Generalization of numerical quasiconformal mapping methods for geological problems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.215045

Keywords:

electrical resistivity tomography, quasiconformal mappings, identification, inverse problems, numerical methods

Abstract

A method for identifying parameters of the conductivity coefficient of objects is generalized for the case of reconstructing an image of a part of a soil massif from the tomography data of the applied quasipotentials. In this case, without diminishing the generality, the reconstruction of the image is carried out in a fragment of a rectangular medium with local bursts of homogeneity present in it. The general idea of the corresponding algorithm consists in the sequential iterative solution of problems on quasiconformal mappings and identification of the parameters of the conductivity coefficient, with an insufficient amount of data on the values of the flow functions on the “inaccessible” part of the boundary. The image was reconstructed according to the data obtained using a full-range gradient array. The developed approach, in comparison with the existing ones, has a number of advantages that make it possible to increase the accuracy of identification of the conductivity coefficient. Namely, it provides an increase, in a qualitative sense, in the amount of input data, allows avoiding the use of Dirac delta functions when modeling areas of application of potentials and sufficiently flexibly take into account the mathematical aspects of the implementation of a quasiconformal mapping of a finite fragment of a half-plane onto a parametric polygon (domain of a complex quasipotential). The solution of the corresponding problem, in particular, occurs not in a single (fixed) investigated fragment of a rectangular soil massif, but in a number of smaller subdomains of the same shape, in the proposed optimal sequence. This saves machine time significantly. The prospects for further practical implementation of the proposed method follow from its ability to give an approximate result with relatively low costs (financial, time)

Author Biographies

Andrii Bomba, National University of Water and Environmental Engineering Soborna str., 11, Rivne, Ukraine, 33028

Doctor of Technical Sciences, Professor

Department of Computer Science and Applied Mathematics

Mykhailo Boichura, National University of Water and Environmental Engineering Soborna str., 11, Rivne, Ukraine, 33028

PhD

Research Department

Bohdan Sydorchuk, National University of Water and Environmental Engineering Soborna str., 11, Rivne, Ukraine, 33028

PhD, Associate Professor

Department of Automation, Electrical Engineering and Computer-Integrated Technologies

References

  1. Holder, D. (Ed.) (2004). Electrical Impedance Tomography. Methods, History and Applications. CRC Press, 456. doi: https://doi.org/10.1201/9781420034462
  2. Loke, M. H. (2020). Tutorial: 2-D and 3-D electrical imaging surveys. Available at: https://www.geotomosoft.com/coursenotes.zip
  3. Pekker, Ya. S., Brazovskiy, K. S., Usov, V. Yu., Plotnikov, M. P., Umanskiy, O. S. (2004). Elektroimpedansnaya tomografiya. Tomsk: NTL, 192.
  4. Kanli, A. I. (Ed.) (2019). Applied Geophysics with Case Studies on Environmental, Exploration and Engineering Geophysics. London: IntechOpen. doi: https://doi.org/10.5772/intechopen.78490
  5. Dahlin, T., Zhou, B. (2005). Multiple-gradient array measurements for multichannel 2D resistivity imaging. Near Surface Geophysics, 4 (2), 113–123. doi: https://doi.org/10.3997/1873-0604.2005037
  6. Herwanger, J. V., Pain, C. C., Binley, A., de Oliveira, C. R. E., Worthington, M. H. (2004). Anisotropic resistivity tomography. Geophysical Journal International, 158 (2), 409–425. doi: https://doi.org/10.1111/j.1365-246x.2004.02314.x
  7. Pessel, M., Gibert, D. (2003). Multiscale electrical impedance tomography. Journal of Geophysical Research: Solid Earth, 108 (B1). doi: https://doi.org/10.1029/2001jb000233
  8. Bomba, A. Ya., Kashtan, S. S., Pryhornytskyi, D. O., Yaroshchak, S. V. (2013). Metody kompleksnoho analizu. Rivne: Natsionalnyi universytet vodnoho hospodarstva ta pryrodokorystuvannia, 430.
  9. Bomba, A. Y., Kuzlo, M. T., Michuta, O. R., Boichura, M. V. (2019). On a method of image reconstruction of anisotropic media using applied quasipotential tomographic data. Mathematical Modeling and Computing, 6 (2), 211–219. doi: https://doi.org/10.23939/mmc2019.02.211
  10. Bomba, A., Boichura, M. (2017). On a numerical quasiconformal mapping method for the medium parameters identification using applied quasipotential tomography. Mathematical Modeling and Computing, 4 (1), 10–20. doi: https://doi.org/10.23939/mmc2017.01.010
  11. Aguiar e Oliveira Junior, H., Ingber, L., Petraglia, A., Rembold Petraglia, M., Augusta Soares Machado, M. (2012). Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing. Heidelberg: Springer-Verlag. doi: https://doi.org/10.1007/978-3-642-27479-4
  12. Rymarczyk, T., Adamkiewicz, P. (2017). Monitoring damage and dampness in flood embankment by electrical impedance tomography. Informatics Control Measurement in Economy and Environment Protection, 7 (1), 59–62. doi: https://doi.org/10.5604/01.3001.0010.4584
  13. Ulyanchuk-Martyniuk, O., Michuta, O., Ivanchuk, N. (2020). Biocolmation and the finite element modeling of its influence on changes in the head drop in a geobarrier. Eastern-European Journal of Enterprise Technologies, 4 (10 (106)), 18–26. doi: https://doi.org/10.15587/1729-4061.2020.210044

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Published

2020-10-31

How to Cite

Bomba, A., Boichura, M., & Sydorchuk, B. (2020). Generalization of numerical quasiconformal mapping methods for geological problems. Eastern-European Journal of Enterprise Technologies, 5(4 (107), 45–54. https://doi.org/10.15587/1729-4061.2020.215045

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Section

Mathematics and Cybernetics - applied aspects