مجله ژئوفیزیک ایران

مجله ژئوفیزیک ایران

Coupled hydrogeophysical finite-element modeling of subsurface flow and ion diffusion for porphyry copper exploration

مقالات آماده انتشار

نوع مقاله : مقاله پژوهشی‌

نویسندگان
Amir Yazdanpanah 1
Maysam Abedi 2
1 M.Sc., School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 Associate Professor., School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran
10.30499/ijg.2025.525910.1700
چکیده
Porphyry copper deposits play a critical role in global metal supply, emphasizing the need for non-invasive exploratory geophysical techniques to identify mineralized zones at depth. This study employs coupled hydro-geophysical finite-element modeling within the a 2D framework to simulate groundwater flow, ion diffusion, and time-lapse electrical resistivity in a plausible  geological domain representative of near-surface porphyry copper systems. The model considers fluid flow through layered geological units and a mineralized zone, while tracking ion transport to mimic copper leaching. Meanwhile, real-time electrical resistivity tomography (ERT) captures electrical resistivity variations induced by ion concentrations. Additionally, the ERT data are then inverted using the Conjugate Gradient Least Squares (CGLS) algorithm, allowing the reconstruction of four 2D electrical resistivity models that illustrate the evolution of the mineralized zone over time. The results highlight distinct flow and concentration patterns, with the inverted electrical resistivity models aligning with the velocity gradients from the forward simulations, improving the detection of the target zone. This integrated approach combines hydrological and geophysical perspectives, providing a scalable framework to optimize drilling strategies while minimizing environmental impact. This innovative approach serves as a non-invasive tool for the exploration of porphyry copper deposits, offering a highly effective methodoslogy for detecting mineral resources beneath the earth's surface. The precision and reliability of this exploration tool not only enhance the efficiency of mineral deposit identification but also contribute to more sustainable mining practices.
 
 
کلیدواژه‌ها
Porphyry copper, hydro-geophysical modeling, ion diffusion, time-lapse electrical resistivity (ERT)

موضوعات

عنوان مقاله English

Coupled hydrogeophysical finite-element modeling of subsurface flow and ion diffusion for porphyry copper exploration

نویسندگان English

Amir Yazdanpanah 1
Maysam Abedi 2
1 M.Sc., School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 Associate Professor., School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran
چکیده English

Porphyry copper deposits play a critical role in global metal supply, emphasizing the need for non-invasive exploratory geophysical techniques to identify mineralized zones at depth. This study employs coupled hydro-geophysical finite-element modeling within the a 2D framework to simulate groundwater flow, ion diffusion, and time-lapse electrical resistivity in a plausible  geological domain representative of near-surface porphyry copper systems. The model considers fluid flow through layered geological units and a mineralized zone, while tracking ion transport to mimic copper leaching. Meanwhile, real-time electrical resistivity tomography (ERT) captures electrical resistivity variations induced by ion concentrations. Additionally, the ERT data are then inverted using the Conjugate Gradient Least Squares (CGLS) algorithm, allowing the reconstruction of four 2D electrical resistivity models that illustrate the evolution of the mineralized zone over time. The results highlight distinct flow and concentration patterns, with the inverted electrical resistivity models aligning with the velocity gradients from the forward simulations, improving the detection of the target zone. This integrated approach combines hydrological and geophysical perspectives, providing a scalable framework to optimize drilling strategies while minimizing environmental impact. This innovative approach serves as a non-invasive tool for the exploration of porphyry copper deposits, offering a highly effective methodoslogy for detecting mineral resources beneath the earth's surface. The precision and reliability of this exploration tool not only enhance the efficiency of mineral deposit identification but also contribute to more sustainable mining practices.
 
 

