TY - JOUR ID - 1603 TI - Geostatistical Modeling of Electrical Resistivity Tomography for Imaging Porphyry Cu Mineralization in Takht-e-Gonbad Deposit, Iran JO - Journal of Mining and Environment JA - JME LA - en SN - 2251-8592 AU - Babaei, M. AU - Abedi, M. AU - Norouzi, Gh. H. AU - Kazem Alilou, S. AD - School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran Y1 - 2020 PY - 2020 VL - 11 IS - 1 SP - 143 EP - 159 KW - Electrical resistivity KW - Electrical Chargeability KW - Geostatistics KW - Inversion KW - Porphyry Cu DO - 10.22044/jme.2019.8709.1756 N2 - This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling. UR - https://jme.shahroodut.ac.ir/article_1603.html L1 - https://jme.shahroodut.ac.ir/article_1603_5574b4cc2a72bba664cba3f9db6a3e8c.pdf ER -