Abstract
The identification and delineation of concealed mineralized zones in settings with weak or overlapping anomalies remains a critical challenge. Conventional geophysical methods provide limited resolution and reliability in such conditions. To overcome this limitation, this study introduces a systematic framework that integrates fractal clustering and geophysical inversion to enhance the accuracy of mineral exploration. Induced polarization (IP) chargeability data, acquired using a rectangular array at the Kabudan gold prospect in northeastern Iran—an area characterized by the Lack of outcrops and surface indications of mineralization—were analyzed using four well-established fractal models: Concentration–Area (C–A), Concentration–Perimeter (C–P), Concentration–Number (C–N), and Number–Size (N–S). To quantitatively evaluate the performance of each model, four statistical validation indices were employed: Silhouette, Davies–Bouldin, Calinski–Harabasz, and cluster stability. Among these models, The C–P fractal model exhibited the highest clustering quality, with the highest Silhouette index (closest to 1 among the models), the lowest Davies–Bouldin index, the highest Calinski–Harabasz index, and the lowest Silhouette index standard deviation (highest cluster stability). To verify the subsurface continuity of the identified anomalies, Four geoelectrical profiles were acquired over the anomalous zones, and two-dimensional (2D) inversion of the induced polarization (IP) and resistivity data was performed. The data were subsequently modeled, and the corresponding cross-sections were generated to illustrate the subsurface variations. The inverted sections revealed coherent chargeable structures that closely corresponded to the clusters derived from the fractal models. The results were further assessed and validated using borehole data, where the correspondence between a high-grade gold-bearing sulfide zone and the anomalies delineated in the profiles confirmed the reliability and accuracy of the interpretations. Overall, the proposed integration of fractal clustering, geophysical inversion, and statistical validation not only enhances the interpretability of subsurface data under complex geological conditions but also provides a scalable and transferable framework for next-generation mineral exploration.
Similar content being viewed by others
Data availability
Data for this study is available from the corresponding author upon reasonable request.
References
Nazih, M., Gobashy, M. M., Khamis, H., El-Sadek, M. A. & Soliman, K. S. Singularity index and multifractal analysis of magnitude magnetic transforms: A new methodology to explore Au mineralization with application to Esh El Mallaha, Egypt. Sci. Rep. 15, 11010 (2025).
Deo, R. N. & Kodikara, J. Direct current resistivity and time domain induced polarization methods in soil corrosivity assessment for buried infrastructure. J. Appl. Geophys. 209, 104921 (2023).
Lenhare, B. D., Moreira, C. A. & Ilha, L. M. Gold ore identification in Santa Catarina Gabbro using electrical resistivity tomography (ERT) and visualization of mineralization in three dimensions, São Sepé, Rio Grande do Sul, Brazil. Geofísica Int. 62, 591–606 (2023).
Power, C., Tsourlos, P., Ramasamy, M., Nivorlis, A. & Mkandawire, M. Combined DC resistivity and induced polarization (DC-IP) for mapping the internal composition of a mine waste rock pile in Nova Scotia, Canada. J. Appl. Geophys. 150, 40–51 (2018).
Revil, A. et al. Field investigation of serpentinite with induced polarization and the K-means clustering technique. Geophys. Res. Lett. 51, e2024GL108920 (2024).
Ashari, I. F., Nugroho, E. D., Baraku, R., Yanda, I. N. & Liwardana, R. Analysis of elbow, silhouette, Davies-Bouldin, Calinski-Harabasz, and rand-index evaluation on k-means algorithm for classifying flood-affected areas in Jakarta. J. Appl. Inf. Comput. 7, 95–103 (2023).
Gobashy, M. M., El-Sadek, M. A. & Araffa, S. A. Gold Deposits in Egypt: Geology, Settings, Types, Genesis and Spatiotemporal Distribution 425–457 (Springer, 2025).
Afshar, A., Abedi, M., Norouzi, G. H. & Riahi, M. A. Geophysical investigation of underground water content zones using electrical resistivity tomography and ground penetrating radar: A case study in Hesarak-Karaj, Iran. Eng. Geol. 196, 183–193 (2015).
Afshar, A., Norouzi, G. H., Moradzadeh, A. & Riahi, M. A. Application of magnetic and gravity methods to the exploration of sodium sulfate deposits, case study: Garmab mine, Semnan, Iran. J. Appl. Geophys. 159, 586–596 (2018).
