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3D inverse modeling of electrical resistivity and chargeability data through unstructured meshing, a case study for travertine exploration | ||
| International Journal of Mining and Geo-Engineering | ||
| مقاله 3، دوره 57، شماره 2، شهریور 2023، صفحه 131-140 اصل مقاله (1.61 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ijmge.2022.347290.594991 | ||
| نویسندگان | ||
| Mohammad Ali Talebi1؛ Seyed Hossein Hosseini2؛ Maysam Abedi* 1؛ Ali Moradzadeh* 1 | ||
| 1School of Mining Engineering, College of Engineering, University of Tehran, Iran | ||
| 2School of Mining Engineering, College of Engineering, University of Tehran, Iran. | ||
| چکیده | ||
| Geoelectrical methods are considered common subsurface geophysical imaging tools that provide significant insight into the electrical properties of targets. Considering the three-dimensional nature of subsurface structures, geoelectrical survey data and their 3D inverted models can yield reliable and accurate results. In this research, using an unstructured tetrahedral meshing, three-dimensional forward and inverse models of electrical resistivity and chargeability data were performed for geological structures with travertine layers. The Application of the unstructured mesh for the discretization of subsurface geological units increases the speed and accuracy of the modelling procedure, as well as the flexibility in designing and implementing meshing on tough topographies and the complex-shaped geometry of the target mass. Using an open-source and full-item Python software named ResIPy, the forward and inverse models were calculated and interpreted precisely. According to the geological background of the studied area, to investigate the applicability and efficiency of the 3D geoelectrical modelling method in imaging the subsurface travertine deposits, three synthetic scenarios were modeled according to the geological setting of the studied area. The results of the 3D inversion of the synthetic models indicated the accuracy and validity of this procedure in the exploration of underground travertine deposits. As a real case study, the electrical resistivity and chargeability survey datasets in the Atashkohe travertine mine were inverted in 3D, aimed to inferring schematic geological sections along the three surveyed profiles. The survey was conducted with electrode spacing of 10 and 15 meters, using a combination of dipole-dipole and pole-dipole arrays. Considering the two-dimensional nature of these data and the relatively large distance between the two main profiles, the three-dimensional inversion results may increase the error rate. Therefore, the 2D batch inversion was preferably utilized in order to obtain a more realistic and sensible geological model. According to the geological studies and instrumental analysis of the rock samples, three types of geological structures were identified throughout the study area. Based on the subsurface electrical characteristics inferred along each profile, three geological layers were designed to illustrate the underground structures. The comparison of the inferred geological models and the drilling results along one of the survey profiles demonstrated acceptable compatibility and concordance, indicating the efficiency of the research utilized approach. | ||
| کلیدواژهها | ||
| Electrical resistivity؛ Electrical chargeability؛ 3D inverse modeling؛ Atashkohe travertine؛ Unstructured mesh | ||
| مراجع | ||
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[1] Gadallah, M.R., Fisher, R., & Mamdouh, R. (2009). Exploration Geophysics. Berlin: Springer-Verlag Berlin Heidelberg. doi: http://doi.org/ 10.1007/978-3-540-85160-8
[2] Soleimani, K., Arab-Amiri, A. R., Kamkar Rouhani, A., Shamsaddini Nejad, M., & Momeni, F. (2019). Investigation of the accuracy of the results of geoelectrical surveys to determine the depth and thickness of bauxite layer in one of Jajarm bauxite deposits. JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS, 4, 225-235.
[3] Aristodemou, E., & Thomas-Betts, A. (2000). DC resistivity and induced polarization investigations at a waste disposal site and its environments. Journal of Applied Geophysics, 44, 275-302.
[4] Binley, A., & Daily, W. (2003). The performance of electrical methods for assessing the integrity of geomembrane liners in landfill caps and waste storage ponds. European Journal of Environmental & Engineering Geophysics, 8, 227-237.
