential resistivity method performs well in the stratified geoelectric model and effectively improves the longitudinal resolution and the signal-to-noise ratio of deep apparent resistivity of the parallel direct-current resistivity method.

Słowa kluczowe

EN

apparent resistivity; signal-to-noise ratio; near-source potential; parallel electrical method

PL

oporność pozorna; stosunek sygnału do szumu

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 6
• Strony: 2705--2714
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Hu Zean

• School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China
• State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Huainan 232001, Anhui, China

• https://orcid.org/0000-0002-0520-3910

autor

Wu Rongxin

• School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China
• State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Huainan 232001, Anhui, China

autor

Cao Jianfu

• School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China

autor

Wang Xiaoyu

• School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China

Bibliografia

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• 14. Tejero R, Gomez-Ortiz D, Garzon Heydt G et al (2017) Electrical resistivity imaging of the shallow structures of an intraplate basin: the Guadiana Basin (SW Spain). J Appl Geophys 139:54–64
• 15. Wu R, Liu S, Zhang P et al (2010) Detection of limestone water-conducting channels in coal mine by parallel 3D electric method of surface boreholes. Chin J Rock Mech Eng 29(S2):3585–3589
• 16. Yang C, Liu S, Liu L et al (2016) Water abundance of mine floor limestone by simulation experiment. Int J Min Sci Technol 26:495–500
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• 18. Yang L, Jin W, Shang Y (2019) Effects on the resolution of high-density electrical method by electrodes array deploying. Prog Geophys 34(01):406–411
• 19. Yin Q, Tao P, Xia Y (2020) Active faults and bedrock detection with super-high-density electrical resistivity imaging. Bull Eng Geol Env 79:5049–5060
• 20. Zhang W (2020) Study on nonlinear inversion for complex resistivity based on parallel electrical method [D]. China Mining University.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).