Mandelbrot, B. B. & Freeman, W. H. Fractal Geom. Nat. 468 (1983).
Farhadi, S., Afzal, P., Boveiri Konari, M., Daneshvar Saein, L. & Sadeghi, B. Combination of machine learning algorithms with concentration-area fractal method for soil geochemical anomaly detection in sediment-hosted Irankuh Pb-Zn deposit, central Iran. Minerals 12, 689 (2022).
Daya, A. A. Comparative study of C–A, C–P, and N–S fractal methods for separating geochemical anomalies from background: A case study of Kamoshgaran region, Northwest of Iran. J. Geochem. Explor. 150, 52–63 (2015).
Zuo, R., Xia, Q. & Zhang, D. A comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas. Appl. Geochem. 33, 165–172 (2013).
Heidari, S. M., Afzal, P. & Sadeghi, B. Molybdenum and gold distribution variances within Iranian copper porphyry deposits. J. Geochem. Explor. 261, 107471 (2024).
Karaman, M. et al. Delineation of the porphyry-skarn mineralized zones (NW Turkey) using concentration–volume fractal model. Geochemistry 81, 125802 (2021).
Cheng, Q. Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China. Ore Geol. Rev. 32, 314–324 (2007).
Chen, Z., Liu, Y. & Zhou, P. A comparative study of fractal dimension calculation methods for rough surface profiles. Chaos Solitons Fractals. 112, 24–30 (2018).
Ghezelbash, R., Maghsoudi, A. & Daviran, M. Combination of multifractal Geostatistical interpolation and spectrum–area (S–A) fractal model for Cu–Au geochemical prospects in Feizabad district, NE Iran. Arab. J. Geosci. 12, 152 (2019).
Carranza, E. J. M. Geochemical Anomaly and Mineral Prospectivity Mapping in GIS Vol. 11 (Elsevier, 2008).
Afzal, P., Khakzad, A., Maaref Vand, P., Rashid Nejad, N. A. & Harouni, A. Separation of mineralization zones in Kahang porphyritic copper deposit situated in Isfahan by means of modern concentration-volume fractal method. J. Earth Sci. 20 (81), 95–112 (2011).
Hassanpour, S. & Afzal, P. Application of concentration–number (C–N) multifractal modeling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran. Arab. J. Geosci. 6, 957–970 (2013).
Ferdows, M. S. & Ramazi, H. R. Application of the singularity mapping technique to identify local anomalies by polarization data (a case study: Hamyj copper Deposit, Iran). Acta Geod. Geoph. 50, 365–374 (2015).
Akbari, S., Ramazi, H. & Ghezelbash, R. Using fractal and multifractal methods to reveal geophysical anomalies in Sardouyeh District, Kerman, Iran. Earth Sci. Inf. 16, 2125–2142 (2023).
Stöcklin, J. Structural history and tectonics of Iran: A review. AAPG Bull. 52, 1229–1258 (1968).
Berberian, M. & King, G. Towards a paleogeography and tectonic evolution of Iran. Can. J. Earth Sci. 18, 210–265 (1981).
Lindenberg, H. G., Corler, K. & Ibbeken, H. Stratigraphy, Structur and orogenetic evolution of Sabzevar zone in the area of Oryan Khorasan, NE Iran, GSI, report, 51, Tehran (1982).
Muller, R. & Walter, R. Geology of the Precambrian-Paleozoic Taknar Inlier northwest of Kashmar, Khorasan Province northeast Iran (1983).
Karimpour, M. H., Farmer, G., Stern, C. & Salati, E. U-Pb zircon geochronology and Sr-Nd isotopic characteristic of Late Neoproterozoic Bornaward granitoids (Taknar zone exotic block), Iran (2011).
Jamali, F., Arab Amiri, A., Kamkar Rouhani, A. & Bahrami, A. Modeling of induced polarization and resistivity data for prospecting and exploration of polymetallic deposit in Kaboudan Area, East of Iran. J. Min. Environ. 12, 693–710 (2021).
Ghasemi Siani, M., Mehrabi, B. & Gholizadeh, K. Geology, mineralogy and geochemistry of Kabudan Fe-rich volcanogenic ore mineralization, North of Bardaskan, Taknar zone. Researches Earth Sci. 10, 253–272 (2020).