[5] De Carlo, L., Perri, M. P., Caputo, M. C., Deiana, R., Vurro, M., & Cassiani, G. (2013). Characterization of a dismissed landfill via electrical resistivity tomography and mise-à-la-masse method. Journal of Applied Geophysics, 98, 1-10
[6] Qarqori, K., Rouai, M., Moreau, F., Saracco, G., Dauteuil, O., Hermitte, D., Veslud, C. (2012). Geoelectrical Tomography Investigating and Modeling of Fractures Network around Bittit Spring (Middle Atlas, Morocco). International Journal of Geophysics, 2012, 1-13. doi: https://doi.org/10.1155 /2012/489634. [7] Ramazi, H., & Mostafaie, K. (2013). Application of integrated geoelectrical methods in Marand (Iran) manganese deposit exploration. Arabian Journal of Geosciences, 6, 2961-2970
[8] Ferdows, S., & Ramazi, H. (2015). Application of the fractal method to determine the membership function parameter for geoelectrical data (case study: Hamyj copper deposit, Iran). Journal of Geophysics and Engineering, 12, 909-921.
[9] Mostafaie, K., & Ramazi, H. (2018). 3D model construction of induced polarization and resistivity data with quantifying uncertainties using geostatistical methods and drilling (Case study: Madan Bozorg, Iran). Journal of Mining and Environment, 9, 857-872. doi: https://dx.doi.org/10.22044 /jme.2018.6852.1516 [10] Yang, J., Liu, Z. H., & Wang, L. (2008). Effectiveness of Natural Field Induced Polarization for Detecting Polymetallic Deposits. Earth Science Frontiers, 15, 217-221.
[11] Flores, C., & Peralta-Ortega, S. (2009). Induced polarization with in-loop transient electromagnetic soundings: A case study of mineral discrimination at El Arco porphyry copper, Mexico. Journal of Applied Geophysics, 68, 423-436
[12] Daneshvar Saein, L., Rasa, I., Rashidnejad Omran, N., Moarefvand, P., & Afzal, P. (2012). Application of concentration-volume fractal method in induced polarization and resistivity data interpretation for Cu-Mo porphyry deposits exploration, case study: Nowchun Cu-Mo deposit, SE Iran. Nonliner Processes in Geophysics, 19, 431-438
[13] Gurin, G., Tarasov, A., Ilyin, Y., & Titov, K. (2015). Application of the Debye decomposition approach to analysis of induced-polarization profiling data (Julietta gold-silver deposit, Magadan Region). Russian Geology and Geophysics, 56, 1757-1771.
[14] Mashhadi, S., & Ramazi, H. (2018). The Application of Resistivity and Induced Polarization Methods in Identification of Skarn Alteration Haloes: a Case Study in the Qale-alimoradkhan Area. Journal of Environmental and Engineering Geophysics, 23(3), 363-368
[15] Öğretmen, Z., & Şeren, A. (2014). Investigating fracture–cracked systems with geophysical methods in Bayburt Kıratlı travertine. Journal of Geophysics and Engineering, 11(6), 1-13. doi: https://doi.org/10.1088/1742-2132/11/6/065009
[16] Grandjean, G., & Gourry, J. (1996). GPR data processing for 3D fracture mapping in a marble quarry (Thassos, Greece). Journal of Applied Geophysics, 36(1), 19-30. doi:https://doi.org/10.1016/S0926-9851(96)00029-8
[17] Kadıoğlu, S. (2008). Photographing layer thicknesses and discontinuities in a marble quarry with 3D GPR visualization. J. Appl. Geophys., 64, 109-114. doi:https://doi.org/10.1016/j.jappgeo.2008.01.001
[18] Porsani, L., Sauck, W., & Junior, A. (2006). GPR for Mapping fractures and as a guide for extraction of ornamental granite from a quarry: a case study from southern Brazil. J. Appl. Geophys., 58, 177–187. doi: https://doi.org/10.1016/j.jappgeo.2005.05.010
[19] Aydın, A., Yağız, S., Özpınar, Y., & Semiz, B. (2005, September 21-25). Investigation of travertine properties using geophysical methods. Proceedings of 1st International Symposium on Travertine.