کلیدواژه‌ها English

Porphyry copper, hydro-geophysical modeling, ion diffusion, time-lapse electrical resistivity (ERT)
Batayneh, A. T., and Al-Diabat, A. A., 2002, Akingboye, A. S., & Ogunyele, A. C. (2019). Insight into seismic refraction and electrical resistivity tomography techniques in subsurface investigations. Rudarsko Geolosko Naftni Zbornik, 34(1), 93–111. https://doi.org/10.17794/rgn.2019.1.9
Berger, B. R., Ayuso, R. A., Wynn, J. C., & Seal, R. R. (2008). Preliminary model of porphyry copper deposits. https://doi.org/10.3133/ofr20081321
Binley, A. (2015a). Tools and Techniques: Electrical Methods. Treatise on Geophysics: Second Edition, 11, 233–259. https://doi.org/10.1016/B978-0-444-53802-4.00192-5
Binley, A. (2015b). Tools and Techniques: Electrical Methods. In Treatise on Geophysics (pp. 233–259). Elsevier. https://doi.org/10.1016/B978-0-444-53802-4.00192-5
Christensen, N. K., Christensen, S., & Ferre, T. P. A. (2016). Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models. Hydrology and Earth System Sciences, 20(5), 1925–1946. https://doi.org/10.5194/hess-20-1925-2016
Field, D. A. (2000). Qualitative measures for initial meshes. International Journal for Numerical Methods in Engineering, 47(4), 887–906. https://doi.org/10.1002/(SICI)1097-0207(20000210)47:4<887::AID-NME804>3.0.CO;2-H
González-Quirós, A., & Comte, J.-C. (2021). Hydro-geophysical model calibration and uncertainty analysis via full integration of PEST/PEST++ and COMSOL. Environmental Modelling & Software, 145, 105183. https://doi.org/10.1016/j.envsoft.2021.105183
Hinnell, A. C., Ferré, T. P. A., Vrugt, J. A., Huisman, J. A., Moysey, S., Rings, J., & Kowalsky, M. B. (2010). Improved extraction of hydrologic information from geophysical data through coupled hydro-geophysical inversion. Water Resources Research, 46(4). https://doi.org/10.1029/2008WR007060
Johnson, T. C., Versteeg, R. J., Ward, A., Day-Lewis, F. D., & Revil, A. (2010). Improved hydro-geophysical characterization and monitoring through parallel modeling and inversion of time-domain resistivity andinduced-polarization data. GEOPHYSICS, 75(4), WA27–WA41. https://doi.org/10.1190/1.3475513
Lesmes, D. P., & Friedman, S. P. (2005). Relationships between the Electrical and Hydrogeological Properties of Rocks and Soils (pp. 87–128). https://doi.org/10.1007/1-4020-3102-5_4
Linde, N. (2014). Falsification and corroboration of conceptual hydrological models using geophysical data. WIREs Water, 1(2), 151–171. https://doi.org/10.1002/wat2.1011
Linde, N., Renard, P., Mukerji, T., & Caers, J. (2015). Geological realism in hydrogeological and geophysical inverse modeling: A review. Advances in Water Resources, 86, 86–101. https://doi.org/10.1016/j.advwatres.2015.09.019
Lovell, M. A., & Pezard, P. A. (1990). Electrical properties of basalts from DSDP Hole 504B: a key to the evaluation of pore space morphology. Geological Society, London, Special Publications, 48(1), 339–345. https://doi.org/10.1144/GSL.SP.1990.048.01.28
Lu, B., Zhang, X., & Dai, Z. (2024). A CGLS-based method for solving magnetic moments of hybrid-model magnetic targets. Measurement Science and Technology, 35(7), 076119. https://doi.org/10.1088/1361-6501/ad3c5c
Mazáč, O., Kelly, W. E., & Landa, I. (1985). A hydro-geophysical model for relations between electrical and hydraulic properties of aquifers. Journal of Hydrology, 79(1–2), 1–19. https://doi.org/10.1016/0022-1694(85)90178-7
Moysey, S. (2007). Hydrogeophysics. Groundwater, 45(1), 8–8. https://doi.org/10.1111/j.1745-6584.2006.00286.x
Notario del Pino, J., & Díaz, R. (1998). Pesticide distribution and movement. Biotherapy, 11(2/3), 69–76. https://doi.org/10.1023/A:1007961524517
Nwankwoala, H., & Udom, G. (2009). Hydrogeophysics: An overview of general concepts, applications and future perspectives. Scientia Africana, 7(2). https://doi.org/10.4314/sa.v7i2.46018
Østerby, O. (2002). Five Ways of Reducing the Crank-Nicolson Oscillations. DAIMI Report Series, 31(558). https://doi.org/10.7146/dpb.v31i558.7115
Portniaguine, O., & Zhdanov, M. S. (1999). Focusing geophysical inversion images. In GEOPHYSICS (Vol. 64, Issue 3). http://library.seg.org/
Rücker, C., Günther, T., & Wagner, F. M. (2017). pyGIMLi: An open-source library for modelling and inversion in geophysics. Computers and Geosciences, 109, 106–123. https://doi.org/10.1016/j.cageo.2017.07.011
Warburton, T., & Hagstrom, T. (2008). Taming the CFL Number for Discontinuous Galerkin Methods on Structured Meshes. SIAM Journal on Numerical Analysis, 46(6), 3151–3180. https://doi.org/10.1137/060672601
Yazdanpanah, A., & Abedi, M. (2024). Geophysical simulation of landslide model based on electrical resistivity and refraction seismic tomography through unstructured meshing. International Journal of Mining and Geo-Engineering, 58(3), 263–270. https://doi.org/10.22059/ijmge.2024.370406.59.
مجله ژئوفیزیک ایران

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