Azmi, H., Parviz, M. & Maghsoudi, A. Resource estimation of the Damanghor gold deposit, based on geology and grade continuity. Geopersia 10, 381–394 (2020).
Karimpour, M., Rahimi, B., Zirjanizadeh, S. & Salati, E. Petrology of intrusive rocks in Taknar mining area, Bardaskan (Iran) (2010).
Hashemi, M. & Afzal, P. Identification of geochemical anomalies by using of number–size (N–S) fractal model in Bardaskan area, NE Iran. Arab. J. Geosci. 6, 4785–4794 (2013).
Hashemi, M. et al. Geochemical anomaly separation by concentration-area fractal model in Bardaskan area, NE Iran. J. Min. Metall. 46, 1–10 (2010).
Hamami Pour, B., Tajeddin, H. & Barahmand, L. In Conference: 18th Symposium of the Geological Society of Iran (In Persian with Enlish abstract).
Abbasnia, H., Karimpour, M. & Malekzadeh Shafaroudi, A. Damanghor intermediate sulfidation epithermal Au mineralization, Northern bardaskan: Geology, alteration, mineralization, and geochemistry. Iran. J. Crystallogr. Mineralogy. 27, 621–634 (2019).
Daya, A. A., Biabangard, H. & Boomeri, M. Identification of anomalies using multivariate fractal modeling in the Maleksiahkuh region, SE Iran. Numer. Methods Min. Eng. 13–25 (2024).
Shafieyan, F. & Abdideh, M. Application of concentration-area fractal method in static modeling of hydrocarbon reservoirs. J. Pet. Explor. Prod. Technol. 9, 1197–1202 (2019).
Afzal, P., Khakzad, A. et al. Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system, central Iran. J. Geochem. Explor. 104, 34–46 (2010).
Cheng, Q., Agterberg, F. & Ballantyne, S. The separation of geochemical anomalies from background by fractal methods. J. Geochem. Explor. 51, 109–130 (1994).
Deng, J. et al. Delineation and explanation of geochemical anomalies using fractal models in the Heqing area, Yunnan Province, China. J. Geochem. Explor. 105, 95–105 (2010).
Sadeghi, B., Moarefvand, P., Afzal, P., Yasrebi, A. B. & Saein, L. D. Application of fractal models to outline mineralized zones in the Zaghia iron ore deposit, central Iran. J. Geochem. Explor. 122, 9–19 (2012).
Mohammadi, A. et al. Application of number–size (NS) fractal model for separation of mineralized zones in Dareh-Ashki gold deposit, Muteh Complex, central Iran. Arab. J. Geosci. 6, 4387–4398 (2013).
Acknowledgements
The authors would like to express their sincere gratitude to the Faculty of Mining Engineering at Amirkabir University of Technology for providing essential research facilities and a supportive academic environment throughout this study. Special thanks are extended to Kharazmi University for their valuable support and collaboration. The constructive comments and suggestions provided by colleagues and technical staff involved in the fieldwork are gratefully acknowledged. The authors also thank the anonymous reviewers for their insightful remarks that helped to improve the quality of this manuscript. Finally, the authors wish to thank Komeh Ma’dan Pars Co. generously providing access to exploratory data, which greatly contributed to the advancement of this research.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author information
Authors and Affiliations
Contributions
A.A. and H.R.R. developed the research concept and designed the methodology. S.M.S.J. and M.H. conducted the field surveys and processed the geophysical data. S.M.S.J., M.H., and A.A. performed the fractal clustering analyses and contributed to the development and validation of the algorithms. A.A. and S.M.S.J. prepared the figures and drafted the main text of the manuscript. H.R.R. provided critical insights into data interpretation and manuscript revision. S.A. assisted with field data acquisition and contributed to the interpretation of geophysical results. All authors discussed the results and reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Ethics approval
The authors confirm that this manuscript is their original work, has not been published previously, and is not currently under consideration by any other journal. No experiments involving human participants or animals were conducted as part of this research.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Sadatian Jouybari, S.M., Afshar, A., Ramazi, H. et al. Integrated fractal clustering and inversion of induced polarization data for concealed gold exploration in Kabudan area NE Iran. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38850-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-38850-8