[20] Yalçıner, C. (2013). Investigation of subsurface geometry of fissure–ridge travertine with GPR, Pamukkale, western Turkey. Journal of Geophysics and Engineering, 10(3). doi:https://doi.org/10.1088/1742-2132/10/3/035001
[21] Billi, A., Filippis, L., Poncia, P., Sella, P., & Faccenna, C. (2016). Hidden sinkholes and karst cavities in the travertine plateau of a highly-populated geothermal seismic territory (Tivoli, central Italy). Geomorphology, 255, 63-80. doi:https://doi.org/10.1016/j.geomorph.2015.12.011.
[22] Particle In Cell Consulting LLC (2015). Finite Element Particle in Cell (FEM-PIC). Westlake village, CA. https://www.particleincell.com/2015/fem-pic/.
[23] Loke, M. H. (1996-2011). Tutorial: 2-D and 3-D electrical imaging surveys.
[24] Chambers, J. E., Wilkinson, P. B., Wardrop, D., Hameed, A., Hill, I., Jeffrey, C., Gunn, D. A. (2012). Bedrock detection beneath river terrace deposits using three-dimensional electrical resistivity tomography. Geomorphology, 17-25.
[25] Doetsch, J., Linde, N., Vogt, T., Binley, A., & Green, A. G. (2012). Imaging and quantifying salt-tracer transport in a riparian groundwater system by means of 3D ERT monitoring. GEOPHYSICS, 207-218.
[26] Uhlemann, S., Chambers, J., Wilkinson, P., Maurer, H., Merritt, A., Meldrum, P., Dijkstra, T. (2017). Four-dimensional imaging of moisture dynamics during landslide reactivation. Journal of Geophysical Research: Earth Surface, 398-418.
[27] Blanchy, G., Saneiyan, S., Boyd, J., McLachlan, P., & Binley, A. (2020). ResIPy, an intuitive open-source software for complex geoelectrical inversion/modeling. Computers & Geosciences, 137. doi: https://doi.org/10.1016/j.cageo.2020.104423.
[28] Binley, A. (2020). The Lancaster Invironment Centre. Retrieved from http://www.es.lancs.ac.uk/people/amb/Freeware/Freeware.htm.
[29] Geuzaine, C., & Remacle, J. F. (2009). Gmsh: A 3-D finite element mesh generator with built-in pre-and post-processing facilities. International journal for numerical methods in engineering, 1309-1331.
[30] Abedi, M. (2020). A focused and constrained 2D inversion of potential feld geophysical data through Delaunay triangulation, a case study for iron-bearing targeting at the Shavaz deposit in Iran. Physics of the Earth and Planetary Interiors, 309, 106604.
[31] Abedi, M. (2022). Cooperative fuzzy-guided focused inversion for unstructured mesh modeling of potential field geophysics, a case study for imaging an oil-trapping structure. Acta Geophysica, DOI: 10.1007/s11600-022-00857-w.
[32] Danaei, Kh., Moradzadeh, A., Norouzi, G.H., Smith, R.S., Abedi, M., & Jodeiri Akbari Fam, H. (2022). 3D inversion of gravity data with unstructured mesh and least-squares QR-factorization (LSQR). Journal of Applied Geophysics, DOI: 10.1016/j.jappgeo.2022.104781.
[33] Talebi, M.A., Abedi, M., & Moradzadeh, A. (2022). Geoelectrical modeling of travertine rocks beneath a rough topographical relief using structured and unstructured meshes. Acta Geodaetica et Geophysica, 57, 351–372.
[34] Telford, W. M., Geldart, L. P., & Sheriff, R. E. (1990). Applied Geophysics. Cambridge: Cambridge University Press. doi: https://doi.org/10.1017/CBO9781139167932. | ||
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