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

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Warianty tytułu
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.
Czasopismo
Rocznik
Strony
2705--2714
Opis fizyczny
Bibliogr. 20 poz.
Twórcy
autor
  • 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
  • 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
  • School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China
autor
  • School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, Anhui, China
Bibliografia
  • 1. Amrani M, Bakkali S (2008) About the use of spatial interpolation methods to denoising Moroccan resistivity data phosphate “disturbances” map. Acta Montanistica Slovaca 13(2):216–222
  • 2. Carbonari DL, Maio RD et al (2017) Denoising of magnetotelluric signals by polarization analysis in the discrete wavelet domain. Comput Geosci 100:135–141
  • 3. Hoorde MV, Hermans T, Dumont G et al (2017) 3D electrical resistivity tomography of karstified formations using cross-line measurements. Eng Geol 220:123–132
  • 4. Jiang F (2017) Research on the practice of parallel electrical prospecting in hilly landform [D]. Anhui University of Science and Technology.
  • 5. Kiflu H, Kruse S, Loke MH et al (2016) Improving resistivity survey resolution at sites with limited spatial extent using buried electrode arrays. J Appl Geophys 135:338–355
  • 6. Lesparre N, Boyle A, Grychtol B et al (2016) Electrical resistivity imaging in transmission between surface and underground tunnel for fault characterization. J Appl Geophys 128:163–178
  • 7. Liu S, Wu R, Hu S, et al. (2006) Prospecting system of the network distributivity parallel electricity method[C]//Proceedings of the 22nd Conference on China Geophysics 2006. Chengdu: Sichuan Science and Technology Press, 2006: 251.
  • 8. Liu S, Wu R, Zhang P et al (2009) Three-dimensional parallel electric surveying and its applications in water disaster exploration in coalmines. J China Coal Soc 34(07):927–932
  • 9. Liu S, Liu J, Qi J et al (2019) Applied technologies and new advances of parallel electrical method in mining geophysics. J China Coal Soc 44(08):2336–2345
  • 10. Loke MH, Kiflu H, Wilkinson PB et al (2015) Optimized arrays for 2D resistivity surveys with combined surface and buried arrays. Near Surface Geophysics 13(5):505–517
  • 11. Lu T, Liu S, Wang B et al (2017) A review of geophysical exploration technology for mine water disaster in China: applications and trends. Mine Water Environ 36(3):331–340
  • 12. Shi L, Wang Y, Qiu M et al (2019) Application of three-dimensional high-density resistivity method in roof water advanced detection during working stope mining. Arab J Geosci 12(15):464–474
  • 13. Tan L, Hu X, Zhang P et al (2015) Continous monitoring technology of parallel electrical method for the infiltration characteristics in the dam body. South-to-North Water Trans and Water Sci Technol 13(05):926–930
  • 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
  • 17. Yang C, Liu S, Wu R (2017) Quantitative prediction of water volumes within a coal mine underlying limestone strata using geophysical methods. Mine Water Environ 36:51–58
  • 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).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-714cdc3f-e72a-4cf2-ba3b-37b39fd51903
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